hackathon_id int64 1.57k 23.4k | project_link stringlengths 30 96 | full_desc stringlengths 1 547k ⌀ | title stringlengths 1 60 ⌀ | brief_desc stringlengths 1 200 ⌀ | team_members stringlengths 2 870 | prize stringlengths 2 792 | tags stringlengths 2 4.47k | __index_level_0__ int64 0 695 |
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10,276 | https://devpost.com/software/homeworkedlinked | Inspiration
Despite in different countries, Arushi in USA and Matthew in South Africa, they were able to find that they face the same challenges as highschoolers. Whenever help needed is needed on a problem, it can be difficult sometimes to approach others and find tutors who would match your learning style and be able to clear any questions. Our inspiration was to help students overcome that fear of asking help and provide them with the chance to get help from mentors but at the same time have the chance to help someone else.
What it does
HomeworkedLinked is a platform that allows any students to sign up for a free tutor and get help on different subjects. In return other students can volunteer to become a tutor.
How we built it
We build it using PHP, CSS, and Hack
Challenges we ran into
Living in different countries, the time difference made it difficult to communicate as a team efficiently. However, with clear vision and tasks in mind, we were able to bring the idea to life.
Accomplishments that we're proud of
Bringing our idea to life and the being to find a solution to problems that we faced is something that we are really proud of.
What we learned
HomeworkedLinked gave us the opportunity to explore the lack of educational resources in certain areas and also the work being done to help these students. We learned about the United Nations Sustainable Development Goals and they work they are doing to help Goal 4, Quality Education. As supporters of this goal, we learned on how we can make an impact of students' lives through HomeworkedLinked .
What's next for HomeworkedLinked
HomeworkedLinked will continue grow as platform in terms of user friendliness, but also scalability. First of all, HomeworkedLinked 2.0 would have many features pertaining to the daily essentials of a students and different features to aid them. Additionally, this platform is highly scalable. Being in two different countries, we can grow the platform from our school to communities. The strength of the network will also grow as the number of users grow, for scalability. We could also partner with schools and make this a primary resource for their students, especially under privileged schools.
Built With
css
hack
php
Try it out
github.com
homeworklinked.com | HomeworkedLinked | Connecting youth to help youth | ['Arushi Aggarwal', 'Matthew Schaefer'] | [] | ['css', 'hack', 'php'] | 11 |
10,276 | https://devpost.com/software/ar-portal-ios-app | Inspiration
When the pandemic began, the lockdown started and everything got indoors then the urge to travel, to explore new worlds,the desire to feel free while travelling inspired us to come up with this idea of
ANYWHERE DOOR
and work towards it's development.
We were all beginners at the moment but the will to create something interesting, to be able to live that moment of turning our imagination into reality kept us moving and motivated. When it finally could be made we called it the
DREAM PORTAL
which truly became a source of turning our dreams true, we were able to live that moment of joy and experience life once again!
## What it does
The app which we have created lets the user enter a desired location and then creates a virtual door through which one can enter into the the location virtually and experience that place with a 360° view and also can see the room left behind himself on the other end of the door which makes this project all the way more charismatic.
How We built it
We first started gaining information as to how and what skills were required in our process which took a long time as we were all beginners but we finally came across unity engine and learned how to work on that within three days and also we worked on A-frame to finalize the project. The incorporation of the 360° view gave us a really hard time and we were not able to move forward but after watching a lot of tutorials, we finally made our
DREAM PORTAL
.
Challenges We ran into
When the whole code was prepared and finalized, the task of uploading it to GitHub became really difficult as GitHub would not accept the code as it is so we had to break it into chunks of code and then upload it and that took a lot of time and made us anxious as to what would happen if we were not able to upload the code in time, but in the end we were able to make it and proceed further.
Accomplishments that We're proud of
When we first started we were complete beginners but as we progressed with our work we learnt a lot and have grown as developers. The project that we were able to make, gives me the confidence that we will give a tough competition to others and not only do we strive to compete but also strive to win this hackathon!
What we learned
We learnt a quite a number of things like the Unity Engine, A-frame.
Then we learnt never to give up and keep solving the problem until its resolved. This project not only increased our skills but also our confidence and motivation to keep growing and learning.
What's next for AR-portal-Ios-App
We Will Create an application in which we will integrate
Google Maps
with our Idea and whenever the user will search a location, they will be able to experience how it feels to be there! Not only that we will integrate the nearby hotels and stores along with the view of the location. And we will keep updating it further.
Built With
c
c++
html
objective-c
objective-c++
shell
Try it out
github.com
www.canva.com | DREAM PORTAL | where imagination meets reality. | ['bruce waybe', 'Maninder Singh', 'Ruhee Jain'] | ['Certified Dank'] | ['c', 'c++', 'html', 'objective-c', 'objective-c++', 'shell'] | 12 |
10,276 | https://devpost.com/software/geometry-knight | scene view
game view 1
game view 2
project inspector1
code1
code4
project inspector2
code2
code3
Inspiration
I believe every child should have access to a strong foundation. As the gap between different socioeconomic classes increases, the best way to combat this problem is through bolstering education with technology. As a kid I always loved playing games and now I love making games, so I thought it would be perfect to create a little game that teaches kids to recognize shapes.
What it does
The game spawns various shapes and thee user has to input the same shape using keys on the keyboard. The circle corresponds with the letter "A" on the keyboard, the square with "S" and the triangle with "D." The user loses when the wrong shape is sent out, and the game automatically restarts.
How I built it
I used Unity to built and render the project.
Additionally, I also downloaded a free asset to help get started. I cropped my own photos as well to create some of the game objects.
Challenges I ran into
Figuring out why when the enemy objects were being spawned/instantiating they were not appearing on the game view even though they were on the scene view. I solved this by playing around with the "near" and "far" clippings on thee main camera object.
I also ran into an issue with detecting collisions. I resolved that by enabling the "on Trigger" function on certain objects.
Accomplishments that I'm proud of
Completing the project.
What I learned
Coding games is incredibly fun!
What's next for Geometry Knight
More shapes and keeping track of the score.
Built With
c#
unity
Try it out
connect.unity.com
github.com | Geometry Knight | By the age 5, a child’s brain develops more than at any other time in life. That's why early learning is critical. Our game addresses this issue by developing shape recognizing skills in young kids. | ['Annie Zhu', 'Karen Yuan', 'Sam Lim'] | [] | ['c#', 'unity'] | 13 |
10,276 | https://devpost.com/software/opportunity-dashboard | Home page
Communities List
Create a community
Create a post/opportunity
post list
Community Page
Inspiration
There are many opportunities in the world for students. We saw things like teachers emailing about events, schools announcing fairs, and website with info on just hackathons or just computer science opportunities. We wanted to create a one-stop site where students, teachers, schools, companies, and organizations can post about opportunities that would reach high schoolers around the world. The world of COVID-19 was also a major factor in creating this project. We saw many other's summer plans canceled and the amount of easily accessible opportunities available have also diminished. This project was designed with this issue in mind and we wanted to be the bridge for students and organizations in finding their opportunities.
What it does
Opportunity Dashboard is a fully functional cloud platform that displays opportunities that are available to everyone whether they're hackathons, internships, or online webinars. It's a hub for those who are looking for something of a particular subject or those who are searching for their passion. Our platform is organized in a manner so that the most popular opportunities and the most recent ones can effectively reach everyone. Organizations can use our platform so that they can find the right person to help and guide or connect with for an important opportunity. Everyone's opportunity is important whether they're big or small but every one of them needs to reach someone and our site does just that.
How we built it
We use Flask and MongoDB to power our backend and HTML 5, Jinja templating, CSS, and JS to create the frontend. Together we created a dynamic site where content can be created, edited, and viewed.
Challenges we ran into
We faced some challenges such as finding the right service to host our online cloud platform. The team ultimately decided to use Heroku and MongoDB for our server provider and cloud database. There were troubles in designing the login user system, for the third-party packages that we used didn't exactly support our cloud database modules. After reading the documentation, the User class could have been overwritten following a set of constraints. We completely redesigned the User class to fit out MongoDB modules.
Accomplishments that we're proud of
We're proud of redesigning the User class. This turned out to be a great boost for our project for we were able to quickly adapt our database models for posting Opportunity data objects and grouping them in Community data instances. We are also proud of creating a responsive site that makes viewing and creating items simple and quick.
What we learned
We learned how to use new cloud technologies and reprogram certain classes based on documentation and online research. Designing the front end also required us to go beyond our comfort zones and code CSS. The team isn't well versed in frontend-design but a member of our team invested time to create a responsive and clean frontend. We also learned how to create dynamic forms and dynamically connect posts to the "posts" page and their respective communities.
What's next for Opportunity Dashboard
Opportunity Dashboard is set up and ready to run for students right now but it can also be shipped as a website for schools to use for internal events. We have a couple of things we would want to add:
Geolocation data so posts can be filtered by location
allow users to follow communities and receive notifications on new posts as well as have the home page be fit for their liking. We would use algorithms to show the most relevant posts based on user interest to improve user's experience on the website.
We would also want to improve forms and how we manipulate our data to create a faster more optimized website.
Connect to paid cloud services that can deliver to many students across the nation or world with ease and scale to account for increased loads.
Create a system to handle images to upload so we can use a cloud CDN to decrease load times and improve files sizes
Improve DateTime use, use UTC to make time consistent and display time to post on posts to give more information to users
Built With
css3
flask
html5
javascript
mongodb
python
Try it out
github.com
oppspoilt.herokuapp.com | Opportunity Dashboard | A cloud platform for students to access opportunities and organizations to provide them. | ['Rafael Cenzano', 'Cap Lee', 'Joshua Pan', 'George Shao'] | [] | ['css3', 'flask', 'html5', 'javascript', 'mongodb', 'python'] | 14 |
10,276 | https://devpost.com/software/masterprofile | Screenshot 4
Screenshot 2
Screenshot 3
Screenshot 1
Screenshot 5
Screenshot 6
Inspiration
We’ve all been part of the job process. It’s a long, gruesome process, where we have to create a resume, send it to the employer, and get a response many weeks later. We decided to create a simple, but revolutionary platform and standard to allow employers to receive information about potential employees.
What it does
MasterProfile is a web application that has one input and two outcomes. First, the user inputs their entire profile and portfolio. They add items such as jobs, achievements, projects, skills, their bio, and more. For the first outcome, we auto-generate a completely free portfolio website for them that they can customize. They can share this website with anyone.
The second outcome is based on our token system. Each user is assigned a token, and with that token, companies and employers can access the profile and portfolio of the user through our API. Our API has extensive documentation that employers can use. Our API is also built on our standard. We standardize the way users’ portfolio data is presented. No more hand-reading resumes with missing information and everything in different places. Our standardized API creates opportunities for portfolio automation and analysis. Along with the standardization comes new business models and opportunities. For example, if an employer wants to find which candidate is the best match, they can use a product which offers a rating to each candidate based on the job requirements, through machine learning. There can be entire products that are focused on assigning ratings to job candidates! This presents endless opportunities for companies and users alike.
How we built it
This project required extensive backend and frontend development. The UI of our project was built using the Materialize CSS framework. Meanwhile, the backend of our project was built with Flask, the python-based web micro-framework. We are using Heroku to host our project, and we are also using a PostgreSQL database to handle user information and portfolios.
Our UI design process was a multi-step process that was used to ensure the quality of the UI and UX. First, we wireframed our UI using Balsamiq. Then, we designed the rough UI with HTML, CSS, and JavaScript, using Materialize CSS. After that, we combined our frontend and backend to finish the UI. Finally, we quality controlled our UI and UX through testing. Our landing page was built with Bootstrap Studio, a WYSIWYG HTML editor.
Creating the backend was also a multi-step process. First, we created database models using SQLAlchemy, and created forms using Flask-WTforms. We eventually did the login and register pages, and then the portfolio management pages. Soon after, we wrote the code that auto-generated portfolio websites for every user. Finally, we wrote the API which allowed the companies and employers to get the data of users through the secure token. The API reference was generated using Stoplight.
Challenges we ran into
We ran into multiple challenges when creating MasterProfile. The first challenge we ran into was allowing users to customize their portfolio websites. We had to use an unfamiliar Python library, Colour, to handle the color choosing aspect of our customization aspect. Another challenge was designing the landing page, known as the “How it works” page. That page was not designed using Materialize CSS, rather it was designed using Bootstrap Studio and a Bootstrap Studio template. We also had a particularly hard time of designing the way the user’s portfolio would be displaying, with Materialize carousels. For the backend, we had an issue developing the API, and returning the data in JSON format, so we developed our own method of returning the user’s information in JSON format.
Accomplishments that we're proud of
We are proud that we built a fully-functioning web application with an extensive backend and stunning frontend. We are also proud of API, which allows employers to make data-driven decisions on who to employ.
What we learned
Delegation & Teamwork
We learned how to delegate tasks and assign tasks for different group members, so we could work simultaneously. For example, if Vishnu was working on the backend and the login and register pages, Lavan would be designing and building the frontend for those pages, and Pranav would be creating the associated database models. This delegation allowed us to work efficiently.
Other
We also learned how to wireframe our application with Balsamiq. Along with that, we learned how to create an API with a secure token system, as well as how to write API documentation using Stoplight.
What's next for MasterProfile
First, we plan on defining an elaborate standard for the way the portfolio and profile information of a user is presented. We will expand this standard from what we have now with multiple additions. We will also work towards patenting the standard and marketing it to expand its usage.
Next, we plan on creating a machine learning integration for our product. We want to create a product that assigns ratings to potential candidates based on a list of requirements for a job. This will allow employers and companies to simplify their hiring process.
Built With
cloudinary
css3
flask
html5
javascript
jquery
python
Try it out
masterprofile.herokuapp.com
github.com | MasterProfile | MasterProfile is a simple yet powerful web application designed to revolutionize the way employers get information about potential candidates. | ['Pranav Rao', 'Lavan Surendra', 'Vishnu S.'] | [] | ['cloudinary', 'css3', 'flask', 'html5', 'javascript', 'jquery', 'python'] | 15 |
10,276 | https://devpost.com/software/move-egaxjk | GIF
Inspiration
When partaking in an activity so general and essential as buying groceries, it is easy to neglect the labor intensive aspect of bringing in groceries. Moreover, for some, such as the injured, elderly and disabled members of our society, the minor burden of bringing groceries into one’s house becomes a monumental, and in some cases, impossible, task
Foods such as milk, which clocks in at approximately 8.6 lbs and rice bags, which can reach over 50 lbs., which are ubiquitous in homes, turn what should be a simple trip to the grocery store, to a process that is expensive and cumbersome at best to impossible at worst.
Simply put, our society does not have adequate accommodations for something as essential for grocery shopping. While there are ample services and employees within groceries to help address this issue, their help stops short at the grocery store and serves no help to those suffering from arthritis, for example. Especially as over 25% of senior citizens aged 60 and older live by themselves in the United States, this issue becomes increasingly more problematic.
With these dire issues in mind, we sought to create MOVE, an autonomous assistive robot for grocery unloading; one that is designed to assist the injured, elderly or disabled people of our society.
What it does
Move is designed to be an autonomous grocery carrying robot, designed specifically to help elderly, disabled, and injured people with the essential task of bringing in groceries. The robot interfaces with a mobile application in order to call the robot to pick up the groceries. The setup occurs in the mobile app, where parameters are sent to the robot which describes the path that the robot must take to the trunk of the car. Additionally, the user is given the ability to prompt the robot to unload the groceries, once again through the mobile app.
On the hardware side, in order to facilitate the movement of groceries, MOVE implements a spinning storage plate which serves as an area to store bags while in transport, increasing efficiency by allowing multiple grocery bags to be delivered in a single trip. The rotating aspect of this subsequently allows for these bags to be dropped off without unnecessary movement of the robot. When MOVE is ready to unload the bags, it keeps the claw at a stationary position and rotates the storage plate to allow the claw access to the various grocery bags. Following the common theme, this can also store other items that need to be transported.
How we built it/How it works
The mobile application is written in Swift, using SwiftUI. The app communicates with an ESP8266 NodeMCU module through WiFi, specifically through a web server. The workflow of this infrastructure works by the iOS app making get and post requests to the flask webserver, and the robot doing similarly. For instance, when submitting coordinates in the app, the app makes a POST request to the server, and subsequently, via the Esp module, the robot can make a GET request to get these values. The robot parses the JSON and processes the data. The advantage of this is that it works through wifi, making this a solution that is not dependent on factors such as distance from the robot, as would be a critical limitation of technologies such as bluetooth. Finally, the flow of data concludes with the passage of data from the esp to the v5 brain via serial communication. The brain uses RS485 communication whereas the ESP requires UART, so an integrated circuit ship was used that allowed for the connection between the microcontrollers. The TI SN65HVD178 allows for a half-duplex communication to go both ways through the use of a control wire that switches between receive and transmit with LOW and HIGH respectively.
The chassis of the robot was designed and constructed with four omni wheels in a standard tank drive configuration. Each wheel is directly driven by a 200rpm brushed DC motor. The skeleton of the chassis is also designed and constructed with aluminum C-channel bars.
Moving up the robot we reach the turntable. It is constructed with a 0.08” thick lexan sheet cut to a circle with a diameter of a yard. This is then secured to a 84 tooth gear 2.1Nm torque DC motor, on a 1:7 gear reduction for a combined torque of 14.7 Nm torque for the rotation of heavier objects. This skeleton of this system is braced by vertical and triangular supports to better endure the weight.
Next, is the two stage chain bar system with a unique arrangement of sprockets, and chain. A single stage chain bar is able to keep the two opposing ends parallel no matter how the arm moves. This is accomplished by a careful assembly that moves only the front sprocket and chain by lockinging the back sprocket’s rotation. We realized this has limitations to its motions so we brainstormed a two staged system for the chain. This means the first stage will move (1:7 gear reduction) while keeping the second stage oriented, and the second stage (also 1:7 gear reduction) can move with changing the orientation of the claw, allowing for a variety of complex V-shaped motions and increased maneuverability.
Finally, the end sprockets are attached to a claw. This aluminum framed claw is created using C-channels and a gear reduction of 1:5 powered by a 100 rpm brushed DC motor in order to have enough torque to grab items securely and reliably. Lastly, we added sheets of anti slip matting on the inner surfaces of the claw to reduce slippage and padding to the items we are grabbing.
The robot code uses odometry combined with a pure pursuit controller to travel. Based on the odometry, a path is calculated that consists of an array of coordinates that the robot moves along. The robot uses encoders and an inertial motion unit to detect its own heading and absolute position. The pure pursuit controller calculates the next point of incidence on the path, and using the data from the odometry calculations to get the robot’s absolute position, generates a circle that connects the two points. A robot can easily move along a circle since the drive used is a differential drive i.e. the robot turns by powering the right and left sides differently. We used the difference in chassis speed as a function of radius, and the pure pursuit algorithm takes in R, and calculates the difference in motor speeds. This constitutes the feedforward loop in response to the feedback from the odometry calculations. The algorithm then identifies the next reference point. There is also a 2D motion profiler running on top of the motion so that there is a clean acceleration curve so that the error is minimized, and to have the least jerk and least overshoot in each motion to the next reference point.
Accomplishments we’re proud of
We are proud of our unique adaptive robot algorithms that use feedback and feed-forward control systems so the robot takes inputs from the physical world and reacts and calculates its motions accordingly. We are also proud of the wireless communication we were able to develop in the short amount of time as it is our teams first time ever working with wireless communication methods via WiFi modules. Similarly, we are also proud of the app that communicates via WiFi with the robot. We are especially proud of the user interface we were able to create, which is designed to be aesthetically pleasing, as well as intuitive. Thinking about, visualizing the design, as well as using design tools like Figma took a significant amount of effort, so we are extremely happy about how the UI turned out. We also take much pride in our unique mechanics. The two stage chain bar adds reliable, smooth, precise movements for the claw’s path. This was the first time our team ever made such a mechanism or something remotely similar. The complexity of this robotic manipulator combines multiple different basic and advanced base mechanisms to widen the range of the manipulator.
Challenges we ran into
Covid-19 acted as a significant barrier when working on this project. MOVE entails a significant hardware component, and the physical nature of this project made it more difficult for us to collaborate effectively. The way we got around this hurdle was through a strict division of roles with this project. However, this solution inadvertently resulted in other issues, such as the difficulty that arose from ensuring that every part of the project can communicate with the other parts so that a stable workflow can be established.
We also faced issues with the execution as well, simply because we were developing our own algorithms for the robot’s motions and had to do numerous article searches to learn about some more new advanced algorithms in order to accomplish the motions on the robot with the physical factors: momentum, friction`, etc.
What we learned
Mechanically, we learned/developed a new method of maintaining orientation of the end of an arm by physical means even though the arm is able to bend V-shaped and even straighten out.
Software and electronically, we learned how to code and wire a WiFi board, ESP-8266. We learned how to also integrate two very different MCUs. Lastly, we learned how to use image processing in order to detect the bags,
Team wise, with the challenge of social distancing, we had to learn to be more efficient debugging especially with such a project that heavily focuses on the use of software being integrated with hardware/mechanics. We learned to communicate problems and solutions faster by having a schedule and setting strict time periods where we must call and check up where each subsystem is at in its development.
What’s next for MOVE
On the mobile app end, with more phones implementing LiDARS allowing for more accurate AR, the user could potentially map out the area where the robot will be used and select an end point or a location for the robot to move to using his/her finger rather than manually plugging in the coordinates.
However, a key advantage of how we designed this system is in its extensibility. With only a few changes to only a few parts of the system, we can effectively address other issues commonly faced consisting of heavy-object lifting. A few of such applications would be box stacking or flight baggage handling to prevent back injuries. These applications would require a more robust motor.
Built with
C++, Swift (SwiftUI), C (Arduino), VEX Robotics Hardware, python (flask)
Built With
arduino
c
c++
flask
python
swift
vex
Try it out
github.com | MOVE | MOVE is a project designed to assist the injured, elderly, or disabled with grocery unloading using robotic and software components. MOVE is easy to configure, and can have several uses. | ['Jay Katyan', 'Shishir Sudhaman', 'CHRISTIAN SO', 'Rohan Minocha'] | [] | ['arduino', 'c', 'c++', 'flask', 'python', 'swift', 'vex'] | 16 |
10,276 | https://devpost.com/software/covid19-kit | dashboard
please check video for the features of the app
booking an appointment with the proctor/ faculty
project and document submission
creating channels for online teaching and mentorship
please check the mentioned github repo for the App. This app is for caretakers of patients with serebral pasly and people on wheelchais.
body temperature, heart rate, alarm functionality with data stored in the cloud database.
dues and assignments
messaging services
online proctored tests
Inspiration
During online classes, many students verbally harass the teachers and students of the class. This spoils the whole environment of the class, So we decided to block these students using speech recognition technology.
Then we all must have seen that delivering the things without contact has become a major problem, therefore we designed a hand gesture moving messenger who deliver things to Covid19 infected people in care centers.
What it does
The first part is a
remote education
android app which resolves all the problems stated above. It contains all the features a student will want in his/her app. We tried to involve every activity that we use to do in offline college times in this App. It consists of
Video call functionality
with a special feature of blocking students who are speaking abusive or bad words during a live session. The student will be reported to the admin of the app and all the records of the blocked student will be sent to the admin app. Admin can unblock the student again. Then our app contains a
chat room
for each classroom a student is enrolled in, it will allow the students and teachers to communicate as they use to do in Offline College. Then comes the appointment feature. Before contacting any teacher we have to make an appointment with him/her to ask for their time. So our App includes this cool feature of
appointment
for the students. This reduces the chaos and brings the working thing so that follows proper protocol. Teachers wanted an invigilation system to invigilate students during the test. In our App, we provided this feature by
camera proctored examination
feature. Under this a teacher can proctor all students through their webcams while the students are giving tests, also the teacher can pass their voice in the whole class to
convey messages
during tests. Also, our app has a feature of
assignment submission
. The teachers can upload the assignment questions along with the due date and students on the other hand can upload the solutions of these tests on the app itself.
How I built it
We used the android studio to build a remote education app. For backend, we used firebase realtime database. For identification of abusive words we used IBM speech to text services to convert the speech of the students in text and then we used this text in the loop to find whether he is abusing or not. We took the dataset of abusive words from Kaggle and gitHub.
For our IoT bot, we used the hand gesture sensor and on the basis of the gesture, the robocare bot will move and deliver thing to patients. It can also be used as a wheelchair.
Challenges I ran into
We faced many challenges like detecting and blocking students who speak the abusive language during the live class. We wanted to make something that everyone can relate with offline college activities. Therefore, we need proper planning and structure. The assignment section needed a proper structure to be executed.
Teachers all over the globe wanted a platform for cheat-proof examination. Our challenge was to make a cam proctored examination with cheat-proof features like on leaving the test you can not re-enter it.
Accomplishments that I'm proud of
We are proud of our abusive language detector system which blocks users when they speak bad words. Also, the structure we made is highly related to offline day to day activities. Our cam proctored test system is awesome, and it restricts the user from cheating and helps the invigilator to invigilate during a test.
What I learned
We learned, how to work with the realtime database, how to use IBM's speech to text services to detect abusive words. In this pandemic situation, we learned the complete use of GitHub and how to collaborate our work with teammates. Also, we learned some new IoT features which helped us to make the robocare bot.
What's next for Covid19 Kit
For future aspects we are planning to make a complete, general messenger system for private and government offices which they can use to share files, letters, assigning task and doing all other stuffs which people do in offline office hours.
Built With
android-studio
arduino
e-learning
education.com
firebase
ibm-watson
iot
Try it out
github.com
drive.google.com
drive.google.com | Covid19 Kit | An android app, an IoT device, and a Covid19 tracker, a complete kit for students, doctors, patients, and common people. An IoT bot to follow social distancing practices. | ['Ayush Sharma', 'Elio Jordan Lopes', 'Shaolin Kataria', 'Ritik Gupta', 'DEVANSH MEHTA'] | ['The Wolfram Award'] | ['android-studio', 'arduino', 'e-learning', 'education.com', 'firebase', 'ibm-watson', 'iot'] | 17 |
10,276 | https://devpost.com/software/3d-cube-runner | An in-engine look at how maps are produced
Inspiration
Cube Runner was inspired by the concept of a high speed game with lots of challenge, that makes it fun difficult, and very rewarding to learn.
The Gameplay
Cube Runner is a 3D runner game in which you run through different levels trying to dodge enemies and as the levels progress, the pacing gets faster and more difficult. On top of this, you're also trying to complete the levels in as little time as possible.
The fast-paced gameplay makes the game difficult at first, but as you get the hang of how to dodge, sprint, and slow down time in your favor, the game becomes all the more rewarding when you finally beat it.
How we built it
Unity Engine
To make the game we used
Unity Game Engine
, which is built in .NET. Unity is one of many game engines, but the reason we chose Unity specifically is because it's a great general purpose engine, some of the more famous ones, such as Epic's Unreal Engine, or Valve's Source are generally developed for specific purposes, and as such, are more easy to use for their intended purpose, both the Unreal and Source engines, for example, are developed to cater generally to the first-person genre, usually shooters.
Unity is different in that it is an even platform for whatever type of game you want to make, and people have even made AR/VR apps in the engine. The focus of the engine is not, like most, to provide utilities and tools for a specific purpose, but to provide a single,
unified
platform for developers to make games. Unity is completely platform compatible with a large variety of platforms ranging from mobile, to console, to even web players. Along with this it provides general purpose tools for the latest technologies such as AR/VR, Hololens, and the latest graphics developments.
Challenges we ran into
One of the biggest challenges we ran into was the scope of the game, originally it was going to be a survival game where you have to brave out a storm long enough to reach the city, dodging trees and debris along the way, and losing health in the cold, the only way to regain health would have been to stay near campfires to warm yourself up, but not to stay for too long so you can make it in time.
This was quickly realized to be an ambitious goal, but we met it with flexibility and reduced the scope of our project into a much smaller, speedrunning/dodging game so we could finish in time.
Accomplishments that we're proud of
One of the things we are most proud of are the graphics and the player movement, the movement is meant to be high fidelity but also smooth, giving the player enough control to be able to play at a very high skill level, and have it still be satisfying.
The graphics are also one of our prouder accomplishments, as the game does look quite nice.
What we learned
Somewhat obviously, we gained some experience in the Unity Engine, but more importantly, that the most important skill when going into game jams, hackathons, or other timed events, is flexibility. As we learned with our original storm game concept, you won't always get to do what you want, and you'll have to be flexible, and that's important above all coding, modelling, or other technical skills.
What's next for Cube Runner
We are planning to make more levels, enemies, and general content, in our limited time we were able to lay the frame of the game, however not much to fill it, meaning a lack of content, however we feel that with further work and polishing, this game might be released someday!
Built With
.net
c#
unity | Cube Runner | Test your skills in a fast-paced, high skill speedrunning game! | ['Harshit Pottipati', 'Mehul Tahiliani', 'Vikranth Nara', 'Neel Sawant'] | [] | ['.net', 'c#', 'unity'] | 18 |
10,276 | https://devpost.com/software/resurrect | Home Page
Recreate Your Friend's Page
Chat with Dad (Family/Friend)
Chat with Celebrities
Chat with Kobe Bryant
Request a Celebrity
Conversation with Therapist
Forum Page
Local Therapists
Inspiration
As hundreds of thousands of people continue to lose family members due to the pandemic, our team has reflected on how we may one day say goodbye to those we love. In addition to seeing families grieving from their losses, we have seen many public figures pass away both before and during the pandemic, such as Kobe Bryant’s untimely death. We wanted to make use of AI and ML to help people cope with their losses, both with loved and inspirational ones.
Thus, we took a unique approach to the idea of staying connected during quarantine.
Instead of creating an application that connects users conventionally, which already has numerous solutions, such as Instagram and Facebook, we opted to develop an app meant to connect people with those they cannot connect with anymore -- namely, those who have passed away. We wanted to find a way to allow friends, family, and even fans to artificially interact with these people and keep a memory of their experiences with those they have lost.
Thus, we developed Resurrect, an application that allows users to bring back those who have passed away through Generative Natural Language Processing Models, which replicate distinct personality and conversational traits.
What it does
Resurrect is a unique progressive web application that lets users artificially bring back loved ones and late celebrities. The core of our project is multiple generative NLP models, which allow users to build conversational agents with the personalities of anyone the user desires. Note that our demo shows the process, but because our model is incredibly large and because each bot needs to be trained for hours, the only way for us to deploy the generative models is to gain access to expensive, high-powered servers. Our model will work for anyone so long we are given the required data, and we hope to automate our model by gaining access to these servers.
First, users can upload both a csv file of their downloaded conversations (by connecting a phone to computer) with their late family members, as well as an audio clip of them speaking. The file is then uploaded to
Google Cloud
, and then we input it into our model. Our model takes the text conversation and begins training to replicate their speaking style. We found a research paper written by Google AI researchers on voice cloning, and while we were unable to implement this model with our generative models due to not having server power, we can still take the inputted audio sample and generate new samples. Once we finish processing their files, we notify them via email. We return a generative model embedded within a messaging interface, where they can have an interactive conversation with their late friend or family, allowing them to cope with their loss or to relive their memories.
We also developed a model to allow people to interact with late celebrities. Rather than using messaging transcripts, we web-scrape data from their twitter accounts, which often display their personality and resemble how they interact with fans. If a celebrity model has already been created, users can instantly interact with it, but if not, they can request one and we will quickly develop one for them.
Lastly, we have a page for those struggling with the death of their loved one or any other mental health issue. We created a generative model that acts as a counselor and therapist for mental health patients. This creates a supportive environment for those struggling with tough losses. We also have a forum where people can express themselves and meet new people who are facing the same grief. In addition, we created an interactive map using the
Google Maps API
, which allows users to find local therapists to receive additional support from.
How we built it
After numerous hours of wireframing, conceptualizing key features, and outlining tasks, we divided the challenge amongst ourselves by assigning Ishaan to developing the UI/UX, Adithya to connecting the
Firebase
backend and creating the chat features, Ayaan to developing our base generative models and researching the voice replicating model, and Viraaj to training the models with
AI-Fabric from UI Path
and connecting the backend.
We coded the entire app in 5 languages:
HTML, CSS, Javascript
,
DockerFile/Makefile
, and
Python
(Python3 /iPython). We developed our chat interfaces and integrated our models using PythonAnywhere and the
Flask
Framework. We used
PythonAnywhere
as our backend. We used
Javascript
to create our website backend, and used
Google Cloud
to store our data. We hosted our website through
Netlify
and
Github
.
For this project, we focused on developing generative NLP models with
Pytorch
and
Tensorflow
. For all our models, we used the pre-trained HuggingAI generative model and fine-tuned it on our data for each circumstance through transfer learning. For our counselor bot, we used the pre-trained Bert NLP Model and fit it to our data. When we get a message from the user, we are able to convert it into a latent vector and thus generate the correct output message. For our voice cloning model, we followed the documentation in the Google AI Research paper, and we were able to recreate their results with modifications, but couldn’t integrate due to server restrictions.
In order to collect data for these models, we developed two webscrapers. First, we created a basic web scraper to collect and format tweets based on a twitter handle. We then developed a web scraper to web-scrape counselchat.com, a forum for experienced and qualified counselors to answer questions, provide support, and post advice. For our adaptation model, we downloaded CSVs of text conversations from our iPhones and used them as data.
Challenges we ran into
The primary challenge that we ran into was developing our generative models. Since we have never built any generative NLP models, we weren’t sure how to start. Luckily, we found great documentation on how to develop them. We ultimately built 4 generative algorithms that all have different tasks. Training these models was also a huge challenge, and we saw that it was taking a long time to train. While we were not able to deploy our models, as they are too large to deploy on free and available servers, as long as users give us the CSVs or twitter handles, we can develop a bot for them.
Accomplishments we are proud of
We are incredibly proud of how our team found a distinctive yet viable solution to allowing people to cope with the loss of their friends and family. We are proud that we were able to develop some of our most advanced models so far. We are extremely proud of developing a solution that has never been previously considered or implemented in this setting.
What we learned
Our team found it incredibly fulfilling to use our Machine Learning knowledge in a way that could effectively assist people who have lost their friends and family. We are glad that we were able to develop a wide range of generative models to help a vast range of people. Seeing how we could use our software engineering skills to impact people’s daily lives was the highlight of our weekend.
From a software perspective, developing generative models was our main focus this weekend. We learned how to effectively build generative NLP models and web scrapers. We learned how to use great frameworks for ML such as
Docker/Makefile
and
Flask
. We grew our web development skills and polished our database skills.
What is next for Resurrect
Since our application is free and available to the web, our project can be scaled and implemented anywhere and with many other programs. With the possibility of a second wave for COVID, it is imperative that people have access to resources that can improve and stabilize their mental health and help them cope with the losses of their loved ones that are inevitable even beyond COVID.
In terms of our application, we would love to deploy our models on the web for automatic integration. Given that our current situation prevents us from buying a web server capable of running the models, we look forward to acquiring a web server that can process high-level computation, which would automate our services. We would also like to find new ways to collect datasets for our adaptation model. Lastly, we would like to focus on refining our voice cloning software and be able to integrate it with the rest of our models.
Our Name
We chose the name
resurrect.space
because our application attempts to resurrect a lost person and fill the space they left behind.
Built With
css
docker
firebase
flask
generative-models
google-cloud
google-maps
html
javascript
makefile
natural-language-processing
netlify
python
pytorch
tensorflow
uipath
xterm.js
Try it out
resurrect.space
github.com | Resurrect | Using Generative NLP Models to Reconnect with Lost Loved Ones | ['Adithya Peruvemba', 'Ishaan Bhandari', 'Ayaan Haque', 'Viraaj Reddi'] | ['Honorable Mention: Best Usage Of A Server', 'Best UiPath Automation Hack'] | ['css', 'docker', 'firebase', 'flask', 'generative-models', 'google-cloud', 'google-maps', 'html', 'javascript', 'makefile', 'natural-language-processing', 'netlify', 'python', 'pytorch', 'tensorflow', 'uipath', 'xterm.js'] | 19 |
10,276 | https://devpost.com/software/hack-auth | Hacker Auth
Preventing cheaters from taking away wins from others
The Idea
After having found many cheaters, I realized many follow the same patterns. So my friend Jacob and I build HackAuth to help judges make more educated decisions about submissions
How it works
_ Full Disclosure _ We weren't able to connect the backend to the front end. We ran into this error when we ran the backend in production and we didn't know what to make of it "x509: certificate has expired or is not yet valid"
Frontend
Javascript extension
Backend
Golang Fiber Server -- Benchmarks more than 3x as fast as NodeJS
Docker -- Containerized application
Kubernetes -- allow the application to scale based on use
Built With
docker
gcp
go
gofiber
google-cloud
kubernetes
Try it out
github.com | Hack Auth | Stopping cheater | ['Benjamin Swerdlow'] | [] | ['docker', 'gcp', 'go', 'gofiber', 'google-cloud', 'kubernetes'] | 20 |
10,276 | https://devpost.com/software/hive-hub-9mdyo8 | Hive Hub Logo
Honeybee Tracking Map
Inspiration
Honeybees are a vital part of our ecosystem and economy. According to the Division of Agriculture at the University of Arkansas, 90% of wildflowers and 75% of crops rely on pollinators; honeybees are responsible for pollinating more than 80% of wildflowers and crops. This means that, not only do they pollinate more than 100 important crops including vegetables, fruits, and spices, they also contribute over $20 billion to the US in agriculture every year. However, honeybees and their homes are being threatened by rapid urbanization and various farming methods. Their population is declining at a rate of 30% per year and facing possible endangerment.
We hope to encourage people across the US to support the conservation and regrowth of the honeybee population.
What it does
We would have a map that records major areas of beehive, and bee, population so that others, as well as ourselves, can clearly see locations that need more hives and then work to construct them there. People can support this cause in two different ways through our website: donating to sponsor the construction of a bee hive, or hosting a beehive themselves. Using AR, people will be able to see what a beehive would look like in their own backyard. If they wish to host a hive, and the environment is suitable for one, they will receive a beehive from us that can be constructed by one of our beekeeping partners.
How we built it
We used repl.it for our entire website, and added an augmented reality element by building a 3D model on EchoAR and adding the QR Code to our website.
Challenges we ran into
We were both new to coding, and it was hard to build an entire application/website without much instruction. Because we both needed to learn how to program without having much, if any, experience, we spent much of our time looking up how to program basic things into our website and didn't have much time to make it complicated. We also wanted to make an app to go with our website, but we couldn't figure out how to in the timeframe given (hopefully next time!)
Accomplishments that we're proud of
We are both very proud of how our website turned out despite all the challenges we faced along the way. We were able to code a basic website with the skills we were taught in one of the workshops, and were even able to add some extra elements like a background image, columns, and a logo, that were not covered in the workshop.
What we learned
We learned how to work with the skills we have to create our own, unique project. We were able to use the short workshops, assistance from the event organizers and our fellow programmers, and Google (haha) to complete our website in 24 hours. We also were able to improve our communication skills by conversing with people that we were not able to physically see and work with due to quarantine.
What's next for Hive Hub
We hope to create an app, as stated on our website, that connects people across the US in the movement to protect and conserve honeybees. People would be able post photos of thriving personal, or local, hives. They would also have personal tracking maps on which they can mark the location of new, unmarked hives they find in their area. We would use those marks (once we confirm that they are accurate) to update our own overall map of the hive and bee concentration across the US. We would also try to reach out to children and the younger generation by including mini games that spread awareness about the importance of bees and the problem with their endangerment, and by implementing a point and badge system that rewards people for playing the games, posting a photo, updating their personal tracking maps, or just interacting on the app.
In short, we wish to create an app, and website, that can be a "hub" for conversation about honeybee conservation and population growth as well as a place where normal people who are not bee specialists can learn about this movement and work together to support it.
Built With
html
replit
Try it out
impurefatalpublishers.thaliainui.repl.co | Hive Hub | Tracking, constructing, and maintaining honeybee hives across the US in order to help prevent the endangerment of honeybees in the US | ['Matthew Inui', 'Thalia Inui'] | [] | ['html', 'replit'] | 21 |
10,276 | https://devpost.com/software/mednav | MedNav Showcase
Inspiration
The inspiration for MedNav came from personal experiences of waiting in a crowded emergency room while experiencing a medical emergency. MedNav aims to improve medical emergency communications and make the process more efficient and convenient for everyone.
What it does
MedNav is an iOS application designed to lead patients to the nearest and most convenient hospital during a medical emergency. The app aims to reduce wait times and provide efficient and effective care to those in need.
How I built it
MedNav was built using Xcode and Swift programming language. Although I was new to Xcode, I learned a lot during the development process.
Challenges I ran into
During the development of MedNav, I encountered several runtime errors that had to be solved. However, with persistence and dedication, I was able to overcome these challenges and create a functional app.
Accomplishments that I'm proud of
I am proud of creating a functional app that can potentially help many people during medical emergencies. I'm glad to have solved many runtime errors while building the app. MedNav seems like a pretty simple app, but I think it can help a lot of people.
What's next for MedNav
Currently, MedNav is just a prototype. But if people like the idea, I will focus on improving it to be more user-friendly and practical. Then, after testing, I think it would be a good idea to introduce it to local hospitals.
Built With
swift
xcode
Try it out
github.com | MedNav | An Emergency Medical Navigator (simulator walkthrough included in video) | ['Daniel Gao'] | [] | ['swift', 'xcode'] | 22 |
10,276 | https://devpost.com/software/button-of-happiness | The page where you can leave a message for others to see. Automatically generates a new message every 5 seconds for you to see.
The main page, where you can choose what kind of activity you'd like to do and how you want to feel. Here we show "I want to be Entertained"
Inspiration
At first, we were thinking about making a website that tackled either a world issue or health but decided to create something more interactive than that. So we ended up creating a website that could cheer people up and make them feel happier afterwards.
What it does
This website allows you to press a button and play either an image, video, or song depending on the option you select. The options are I want to be entertained, I want to be motivated, and I want to be relaxed. Entertained will play a video, Motivated will show a motivational quote, and Relaxed will play an Mp3 of calming sounds and switch songs with a click of the button ("Hey, Can I get another one?"). You can also leave a motivational message for other people that visit the site, and view some of the messages other people sent you.
How we built it
We built the website using Flask, HTML 5, Javascript, and CSS3. The website is hosted on an Amazon Web Services EC2 instance running a Debian based server. We used Jenkins for continuous integration and to keep the website up to date, and used AWS DynamoDB for the database to store and get the messages.
Challenges we ran into
Some of the challenges that we ran into were the buttons, audio, and pushing changes from GitHub onto the website. There were also issues with getting Flask to communicate properly with the frontend as we had to use HTTP requests to get and receive data from Flask, which took a lot of trial and error to get working correctly. Another issue that we faced was with the button and the button disappearing along with the button giving an undefined result. Jenkins and AWS were difficult to set up at first, and especially DynamoDB as we hadn't worked with databases up until now. Jenkins in particular was quite annoying to configure the permissions and webhooks required to link it with the Github repository and update and restart the server once a commit is made.
Accomplishments that we're proud of
Being able to use a database (SQL)
Streamlined build and deploy system with continuous integration
Scalability and reliability with remote databases.
Written 100% from scratch during the hackathon, without any templates or guides
Able to generate content from an easy to manage list
What we learned
Learned how to use Flask for backend management
Learned how to use DynamoDB for professional data management and storage
Learned how to use Jenkins and AWS for remote build, testing, and deployment
Learned how to manage HTTP requests on a server and send them from the front end
What's next for Button of Happiness
More videos that added onto the selection.
Being able to send gifs to others.
More quotes and images.
A more aesthetic format for the images and better quotes.
Allow users to create an account so they can favorite or star their favorite activities generated by the button
Allow users to customize the color scheme to maximize relaxation or comfort
Provide a rating system for each activity the button generates (lets devs know which activities worked and which didn’t)
Create a page where users can submit requests on what kind of activities the button generates
Update and improve the favicon.
Built With
css3
flask
html5
javascript
Try it out
happybutton.ddns.net
github.com | Button of Happiness | How do you want to feel today? Motivated, relaxed, entertained... This site can help you with that. The button provides you with images, sounds, videos and messages to help you feel how you want to be | ['Lingfeng Ren', 'Elton Zeng'] | [] | ['css3', 'flask', 'html5', 'javascript'] | 23 |
10,276 | https://devpost.com/software/hack-the-fog-game | Kappa Enigma is a game where you control the green prince and defeat enemies to reach the princess.
Inspiration:
We were inspired by classic 2d games such as Mario, I Wanna Be The Boshy, and Cuphead. We wanted to make a challenging game that incorporates a deep storyline and is most importantly, fun.
What we learned
We learned a lot about how to create games using Jquery. We previously only had experience using it to build websites and webpages, so creating a game was a new but fun experience. We learned about a lot of things, especially about how to create game mechanics like moving the characters and using the fighting abilities, having different stages, AABB(Axis-Aligned Bounding Box) collision detection, spawning enemies, and adding unique stats and features to each of the characters that changes as the game goes on.
How we built it
We used Html, CSS, JavaScript, more specifically we utilized the Jquery library to build a webpage that incorporates a game. We used ms paint to draw the characters each of the characters and bullets. We scoured the internet for background images that fit our theme and makes the player feel like they are actually a part of the world they are playing.
Future Vision
Add various skills for the green princess, such as blocking and healing.
Customizable enemies and stages
Challenges we faced
Hit box
Enemy behavior (shooting, attacking, moving towards the player)
Moving the characters
Spawning enemies
Built With
css
html
javascript
Try it out
github.com
drive.google.com
helix-boiled-soybean.glitch.me | kappa enigma | Fight against the evil princess that stole the world's most powerful energy source for her own evil deeds. | ['Justin Huey', 'Hongjun He', 'Liwei Huang'] | [] | ['css', 'html', 'javascript'] | 24 |
10,276 | https://devpost.com/software/the-orchid-organization-sunwatch | SunWatch Design
Inspiration
I have always wanted to go into medicine because I wanted to make a difference in people's lives every single day. However, recently I realized that as a clinician, although I would be helping people, it would only be a handful at a time. Whereas if I were to develop an application of technology that revolutionized health care, I would be impacting the lives of hundreds of thousands if not millions of individuals worldwide! The importation for SunWatch came from one of my classes this year where we were tasked to create a medical intervention that prevented or treated skin cancer.
What it does
Exposure to UV or ultraviolet radiation is one of the leading causes of skin cancer. By being more aware of what measures we can take to protect ourselves, we limit our risk of developing skin cancer in the future. SunWatch works by having the user input their location and the UV index of the day, based on that information, SunWatch provides the user with helpful tips and suggestions as what to wear and how much sunscreen to apply throughout the day. Although it may seem simple in theory, if applied correctly it can make a significant difference in a person's exposure to radiation.
How I built it
I built this application on the website for my organization, The Orchid Organization. The Orchid Organization is a community-based organization led by students whose purpose is to raise awareness about personal health and wellness. I used CSS, HTML, and Bootstrap to build the website and design it. I then used JavaScript and utilized my own web API to create a function that determined what suggestions should be given to the user based on the user's UV index input.
Challenges I ran into
Since I am new to coding altogether, I particularly struggled with JavaScript and creating the functionality of the SunWatch.
Accomplishments that I'm proud of
I am extremely proud of the amount of time I completed this project in. A week or two ago, I would have taken twice as long with less that optimal results. I am also really proud of making the website accessible and responsive.
What I learned
I learned a lot about using functions in JavaScript and how to use variables, events, and how even the smallest typo can throw the entire code off.
What's next for The Orchid Organization: SunWatch
I hope to incorporate AI into my SunWatch so that the suggestions are more personalized to the user's location, such as it takes into account whether it is cloudy or sunny or rainy. I also want to find a way to personalize it so that the SunWatch accounts for whether the user is at risk for developing skin cancer due to family history or other reasons.
Built With
api
bootstrap
css
html
javascript
Try it out
github.com
oasisa.github.io
oasisa.github.io | The Orchid Organization: SunWatch | Empowering our community to take their health into their own hands and protect themselves from the detrimental effects of UV radiation. | ['Aqsa Owais'] | [] | ['api', 'bootstrap', 'css', 'html', 'javascript'] | 25 |
10,276 | https://devpost.com/software/melanomai-i3e1c7 | Thanks Page
Home Page
Note
After the deadline we were able to integrate the AI and host the website. We couldn't host the AI model because the free tier wouldnt allow it and the AI models were quite large, but you can check everything else out. (There are some minor bugs related to styling, but if you enter an image and your email it should work!)
The github repo was updated according to the changes as well.
https://melanomai.herokuapp.com/
Note
The images needeed for diagnosis are dermascopy images which need to be taken by a dermatologist. Thus this isn't entirely remote, however by providing a more effective and accurate analysis this could cut down on the number of trips required to the dermatologist and can also be much more convenient and cheaper.
MelanomAI is still a much better alternative to current methods of diagnosis.
There are ways for people to do self dermascopy, but those ideas are still in development.
(This could be something we do in another hackathon or after this hackathon to suplement and support this idea)
Inspiration
Melanoma is a deadly skin cancer which affects all ages. It starts off as a cancerous growth but can spread to other parts of the body as well.
The worst part is that Melanoma has a 25 - 30 percent misdiagnosis rate meaning 1 in 4 people have been misdiagnosed with the cancer.
Considering how dangerous and scary cancer can be a 25% misdiagnosis rate is too high.
1 in 4 people should not have to suffer due to an accident that can be avoided.
MelanomAI works to fix this problem by making Melanoma diagnosis easy, fast, and above all accurate.
What it does
MelanomAI is a 6 layer convolutional neural network which can analyze an image to detect and classify melanoma. Convolutional neural networks are very good at analyzing images and giving accurate results. With enough time our team is confident that we could bring accuracy into the mid to high 90’s.
Here’s how it works for the user:
Go over to our website
Upload an image of melanoma
Enter your email
Submit
Check your email for results!
Diagnosing Melanoma accurately is just 5 steps away.
How We built it
We used pytorch to build the AI model and train it.
We used bootstrap, django, css, and html to create the website.
Challenges I ran into
One of our members lost half of their files 3 hours before the hackathon and had to recode all of them.
It was a traumatic experience and was a good learning opportunity on how to store files and use github.
We struggled to actually integrate the AI and the website due to some errors, given some more time we might have been able to fix it.
Accomplishments that I'm proud of
We are proud of our accuracy. We were able to get an extremely high accuracy in such a little timeframe and with more time we are confident we can get the accuracy to above 90%.
We are also proud of our website as this was out first time making an AI and a UI to go along with it in a Hackathon.
What I learned
How to work with AI(Pytorch)
How to use django to build websites.
The benefits of using github as source control and a way to ‘backup’ files.
What's next for MelanomAI
We want to integrate the self standing AI and the website, we faced issues with this part, but given some more time we are confident we would have been able to succesfully integrate the two.
Once we get a complete product we want to host the website to make it available to all, and given that it gains some popularity possible even try to implement it in the real world!
Built With
css3
django
html5
python
pytoch
Try it out
github.com | MelanomAI | Detect and Classify Melanoma Effectively | ['Gaurish Lakhanpal', 'Anish Karthik'] | [] | ['css3', 'django', 'html5', 'python', 'pytoch'] | 26 |
10,276 | https://devpost.com/software/covidnet-jq97oa | Our site's homepage.
Site homepage (ctnd).
A diagram showing the relationship between the various components in our project.
covidNet by Anirudh Kotamraju and Kailash Ranganathan - A Deep Learning Powered Coronavirus Visualization and Prediction Software
Inspiration
Coronavirus is undeniably the most major problem of current times, but it seems that quarantine and the effects it is having on the global market and on people’s lives are influencing a new wave of openings, and with it, an even stronger and more potent virus.
People are not adhering to social distancing as much, and while we understand their perspectives to want to quickly resume their normal lives, we wanted to deliver an objective and informative way to show people that coronavirus is more potent and spreading faster than ever.
To do this, we built covidNet, a realtime web app that uses up-to-date coronavirus data to display the growth of the virus in all US states and also use deep learning to give predictions and insights into how coronavirus will grow over the next 30 days using recurrent neural networks. This will be able to give a better insight into how coronavirus could grow over standard regression and curve-fitting models in place.
What it does
covidNet delivers a neat and clean UI straight to your device that gives visual data for all 50 US states on total cases and how they have grown since the start of the coronavirus outbreak. But the main attraction is the prediction curves, where we trained individual “recurrent neural network” models for each of the 50 states to analyze how the virus has grown over the past few months and continue the curve to predict the virus’s cases over the next 30 days, a lookahead from today. Quick highlights for predicted (total) cases tomorrow, in 3 days, and in one week are also visible for each of the states. The website is updated daily.
Each day, a Google Cloud Virtual Machine automatically starts up. It gets the new data for the day, and automatically trains each of the 50 models using the new Johns Hopkins data (not from scratch, but starting from the previous day’s trained models). It then uploads the new models’ predictions for the historical time and the next 30 days into a Github repository as well as the model files for the next day’s training. Whenever a user visits the website (hosted on Heroku), the predictions are taken from this Github repository. Thus, both our models and website are automatically always up to date with the newest trends in each state's fight against the pandemic.
With this project, we are able to give well organized and accurate predictions using state-of-the-art deep learning methodologies of what the virus could become in each state if further action is not taken. We hope that this will help present the true danger of the uncontrolled virus and encourage preventive action to be taken in the future.
How we built it
We used Dash and Plotly for our frontend, libraries especially relevant for visualizing data science results. With this, we are able to efficiently and effectively integrate our neural network prediction backend with a clean frontend all in Python with some CSS formatting.
The model updating happens on a Google Cloud Virtual Machine. It is configured with CRON to automatically start up at a certain time and run a startup bash procedure each day. This procedure begins training the models and pushing the csv and model files to our main github repository, where these results are integrated with our frontend. It features a streamlined python script that fetches data from Johns Hopkins, formats it and retrains 50 state models, and saves those to files as well as their historical and 30 day future predictions to a csv. The models are trained using 2 layer deep LSTM neural networks, with dropout rates of 0.2-0.3 implemented to prevent overfitting. The model files are saved so that on the next day, rather than starting training on the dataset and next day’s data from scratch, the training can load in the preexisting model and continue from there, making the model more accurate as time goes on.
The website is live and anyone can access it at
https://covid-net.herokuapp.com/
. Because our training is scheduled, the website and models are automatically updated daily without us having to do anything.
Challenges we ran into
Because LSTM’s are more complicated structurally (and time-dependent as opposed to normal ANNs) than normal feed-forward neural networks, our analysis of coronavirus time series from raw data was quite difficult. We spent a long time devising algorithms to convert the data from raw text (from the Johns Hopkins coronavirus dataset) to properly formatted and normalized tensors to run through our LSTM but were able to generalize this process and train a model given state data just by inputting the state name into our program. With this data our models devised, we were able to quickly create interactive graphs with it to display on our website.
Furthermore, one of the most important parts is that the whole program updates daily automatically, meaning that we don't have to manually change anything and the models will automatically take data from the dataset, continue training from the previous day's models, and fit to the new data while becoming more accurate. This was extremely hard, as we had to go from a python script that ran one model at a time to one that took data, formatted it, and trained and saved all models in an organized manner. Furthermore, integrating the frontend and backend using Github was also a challenge between configuring the GCP Virtual Machine and Heroku.
Accomplishments that we're proud of
We are proud that we were able to write the neural network, train 50 individual models on 50 individual datasets (one for each state), and deliver it in a functioning and visually pleasing UI in the timeframe of the Hackathon. We were able to functionally link the backend neural network Tensorflow model with the frontend Dash and Plotly web app and in the end, could deliver a useful and easy to use visualization of current coronavirus statistics for all 50 states and our deep learning predictions for future cases starting with the next 30 days. Because daily updates from a virtual machine have zero room for error (or the whole website comes crashing down), our process for automatic updates is robust, reliable, and organized well so that connections between backend and frontend are clear (through GitHub). We are also proud of the completely automated model and data update process, which updates the models using *
bash scripts on Google Cloud, then writes them to Github, and the Heroku app accesses those updated data files on Github and presents them to clients on a real time basis. *
What’s next for covidNet
Our application and neural network still have some refining to go through, even though it works quite well for all 50 states as a prediction device. We wish to make a bigger, deeper, and more powerful LSTM network to detect more subtleties and insights in the coronavirus data, and also bring in more variables, such as the openings of states, different social distancing orders, and other factors that may affect the spread of the virus. We already expanded on this project by going from only 37 states in a static website initially to a realtime, updated daily website with not only more accurate results but new data and extra training every single day. Perhaps with more computational power and a multivariate system, we will be able to not only predict coronavirus cases, but simulate different paths for the virus using different societal and community parameters, such as level of lockdown, average interaction among crowds, and others.
We hope you all stay safe and have fun :)
Built With
dash
github
google-cloud
heroku
numpy
pandas
plotly
python
scipy
tensorflow
Try it out
covid-net.herokuapp.com
github.com | covidNet | A Deep Learning Powered Coronavirus Visualization and Prediction Software | ['Hoponga (Kailash Ranganathan)', 'Anirudh Kotamraju'] | ['Second Place'] | ['dash', 'github', 'google-cloud', 'heroku', 'numpy', 'pandas', 'plotly', 'python', 'scipy', 'tensorflow'] | 27 |
10,276 | https://devpost.com/software/only-masks-allowed-upt1a4 | Inspiration
I saw lots of datasets regarding masks and also saw the idea of training a model to recognize if a person is wearing a mask to be widely used at devpost. Therefore, I thought of a different approach to using the face mask dataset: creating a game.
What it does
It is a "Dumb ways to die" like game. It selects randomly from a range of face mask images for the gameplay. In the only mode that I coded, it requires you to click on people with masks on.
How I built it
I used nodejs to preprocess the face mask dataset and compressed the images too. Then I used frontend javascript to run the game.
Challenges I ran into
Since this was my first time coding a game, I ran into a lot of challenges. I couldn't figure out the proper HTML format for a game, how the game initialization process should be like (conventionally), and how to maintain the code with it being all spaghetti.
Another big challenge was time. I had a lot of time constraints (I am currently having three online summer camps) so I only had three hours to make the game. Combined with my immature understanding of making games in HTML, coding this project was a big challenge.
Accomplishments that I'm proud of
I am proud of the fact that I was able to pull off this project within a short timeframe at the same time being new to the game coding mindset.
What I learned
I learned the architecture of a basic game and experienced the mindset required to code a basic game.
What's next for Only Masks Allowed
I would definitely patch up some bugs and include more modes. Also, if I had more time, I would fix up the UI in the game.
Built With
css
html
javascript
node.js
Try it out
github.com
only-masks-allowed.surge.sh | Only Masks Allowed | An unfinished "Dumb ways to die"-like game. Has potential to include different modes and animations/effects. | ['Simon Cheng'] | [] | ['css', 'html', 'javascript', 'node.js'] | 28 |
10,276 | https://devpost.com/software/svt | Inspiration
We were inspired by our love of coding, even if we have just begun learning it.
What it does
Our password generator first asks how many characters you would like to have in your password. Once you type in your desired password length, it will give you a password as long as you wanted it to be. Then, it will ask you if you would like another password. If yes, you type "y" and it will ask you again how many characters you want it to be. If no, you type "n" and it stops the program.
How we built it
Well, a random password generator needs a set of characters to use randomly so we had a string of all the possible characters. Then, we used a prompt to ask the user how long they want their password to be. After getting that number, we created a random number generator that generates integers from 0 to their desired password length
loop. That range is as many times as how long they want it. Then print the outcome that's all in a while loop that repeats until the user types "n" or "N" to stop the code.
Challenges we ran into
Some challenges were that we were new to coding and had to figure out some of the more complicated steps. This also took up a lot of time which eventually became its own problem.
Accomplishments that we're proud of
We're proud that we got through the bugs and errors without getting frustrated.
What we learned
We learned that we should plan and manage our time better.
Built With
javascript
Try it out
repl.it | SVT | A random password generator with the number of characters of your choice! | ['Wesley Tam', 'Claire Tao', 'Fiona Gan'] | [] | ['javascript'] | 29 |
10,276 | https://devpost.com/software/pong-flappy-b53ud6 | This is a picture of Pong!
This is a picture of the Creators page which shows our names and bios!
This is a picture of Flappy!
Inspiration
We were very puzzled at what to create for this hackathon. So we decided to think of some problems that we have right now. We said at the same time that the quarantine had made us so "bored" that we were about to go insane. From there, we were thinking of ways to interest other people and how to captivate others. That's when we thought of Pong!+Flappy!
What it does
The website we created features two games plus a quick bio of us. Pong is one of the games featured on the website and it has many cool features. If you didn't know already, Pong is a table tennis sports game featuring simple two-dimensional graphics. However, we added cool extra features to the game. Pong's extra features: 1. There is the option to play music in the background while the user is playing and keep in mind, you can skip around the music track AND adjust the volume. 2. There is an option of enabling confetti which is an animation that plays across the whole screen when a user wins. That way, it makes the winner feel much happier and wants to play again to get the same satisfaction :) 3. If the game is too easy for some people, we added an extra "fast mode" so users get some challenge! In "fast mode", the ball is much faster but the speed that the user can move the block is still the same. 4. Thinking of games, I knew that Fortnite and all those first-person shooter games had the option to change keybinds (controls to move). So we thought, why not let the users have the option what buttons to press, to move the user block. At the bottom of the screen, lays the 4 different keybinds for Person 1 and Person 2 to change when they want their block to move up and down. 5. Another feature we added was a "reset keybinds" where if a user tries to set a keybind as "∆" and it was an accident, they can reset keybinds and see what the recommended keybinds are. 6. There is a "game objective" button because we wanted it so that users can play up to an objective and not play forever or else no one will be the "winner". (Also, the confetti play when someone hits the objective that the user chooses). Instead of giving options on what the objective is, we asked the user to put in an objective number whenever they click the button "game objective". If the user puts something else besides a number, it says invalid response. 7. Also, the button "reset game" resets the score, ball, and game objective. 8. We also wanted to add a pause/resume button to let the user have extra control when they are trying to change their keybinds, game objective, music, or any other setting. 9. We also added options of different objects that the user could use instead of the standard ball. If you didn't already know, Flappy Bird is a game where the objective is to make the bird go through pipes without touching them. The more pipes the user goes through, the higher the score. Flappy's extra features: 1. There is a normal and fast mode to challenge users and make the game more interesting. 2. We blocked users from cheating by flying really high by making the user die if they try and go super high. 3. We have a glow behind the game screen. 4. We also added audio which is adjustable just like Pong! 5. We have a cool face animation next to the title "Flappy Bird". 5. For any electronic device beside a computer, touching/tapping is how you move the bird but for keyboard, we made it so that any key that is pressed can make the bird move. 6. We added options for the user to pick instead of just having a bird.
How I built it
We used repl.it to build everything that you can see on the website.
Challenges I ran into
One challenge we had was making the UI. There are a lot of features and we didn't want to make everything super cluttered. At the same time, we had to make it so that the user has options and can adjust their game according to their liking.
Accomplishments that I'm proud of
Definitely the custom keybinds. It was pretty hard capturing keycodes and then updating the text to reflect the changes that were made. Also, creating two games in two days completely with the added features was pretty tough.
What I learned
We both got much closer to each other and now are very close friends. Also, we both learned that we can make simple games turn into much more fun and complex game. We learned how to host audio, not on repl.it, learned more about HTML5 canvas, and how to have the mindset of always being creative and adding new features to the game. Lastly, we learned that hackathons like Hack the Cloud are an amazing opportunity to bond and collaborate with people who have the same interests as you!
What's next for Pong!+Flappy!
Pong!:
If we had extra time, we would have created a solo mode where it would be the user vs a robot! Maybe even a multiplayer setting where you could play with people from all over the world! Also, the ability to drop and drag any music the user wants, and the ability to drop and drag whatever object they wanted instead of selecting a limited amount of options!
Flappy!:
If we had extra time, we would add coins between the green poles so whenever the bird goes through they collect coins and we could create a shop where there would be different options of skins that could be bought by coins! Also, just like Pong, the ability to drop and drag any music the user wants and the ability to drop and drag whatever object they wanted instead of selecting a limited amount of options! Maybe even.... having multiple people playing with you?
Built With
css
html
html5
javascript
Try it out
pong.jasonantwiappah.repl.co | Pong!+Flappy! | Two web games completely made from scratch with an extra added twists of our own! We hope you enjoy! | ['Jason Antwi-Appah', 'Winston Iskandar'] | [] | ['css', 'html', 'html5', 'javascript'] | 30 |
10,276 | https://devpost.com/software/liftyourselfup | This project was created by Anthony Mitine and Suhas Ravi. We have created a free ChatBot that gives people the opportunity to talk to someone. This interactive website was created in honor of Zachary Nimmo, a Pleasanton teen who committed suicide in October 2018. If you are feeling depressed, lost, or confused, please feel free to use our ChatBot. This ChatBot allows teenagers or anyone to have an understanding friend. Though this isn't a real person answering the messages, we do allow the users to contact us via email or via call/text. We built it using HTML, CSS, and JS. We did not run in any challenges. We are glad that this project has turned out successful and can be used. We both learned how to use our existing knowledge in web design to create this. We also deepened our communication and coding skills. Our next steps are to partner with the Z-Cares Foundation, which was started by the Nimmo Family after Zach has passed away.
Built With
css
html
javascript
Try it out
liftyourslefup20.anthonymitine.repl.co
docs.google.com
github.com | LiftYourselfUp | This project was created to help out teens who are feeling lost, confused, depressed, our just need someone to talk to. | ['amitine26 Mitine', 'TsukiLightSpace'] | [] | ['css', 'html', 'javascript'] | 31 |
10,276 | https://devpost.com/software/jinaviard | Inspiration
Jinaviard is a project inspired by choice-driven games like the Henry Stickman series and other story RPGs.
What it does
Jinaviard is a web-based game that tells the story of a hero on a quest to defeat an evil overlord in order to save the world, and there are multiple endings for you to try out.
How it was made
We brainstormed ideas on what to make, and we ultimately decided to create a Story RPG game.
The frame of the pages is completed on the first day, and later during the first day, we brainstormed the idea for the story's scenarios and choices.
During the second day, Richard worked hard to create the Javascript that made the choices work.
Jinkang worked on the story.json file whilst updating the structure to support Richard on the code.
And Octavio made final touches and adjustments to the structure of the page.
Challenges we ran into
There were a lot of challenges we encountered along the way.
Front-end: We had difficulty dealing with scaling and positioning elements.
Front-end manipulation: We had trouble figuring out what was causing various bugs with how the player interacted with the choices.
What we learned
"I learned some logics of Javascript from looking at Richard's script, and I learned the process of creating a project like this." - Jinkang
"I learned about how Javascript becomes implemented with HTML and CSS." - Octavio
"I learned how to use Regex to replace text in URLs and utilize JSON to organize our story." - Richard
Built With
css3
express.js
glitch
html5
javascript
Try it out
hackthecloud-story-rpg.glitch.me
github.com | Jinaviard | A short and complex web-based story RPG | ['Jinkang Fang', 'Richard Yu'] | [] | ['css3', 'express.js', 'glitch', 'html5', 'javascript'] | 32 |
10,276 | https://devpost.com/software/petcare-tracker | Inspiration
In the United States alone roughly 37% of dogs are overweight and 19% are obese. This equates to more than 50% and research has found that these numbers will continue to grow. More often than not dogs are overfed or given poor exercise leading to severe health issues and decreased life expectancy. When we talked to veterinary professionals, they told us how they usually have to calculate the lean weight of the owner’s dog to update the food amount given to their dog on a daily basis. The problem is dog owners usually only go to checkups once a year. That means that the food amount will eventually be invalid, and the dog may be eating too little or too much based on its lean weight progress over time.
What it does
Our app takes in user input of a dog's characteristics and information to determine how much food and exercise the dog should be receiving on a daily basis. What’s unique about our app is that we have an API that will progressively update the age of the dog, and we have our own python machine learning predictive model using Keras that will predict what the lean weight of the dog will be over time since we already know how much the dog is eating every day. The predictive model is graphed on the nutrition page, and you can see key weight milestones for the dog such as when it’s 1 year old, 2 years old, wtc. We also have additional features such as a Vaccine Log that will help the user keep track of all past vaccines and a Behavior Log that will help owners track significant behavioral changes which could ultimately help veterinarians diagnose diseases and problems sooner.
How we built it
We used the Flutter SDK by Google to create an app that can run both on the app store and the play store. The primary language we used was dart, and we worked as a team and split up different pages of the app, and once we were done with our individual work, we merged everything using GitHub. Our key emphasis throughout the app was to have a simple but functional user experience. Most other pet tracking apps only track physical activities or calorie count, but require the user to enter in the calorie amount and exercise time every time the dog eats or wants to go out. We knew this can be disheartening for a consumer to consistently use an app, so our main focus was to have one setup process where you set up your dog’s information when you first download the app, then the user will never have to edit anything again. We also chose a lighter tone for the UI of the app to make it seem more simplistic to the user.
Challenges we ran into
When submitting we ran into technical difficulties since our Zoom calls weren’t working. We also had a lot of challenges with the Flutter software. We also experienced a lot of problems with the animations throughout the app. We wanted to make the user experience as appealing as possible, so our decision to spend a significant amount of time on it led to numerous animation bugs and rendering problems. Issues with implementing the API and other UI navigation issues constantly popped up as well but we worked through it together, and we are extremely proud of the product we produced.
Accomplishments that we're proud of
We are most proud of the nutrition page because there is currently no app that can predict the lean weight of a dog over time, and determine the exact amount of food the dog should be eating. The model required the implementation of an API that could determine time zones, and update the age of the dog over time. This implementation in itself was difficult for us, and we were very proud to see everything work in cohesion. We were also proud of the animations throughout the app and transitions between screens because these ultimately made our app look more professional and appealing for us to use.
What we learned
We learned a lot about how to make an app, and specifically how to implement an API and python back end. This was the first time we had built an app through the Flutter software, and we were excited to create an app which would work for both IOS and Android. We spent quite some time working through the small errors so it was very nice to solidify the basics. We did have experience with the android studio so it made it easier for us to build this app as a whole, but we learned a lot about Flutter and Dart.
What's next for PetCare Tracker
So currently we are focusing on creating a fully functional and viable prototype as there are many features and tweaks we would like to make. Once we do that we plan on running a few Beta trials with Pet Owners and their Vets. At that stage, the revenue would be generated through ads. If our trials prove to be successful we will file for a proprietary license and copy-right the code. We’ve read the USPTO criteria and we believe our app would be eligible for a patent as well since with combination of features, especially the predictive model. For our third stage, we would also generate revenue through a licensing fee if we can work with pet clinics.
Built With
dart
flutter
python
timeszonesapi
Try it out
drive.google.com | PetCare Tracker | A solution to so many dogs in the U.S. being overweight and obese is an app that monitors the dog's health while providing the necessary information to maintain fitness. | ['Akhil Giridhar', 'Kaushik Indukuri', 'Dreadnought202'] | [] | ['dart', 'flutter', 'python', 'timeszonesapi'] | 33 |
10,276 | https://devpost.com/software/covid-19-cases-predictor | Start Screen: Selecting Data of Interest
Initial loading screen for state and county data sets
County - specific data set visuals
Polynomial Regression model button activated (Zoomed in)
COVID-19 Cases Predictor
Creator: Piero Orderique
This COVID-19 Cases Predictor program takes a machine learning approach to battling COVID-19 cases in America. Written in Python using tkinter, matplotlib, and scikit-learn, the easy-to-use UI permits users to display data of their choosing and run a polynomial regression model on the data to see how cases will tend towards in the future.
My Purpose
Mostly inspired by the recent spikes in the COVID-19 pandemic in the United States, I decided to use machine learning to tackle the problem starting at a fundamental community level. Most visuals out on the internet showcase either worldwide, national, or state data. While this data is beneficial to all, I believe that showing visuals at a county level will help bring a more personal awareness of how the pandemic has affected the community around us. Not only does this program make these visuals available to users, but by allowing them to run a regression model, users can further see the potential implications on their communities if the current state of the pandemic continues to grow.
Features
National, State, and County Selection Data
Regression Button that trains the model
Navigation Bar to zoom into more or less recent dates
Evaluation Summary of Model when tested with "outside" data
How it was Built
Python was used for the entire program along with tkinter, matplotlib, and scikit-learn libraries.
What I learned
How to embed graphs into tkinter windows, how to run a polynomial regression model on COVID-data, how to create training and testing data sets
Challenges
A new Navigation Bar object was created every time a new graph was selected, eventually covering the entire screen. Regression model generalization in order to use one function to handle all possible graph selection events.
Future Goals
The current goal is to further develop the regression model to where the program can distinguish between logistic, polynomial, and exponential trendlines and make a decision to which one fits the data best. Furthermore, I would love to take this project into augmented reality to showcase data in 3 dimensions.
Built With
matplotlib
python
scikit-learn
tkinter
Try it out
github.com | COVID-19 Cases Predictor | A machine learning approach to bringing awareness of rising COVID-19 cases at an individualized community level | ['Piero F Orderique'] | [] | ['matplotlib', 'python', 'scikit-learn', 'tkinter'] | 34 |
10,276 | https://devpost.com/software/quarancare | Sign up- doctor
Welcome message
Homepage
Choosing doctor or patient
Log in page
Doctor- chatting with patients
Doctor- sign out
Doctor- profile
Patient- symptoms
Patient- choosing a doctor
Patients- chatting with doctors
Sign up- patient
Patient- sign out
Inspiration
My inspiration for this app is the Covid-19 cases here in Singapore and back in my homecountry, India. Many migrant workers have symptoms related to Covid-19 such as cough and fever, but they did not want to get them checked out as the medical opinion is very expensive and I am sure that these workers would rather provide their family with food instead. I think that this resistance was one of the reasons that Covid-19 has been spreading so much within the migrant workers and I believe that through this app the spreading of Covid-19 could be reduced as people can get free medical opinion on their symptoms.
What it does
What the app does is connect patients and doctors so that they can chat with one another. The focus audience for this app is patients from low-income families who can not afford to pay for medical care and doctors who would like to volunteer to help patients without getting any income. The user can log in and access chats with different doctors/patients.
How I built it
I used xcode to build the app, most of the app is to do with the user inference as well as some code to save the login details and run the app as it should. I used a lot of help from outside sources such as youtube to guide me along the way.
Challenges I ran into
There were a number of frustrating challenges that I faced when the code was not working as it was supposed to, the login and sign up code was especially challenging, especially since this is my first time participating in a hackathon as well as making a mobile app.
Accomplishments that I'm proud of
I am very proud of myself in finishing this app especially in the time constricts of the hackathon. I put in a lot of hard work and sweat and am pretty glad of how the app came out to me. I do think with more time I could have done a little better with the user interface such as how to add profile pictures or perhaps users can choose to share their information or not and adding more features.
What I learned
I think the most important skill I have learned from this hackathon is time managment and perserverance. There are many times late at night when things were not working out and I simply wanted to give up on that app, but I decided to fight through and I am pleased with the solution that came out as I genuinely believe that it could help and connect people all around the world.
Built With
xcode
Try it out
github.com | Quarancare | An app to connect low income families to volunteer doctors in order to get a medical opinion without any cost. | ['Tanya Vaish'] | [] | ['xcode'] | 35 |
10,276 | https://devpost.com/software/hack3 | This is our logo.
Guest Manager
We are Team Yes.
Inspirations
We were inspired to create this application because of the restrictions placed on businesses and public places during COVID-19 as they can only have a certain amount of people in their building at a time. Our project addresses this issue by keeping track of how many people are currently present as well as how many reservations there are.
Learning and Building
Throughout the project, we learned how to work with the current time in Java as well as styling with CSS in Gluon Scene Builder. Our project has two main classes, being the Person class and the GuestController class. The Person class holds information such as their name, phone number, how time they can stay, and the time of their reservation (if they have one). The GuestController creates ObservableLists of Person objects in order to properly display them in the table with all of their information. It also controls the rest of the display for the user.
Challenges
One of the challenges that we faced was figuring out whether the reservation time was AM or PM. In the end, we decided to have the user input AM or PM in the textField so the program could read the last two characters and set up the reminder accordingly. A similar issue to this is verifying that the user entered a valid time. We realized that a user could enter 13:61AM as a time, which makes absolutely no sense. To fix this issue, we had to edit the way that we read the time from the user. Another issue that we faced was with the guests or reservations that were expired. Since both had similar implementations, we got confused quickly when we tried to create methods that applied to both circumstances. Ultimately, we decided to make a set of methods for both guests and reservations.
Another challenge we faced was when manipulating the guest data for guests that expired. We figured out that our problem was that when getting the selected table cells, we are given a readable list, which limited what we can do with it, and caused errors as we tried to manipulate it. Once we converted it to a writeable list, we were able to then apply the changes correctly as necessary.
Built With
css
java
Try it out
github.com | Guest Manager | Guest Manager, the all-in-one-tool for public and private gatherings. | ['Vijay Sreenivasan', 'Adrien Bekker'] | [] | ['css', 'java'] | 36 |
10,276 | https://devpost.com/software/shopala | home screen
users add images of clothing to inventory and say how often they wear it
users can predict cost-per-use of a new item they find by imputing the cost and image of item
based off previously inputted images, the app will predict cost-per use based off how often users wear owned items
Inspiration
Our generation is
obsessed
with online shopping, especially during quarantine. I personally have online shopped a lot, and recently, I have researched about the damage this is causing to our planet and the health of thousands. The textile industry is one of the most
polluting industries in the world
, and due to fast fashion brands like
Zara
and
Shein
, buying cheap, trendy clothing is appealing. However, the waste from making these items is
damaging waterways, using up hundreds of gallons of oil and water, releasing more emissions than flights, and the chemical runoff is leaving people with medical health issues
. We can’t just tell people to stop shopping. Instead we can teach people how to become
smarter
shoppers and help them save money and help the planet at the same time. So, I have developed
Shopala
, the first machine learning shopping assistant app of its kind.
What it does
It calculates
cost per wear of items that users want to buy while they are shopping, based on items the user already has
. When users take a picture of items they want, the machine learning used enables the app to compare the image to previously imputed images of clothing that the user already has. It takes the
cost
of the new item and divides it by
the number of times users wore a similar item
in their closet.
How I built it
I used
react native
to develop the mobile application. I used the React APIs to render the components on a mobile device. I also used
Clarifai API
to incorporate machine learning. I created a custom model to get the model to begin understanding differences among specifically clothing and store
json metadata
of the amount of times users wore that particular item. As users input more apps, the model becomes more intelligent in recognizing differences in apparel, fabric, and clothing types.
Challenges I ran into
Getting the imputed information to enter the model and be set as json metadata for each particular image was difficult. Fetching this data when users selected an image similar to it was also a challenge. However, I read a lot into json metadata and its functionality, and learned a lot considering I have never heard of this functionality prior to this hackathon. After a lot of trial and error, I was able to narrow down the hits of similar images to 10, and have the metadata return. After this point, it was just a simple arithmetic function that provides the user the cost-per-wear value.
Accomplishments that I'm proud of
Creating a whole
custom model
and getting the
json metadata
to work was something that I was surprised to do in just 24 hours. I have some experience with machine learning, but I have definitely refined my skills a lot, and learned about connecting user input into a machine learning model. I also spent a lot more time on
UI
and it resulted in a professional looking application.
What I learned
I learned about more React API features in React Native and implemented them for a better UI. I also learned about json metadata and connecting it with Clarifai custom model API. I was able to use this
cutting edge machine learning technology
to make a mobile application, and develop it to successfully and accurately predict images.
What's next for Shopala
I was pleased that the machine learning aspect works and is accurate, but I would like to continue to develop this app and put it in the app store soon! I want to create a
user profile page
where users can input their name and set some preferences. By doing this, I can welcome the users on the homepage when they enter with a “hi !”. It’s a small touch, but it makes the world of difference because it makes the app more friendly. After all, it is a shopping buddy. In addition, I would like to include an
image gallery
of all the previously imputed images and users will have the ability to remove images, or edit the json metadata of how many times they wear the item in a year. Finally, I would like to improve the
UI
even further. I have gotten amazing advice on moving forward from Vicky Vo, project designer mentor during the hackathon, and have begun to implement some of the features she suggested, but I will continue to edit it. All in all, I am proud that the machine learning worked excellently, and I am excited to continue to develop it following this hackathon.
Built With
clarifai
github
javascript
react
react-native
Try it out
github.com | Shopala | First ever machine learning shopping assistant app that calculates cost per wear of clothing items based off items you already own | ['Nandita Kathiresan'] | [] | ['clarifai', 'github', 'javascript', 'react', 'react-native'] | 37 |
10,276 | https://devpost.com/software/covid-watch-ag9t2i | Inspiration
a
What it does
a
How we built it
a
Challenges we ran into
a
Accomplishments that we're proud of
a
What we learned
a
What's next for a
a
Built With
appy-pie | a | a | ['Mashrur Chowdhury', 'Philip Choi', 'Moe S'] | [] | ['appy-pie'] | 38 |
10,276 | https://devpost.com/software/wecare-5l9dgi | Home Screen of app, which allows you to report your symptoms, check the status of your circle, and get daily personalized tips.
Map Screen of app, which allows you to see hotspots around you and your Care Circle.
Care Circle screen of app, which allows you to health conditions of your loved ones.
Web interface, which can be used to update the symptoms. It is synced with the app.
New logo.
Update with a key.
Hotspots for countries.
Options from the start.
Questions about your health.
Hot spots.
App design
As the outbreak of COVID-19 continues to spread throughout the entire world, more stringent containment measures from social distancing to city closure are being put into place, greatly stressing people we care about. To address the outbreak, there have been many ad hoc solutions for symptom tracking (e.g.,
UK app
), contact tracing (e.g.,
PPEP-PT
), and environmental risk dashboards (
covidmap
). However, these fragmented solutions may lead to false risk communication to citizens, while violating the privacy, adding extra layers of pressure to authorities and public health, and are not effective to follow the conditions of our cared ones. Unless being mandatory, we did not observe the large-scale adoption of these technologies by the crowd. Until now, there is no privacy-preserving platform in the world to 1) let us follow the health conditions of our cared ones, 2) use a statistically rigorous live hotspots mapping to visualize current potential risks around localities based on available and important factors (environment, contacts, and symptoms) so the community can stay safer while resuming their normal life, and 3) collect accurate information for policymakers to better plan their limited resources.
Such a unified solution would help many families who are not able to see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. These urgent needs would remain for many months given that the quarantine conditions may be in place for the upcoming months, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and COVID-19 potential reappearance next year at a smaller scale (like seasonal flu). There is still uncertain information about immunity after being infected and recovered from COVID-19. Therefore, it is of paramount importance to address them using an easy-to-use and privacy-preserving solution that helps individuals, governments, and public health authorities.
WeCare Solution
WeCare is a cross-platform app that enables you to track the health status of your loved ones. Individuals can add their family members and friends to a Care Circle and track their health status and get personalized daily updates on best prevention practices. In particular, individuals can opt-in to fill a simple questionnaire, supervised by our epidemiologist team member, about their symptoms, comorbidities, and demographic information. The app then tracks their location and informs them of potential hotspots for them and for vulnerable populations over a live map, built using opt-in reports of individuals. Moreover, symptoms of individuals will be tracked frequently to enable sending a notification to the Care Circle and health authorities once the conditions get more severe. We have also designed a citizen point, where individuals get badges based on their contributions to solving pandemic by daily checkup, staying healthy, avoiding highly risky zones, protecting vulnerable groups, and sharing their anonymous data.
WeCare includes a contact tracing module that follows the guidelines of Decentralized Pan-European Privacy-Preserving Proximity Tracing
(PEPP-PT)
. It is an international collaboration of top European universities and research institutes to ensure the safety and privacy of individuals.
What we have done during the weekend
Have been in contact with other channels in Brazil and Chile.
We have updated the pitch (extended), app-design and backend connection of the app this week. New contacts with Chile and Singapore. We have also made some translation work with the app. Shared more on social media about the project and also connected to more people on slack and LinkedIn. We have also modified the concept of Care Circle and how to add/remove individuals. Now, the app is very easy-to-use with minimal input (less than a minute per day) from the user. We are proud of the achievements of our team, given the very limited time and all the challenges.
Challenges we ran into
The Hackathon brought together plenty of people of different expertise and skills. There were challenges that we faced that were very unique, as we faced a variety of communication platforms on top of open-source development tools.
Online Slack workspaces and Zoom meetings and webinars presented challenges in forms of inactive team members, cross-communications, and information bombardment in several separate threads and channels in Slack and online meetings of strangers that are coordinated across different time zones. In developing the website and app for user input data, our next challenge was in preserving the privacy of user information.
In the development of a live hotspot map, our biggest challenge here was to ensure we do not misrepresent risk and prediction into our live mapping models.
Also for the testing of the iOS version, we ran to the new restriction of App Store for COVID-related apps, which should be backed up by some health authorities or governmental entities.
The solution’s impact on the crisis
We believe that WeCare would help many families who can see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. The ability to check up on their Care Circle and the hotspots around them substantially reduces the stress level and enables a much more effective and safer re-opening of the communities. Also, individuals can have a better understanding of the COVID-19 situation in their local neighbourhood, which is of paramount importance but not available today.
The live hotspot map enables many people of at-risk groups to have their daily walk and exercise, which are essential to improve their immunity system, yet sadly almost impossible today in many countries.
The concept of Care Circle motivates many people to invite a few others to monitor their symptoms on a daily basis (incentivized also through badges and notifications) and take more effective prevention practices.
Thereby, WeCare enables everyone to make important contributions toward addressing the crisis.
Moreover, data sharing would enable a better visual mapping model for public assessment, but also better data collection for the public health authorities and policymakers to make more informed decisions.
The necessities to continue the project
We plan to continue the project and fully develop the app. However, to realize the vision of WeCare we need the followings:
Public support: a partnership with authorities and potentially being a part of government services to be able to deploy it on AppStore. It also makes WeCare more legitimate. This would increase the level of reporting and therefore having a better overview and control of the crisis.
Social acceptance: though being confirmed using a small customer survey, we need more people to use the WeCare app and share their data, to build a better live risk map. We would also appreciate more fine-grained data from the health authorities, including the number of infected cases in small city zones and municipalities.
Resources: So far, we are voluntarily (and happily) paying for the costs of the servers. Given that all the services of the app and website would be free, we may need some support to run the services in the long-run.
The value of your solution(s) after the crisis
The quarantine conditions and strict isolation policies may still be in place for upcoming months and year, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and possible COVID-19 reappearance next year at a smaller scale (like seasonal flu).
Therefore, we believe that WeCare is a sustainable solution and remains very valuable after the current COVID-19 crisis.
The URL to the prototype
We believe in open science and open-source developments. You can find all the codes and documentation (so far) at our
Website
.
Github repo
.
Pitch:
https://youtu.be/7fMrVqxoPKY
Pitch extended version:
https://youtu.be/Vo0gs3WlptU
Other channels.
https://www.facebook.com/wecareteamsweden
https://www.instagram.com/wecare_team
https://www.linkedin.com/company/42699280
https://youtu.be/_4wAGCkwInw
(new app demo 2020-05)
Interview:
https://www.ingenjoren.se/2020/04/29/de-jobbar-pa-fritiden-med-en-svensk-smittspridnings-app
Built With
node.js
python
react
vue.js
Try it out
www.covidmap.se
github.com | WeCare | WeCare is a privacy-preserving app & page that keeps you & your family safer. You can track the health status of your cared ones & use a live hotspot map to start your normal life while staying safer. | ['Alex Zinenko', 'Sina Molavipour', 'Ania Johansson', 'Hossein S. Ghadikolaei', 'Christian M', 'Seunghoon HAN', 'Tomasz Przybyłek', 'Mohamed Hany', 'Alireza Mehrsina'] | ['1st Place Overall Winners', '2nd Place'] | ['node.js', 'python', 'react', 'vue.js'] | 39 |
10,276 | https://devpost.com/software/no-touch-disinfectant-wipes-dispenser-y7l9g3 | Future idea of the project
Full project
Arduino code
Circuit
The problem
Hey, I am Tanya Rustogi and I got the idea of the wipes dispenser when I was thinking of how Covid-19 is affecting developing countries. My first thought was that to open a wipes container like lysol you need to touch at least two surfaces which can spread coronavirus. Additionally, having a container of wipes per person in an office or school is not realistic due to the shortage of disinfecting wipes. Then came the idea of an affordable, easy disinfecting wipes dispenser that can be used for classrooms to day cares to shopping carts everywhere.
The solution
So what this dispenser does is when an object such as your hand comes within ten centimeters of the sensor, the motor starts moving which is connected to a rod with rolled up wipes on it. The rotation of the motor moves the roll of wipes, causing them to unroll and make their may out of the container.
How to build
So, each of the pins except the ground and vcc on the motor driver are connected to pins on the arduino, which we defined in the code. The trigger and echo pin on the sensor are also connected to the arduino which are defined in the code. Then the ground and vcc of both the motor and the sensor are connected to the ground and vcc of the arduino which is connected to the power. The sensor detects the distance by seeing how long it takes a wave to come back. The code on the arduino makes sure that if the sensor detects something within 10 centimeters of it, it runs the function stepper which causes the motor to run. The container is made from the lysol container, hopefully making it cheaper for developing countries. The container has two holes, one for the wipes to come out from and one for the motor. Then we need to connect the motor to the container which I achieved with tape. The rod connects to the motor which is held on the other side through the hole already provided in the lysol container. Now when the motor rotates, the rod rotates as well.
What’s next
This is just a prototype, with more material, the final product would look cleaner with a box covering the circuits and the pcbs and circuits connected to the container.
What did I learn
I think the most important thing I learned through this experience is time-management due to the time constraints of two days to make the whole thing as well as perseverance to be able to try again despite how many times the circuit and the code did not work as it was supposed to.
Built With
arduino
Try it out
github.com | No-Touch Disinfectant Wipes Dispenser | A prototype of a no-touch dispenser that is easy and affordable to make and could be used from cleaning tables to disinfecting carts. | [] | [] | ['arduino'] | 40 |
10,276 | https://devpost.com/software/alexa-let-s-code | Best Main Prize - Machine Learning - Alexa, Let's Code
Inspiration
With the recent COVID-19 pandemic, students worldwide have transitioned to online schooling. For some students, however, the transition has been harder than for others. Near where Veer lives is the oldest school for blind students: Perkins School for the Blind. Veer had always wanted to help them, and, during these times, he decided to help them when they needed it more than ever. Together, our team worked on an online platform dedicated for the blind and targeted for our favourite lesson: programming.
According to the National Federation of the Blind, COVID-19 has had a disproportionate impact on the blind, with many facing additional challenges during the pandemic. From an education standpoint, blind students and blind parents face uncertainty about the types of electronic materials they will be expected to use for the remainder of the academic year, making it hard for them to keep up with classes. Lastly, it is difficult for the visually impaired to learn how to code on their computer, a challenge which has been exacerbated by the pandemic.
What it does
We utilized a complex tech stack incorporating alexa skills, flask endpoints, rest api's, google cloud speech to text, and a python desktop application in order to build a speech-to-text editor which can listen to speech, translate it to Python code, and then display the code in an desktop text editor. The platform is complete with voice enabled git commands which the user can perform using the amazon alexa.
We used natural language processing to:
Allow the visually impaired to code in python by simply speaking
Provide a handful of voice enabled git commands and speech recognition features to effectively teach coding and version control
Display the spoken code in an online IDE, where one can run it and get the output
How we built it
We used:
Amazon Alexa
Flask
Python
Natural Language Processing
Google Cloud Speech API
Challenges we ran into
At first, we wanted to run everything through Alexa; however, we soon learned that we could not read raw text directly from an Alexa action. Thus we decided to pivot to using Alexa for specific commands and the GCP to intake and process all the commits. We also faced difficulty with time zone differences and staying connected.
Accomplishments that we're proud of
We're proud of how we handled the situation once we figured out Alexa couldn't process raw data. We were able to pivot our project nicely and create a product we're proud about. Despite never having met in person, our team as a group was able to be flexible and adapted to the situation.
What we learned
We learnt how to use speech recognition and execute the code in string form. We also learned more about linking Alexa skills and git commands with Python, as well as connecting to flask endpoints through desktop applications, especially for real-time work. Overall, three of our four teammates learned about Alexa and its compatibility, and we all tried to learn more by combining different technologies together.
What's next for Alexa, Let's Code
We eventually want to push this out for all Alexa users. In addition, we want to connect our application with popular text editors, such as VSC, Repl.it, and Atom. We want to eventually expand our project to more languages and functionalities to ease the life of developers.
Built With
amazon-alexa
flask
google-cloud
natural-language-processing
pyqt
python
Try it out
github.com | Alexa, Let's Code | Using Alexa to empower the visually impaired to code simply by speaking | ['Veer Gadodia', 'Nand Vinchhi', 'Shreya C'] | [] | ['amazon-alexa', 'flask', 'google-cloud', 'natural-language-processing', 'pyqt', 'python'] | 41 |
10,276 | https://devpost.com/software/emergex | Inspiration
We had won the grand prize at an APAC-level hackathon and he got a chance to go to a startup conference in HongKong this summer. But due to the pandemic, it was canceled. Now, we are not sure if we’ll go even if the conference is next year. We realized this would be the case for many travelers, both leisure and business. One of the major problems would be making travelers gain the confidence to travel again. We decided to do something to encourage people to travel, by assuring them of safety.
Problems Tackled
We have created a web-based service that will be sold to various travel websites with add-on safety features and Private tourists spots such as restaurants, hotels, etc for better analysis of the implication of social distancing norms. We plan to solve the following problems:
From the website, the user can get the latest news of the place of travel (Government restriction, Border Closures, etc) along with the number of live COVID cases in that place.
The website also uses a Machine learning model called the RNN which will help predict future trends in COVID places of that particular place. This will help travelers make more informed decisions about their travel dates.
We also incorporated a feature for Touchless travel wherein the user can fill the Immigration or the Custom declaration form via the website to prevent contact at the airport.
We will also mention the safety features of various hotels/restaurants enabling the visitors confident enough to travel those places.
Our Social Distancing ALgorithm along with the mask detection algorithm which will be sold as a service to private tourist places will help in analyzing the implication of such norms on the public.
What it does
We have created software services for hotels, airports, parks, restaurants, museums, theatres, and other enclosed private tourist spots. Our system will automatically detect whether people are following social distancing and whether they are wearing masks or not, from CCTV footage. These places can advertise that they’re using an automated system to ensure safety, and this will attract more tourists. The other facet of our solution is a website for travelers/tourists. This service can be used by any travel company as an additional service to the users. Users can pick a destination and a date of interest. We will show them the updates of that city, and give the estimated number of cases along with news of that place. This estimation is based on a predictive ML model. This will help users make an informed decision and they can postpone their trip well in advance, without losing out money on cancellation charges. This will also help air travel companies and hotels, who have to bear losses if a person cancels their stay. Lastly, an online immigration form will be provided to minimize physical touchpoints.
How we built it
We have taken a sample recording of the CCTV camera footage. A machine learning model detects and classifies various bounding boxes based on the distance between people in the video. Also, we have the Mask detection algorithm which was built using CNN and it checks whether people are wearing a mask or not and creates a bounding box around the face. So the viewer knows the number of people violating the norms. These models were built in Python. For COVID trend prediction, we had used the RNN model.
For news and daily updates of the COVID cases, the data is scraped online and displayed on the website available online. The website for travel users (of the hotel, market, tourist spot) was built using React, Firebase, and Node.
Challenges we ran into
Data Privacy was the one challenge we encountered during this Hackathon. However, the service which we will be providing will enable the private tourist places to analyze the data and count the number of people maintaining the social distancing norms without giving any private information of the person from the CCTV frames. The clients will just have to push the data in the backend for our analysis so that we can give them a safety rating. In the future, we plan to add a pipeline which will blur the faces of the people present to provide an even safer and secure service.
Accomplishments that we're proud of
We are proud of the fact that our project will help many travelers, both leisure and business in the aftermath of this pandemic. We will be providing one of the major strengths to travelers that are gaining confidence to travel again. We are really happy to be part of the change that will boost & encourage people to travel safely.
What we learned
We learned the importance of team work and work together even though not being in touch physically. We interacted online and distributed task to each other. We learned to ideate and come up with an innovative solution in a short span of time. We faced many challenged while the hackathon but we were determined to go on and we persevered.
What's next for EmergeX
The next plan would be to host our entire web application on the cloud. The ML models and the backend will be deployed on the cloud. In phase 1, we would like to try out this solution locally. We will tie-up with local hotel chains and tourist spots in Mumbai and devise a basic billing plan to start earning revenues along with other travel agencies so that they can use our web app as an additional module or service. We will also release our app for tourists on the play store. After these iterations and learning from the results, we would like to partner with more places and or a company like Trivago which can in turn sell these services to its partners.
Built With
angular.js
machine-learning
node.js
python
Try it out
github.com | SafeT | Every life counts | ['Vedant Kumar', 'Siddhant Kumar', 'Pradhuman Singh', 'Parth Shingala'] | [] | ['angular.js', 'machine-learning', 'node.js', 'python'] | 42 |
10,276 | https://devpost.com/software/spark-cdr0kl | Inspiration
Over the past decade, Northern California has been constantly plagued with hundreds of inevitable wildfires, many of which are sparked by malfunctions in the power grid. As utility companies like PG&E have utility lines spanning thousands of miles, routine checks on each of these lines can only happen once a year, so vegetation around utility poles can grow out of control and come into contact with power lines.
What it does
It is a simple-to-use iOS application that helps anyone with an iOS device seamlessly notify utility companies of hazardous situations such as a tree branch leaning on a utility pole or power line, which could potentially start a fire. It’s quick, accurate, and very helpful for utility companies to use.
How we built it
The application was built using the Swift Programming Language via the XCode IDE. We started with developing the UI of the application to make it responsive and easy-to-use. Next, we programmed the logic of the buttons and saving the data in Google Firebase Realtime Database. Using the CocoaPods Framework, we were able to file a report into the database sending the report information and a picture. We also created a website using HTML/CSS/JS to be able to present the data extracted from the Firebase Database and display that for utility companies to view. We finally added the Map to pin-point the user locations.
Challenges we ran into
Particularly, sending the image that the user took of the incident to the database was very hard to master. Unlike text, where you can just send data as a string to be displayed as such in the database, images have completely different protocols for transmissions.
Accomplishments that we're proud of
Other than this, finding bugs were the most rewarding yet frustrating part of the experience, as we learned that nothing is more fulfilling than fixing a SIGBART fatal error. However, being stuck trying to solve that same error lends a feeling of hopelessness, and so the duality of the experience really appealed to us.
What we learned
By the end of development, we learned a lot about troubleshooting and teamwork, as even the most minor problems once seemed like impossible obstacles to overcome.
What's next for Spark
So far, our solution has the potential to save the state of CA millions of dollars because it solves a problem that would otherwise be addressed using expensive hardware systems that, as estimated by the California Public Utilities Commission, could cost well over five million dollars. PG&E has been proposing many solutions to this issue, but none have been passed because of the hefty price tags of these propositions. This is why we would like to create a second version of the application that can create a complete database of every utility pole in the state of California.
Built With
cocoapods
css
firebase
html
javascript
swift
Try it out
drive.google.com | Spark | Spark is an application created to simplify the process of reporting potentially hazardous vegetation and wires near power lines and utility poles. | ['Aditya Sharma', 'Ishan Goyal'] | [] | ['cocoapods', 'css', 'firebase', 'html', 'javascript', 'swift'] | 43 |
10,276 | https://devpost.com/software/remote-elderly-home-care-via-privacy-preserving-surveillance-9mrdgx | Privacy preserving person face detection at home
Plug and Play AI device discovery
Home Page
Person detection indoors
Person detection outdoors
Inspiration
COVID19 isolated at home many of us, including our elderly parents and grandparents. Not being able to check on them regularly elevates the risks that they are exposed to such as falls, gas leaks, flooding, fire and others.
What it does
Ambianic.ai is an end-to-end Open Source Ambient Intelligence project that removes the stigma associated with surveillance systems by implementing privacy preserving algorithms in three critical layers:
Peer-to-Peer Remote access
Local device AI inference and training
Local data storage
Ambianic.ai observes a target environment and alerts users for events of interest. Data us only available to homeowners and their family. User data is never sent to any third party cloud servers.
Here is a blog post that goes into the reasons why we started this project:
https://blog.ambianic.ai/2020/02/05/pnp.html
And here is a technical deep dive article published in WebRTCHacks. It clarifies that it is absolutely possible to build a privacy preserving surveillance system, despite popular cloud vendors making us believe that all user data belongs safely on their cloud servers:
https://webrtchacks.com/private-home-surveillance-with-the-webrtc-datachannel/
How we built it
Ambianic.ai has 3 main components:
Ambianic.ai Edge: a Python application designed to run on an IoT Edge device such as a Raspberry Pi or a NUC. It attaches to video cameras and other sensors to gather input. It then runs inference pipelines using AI models that detect events of interest such as objects, people and other triggers.
Ambianic.ai UI: A Progressive Web App written in Javascript using Vue.js and other front end frameworks to deliver an intuitive timeline of events to the end user.
Ambianic.ai PnP: A plug-and-play framework that allows Ambianic UI and Ambianic Edge to discover each other seamlessly and communicate over secure peer-to-peer protocol using WebRTC APIs.
Challenges we ran into
Challenges include selecting high performance, high accuracy and low latency AI models to detect events of interest on resource constraint edge devices.
Another challenge is taking into account user local data to fine tune AI models. Pre-trained models can perform reasonably well, but they can be improved with privacy preserving federated learning on unique new local data.
Accomplishments that we're proud of
Ambianic.ai has been in public Beta for several weeks helping a number of users in their daily lives. Some users report success in keeping an eye on their elderly family members:
https://twitter.com/mchapman671/status/1230931722650423299
What we learned
Although the project sets ambitious goals, there seem to be sufficient enabling Open Source frameworks and community momentum to drive the ongoing success.
What's next for Remote Elderly Home Care via Privacy Preserving Surveillance
We need to work on these major areas:
Recruit volunteers in the home care community to test the system and provide feedback
Select more models to address open use cases such as fall detection, gas leaks and others
Work on implementing Federated Learning infrastructure to fine tune initial pre-trained models.
Built With
javascript
pwa
python
raspberry-pi
tensorflow
webrtc
Try it out
docs.ambianic.ai | Remote Elderly Home Care via Privacy Preserving Surveillance | COVID19 isolated at home many of us, including our elderly family members. Left unattended they are prone to risks such as falls, gas leaks, flooding, fire and others. | ['Björn Kristensson Alfsson', 'Yana Vasileva', 'Ivelin Ivanov'] | ['Best EUvsVirus Continuation', 'Best Home Care Project', 'Best Platform'] | ['javascript', 'pwa', 'python', 'raspberry-pi', 'tensorflow', 'webrtc'] | 44 |
10,276 | https://devpost.com/software/ar-anatomy-827wgq | Ar view
Inspiration
As we know that this pandemic is really tough for us so I made an AR app which will help the people as well as the doctor
What it does
It will give the virtual world related information of our body parts.
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for AR Anatomy
Built With
augmented-reality
echo-ar
Try it out
drive.google.com | AR Anatomy | AR based app for the hospital | [] | [] | ['augmented-reality', 'echo-ar'] | 45 |
10,277 | https://devpost.com/software/fundit-4mti2o | Login
Highlights
Startups Pitchs
Payments
fundIt
A platform that democratizes access to capital for small businesses via crowdfunding
Inspiration
Startups founders don't have those connections or profits to get funding and especially in a year full of uncertainties many big investors are scared to invest in small businesses. And not all startups makes million dollars in their beginning years.
Meanwhile, most people are not as rich but want to invest. So we want to build a platform that benefits color businesses (because majority of them are quite small) and Investors both. Startups put their video pitches to help make investor a decision on the startup and investor can make an appointment with the business to know about their future goals before investing.
What it does
fundIt is a an app for small businesses to get crowdfunding by retail investors for equity.
Users can login and authenticate their credentials via Apple/Google/Email
Startups can post data such as PDFs, Images, and Text to supplement their crowdfunding campaign and help investors to make investment decisions
Investors can browse all campaigns via a Tab view
The most unique feature of this platform is the highlighted businesses of the month. Underrepresentation and discrimination is a huge problem in business investments so we want to represent those businesses by having a separate page for them.
Investors can schedule a virtual meeting with the representative of startup that will help investor know about the future plans of the business
Investors can pay as little as $10 for a share in the startup’s equity offered in the crowdfunding campaign
Investors can view their past investments & their total investments on a profile view
Startups can checkout the funds raised from the crowdsourced campaign via Apple/Google Pay to Apple/Google Wallets in a virtual FundIt card
How I built it
Flutter: Dynamic Mobile Applications that runs both on Android and iOS.
Firebase: For authentication
Square: Payment Processing
SQL: For storing the Business and Investor Information
UiPath: For automating the process for investors displaying startups according to their search history
Potential Users
Retail investors - who will be investing in the companies that are listed on our platform
Startups - they sign up for crowdfunding in exchange for equity.
Challenges I ran into
Payment Processing using Square
Automation with UiPath
Making dynamic user interface for startup took some time to apprehend
Accomplishments that I'm proud of
Able to build a working platform with a great team work in such a short time.
What we learned
Learned how to divide tasks as a team and be accountable for it, setting report time
How to do payment processing
What's next for fundIt
We are planning to reach small businesses and small investors who could benefit from each other. Small businesses by getting money and small investors by getting returns on their investment with as little as 10 dollars.
Domain.com
FundIt.space
Built With
dart
firebase
sql
square
uipath
Try it out
github.com | fundIt | A platform that democratizes access to capital for small businesses via crowdfunding | ['Rupakshi Aggarwal', 'Sulbha Aggarwal', 'Rishav Raj Jain'] | ['1st Place'] | ['dart', 'firebase', 'sql', 'square', 'uipath'] | 0 |
10,277 | https://devpost.com/software/cognito-bnup5t | Note
We had the individual AI and Keylogger working, we were unfortunatley unable to combine them and thus there was no demo. To watch the individual demos for the AI and Keylogger you can go down to demo videos.
Inspiration
Every year thousands of people are diagnosed with Parkinson's. Many times its too late and their relatives are forced to watch as they become shells of the humans that they once were. The worst part is that Parkinson's is often difficult to detect and can be tricky to diagnose.
We wanted to create something that could help detect Parkinsons in a quick and efficent way, without being obtrusive or expensive.
Thus we present Cognito
What it does
Cognito is very simple
Cognito has a key logger which tracks specific typing metrics. Cognito stores these metrics which are then analyzed by an advanced AI algorithim which detects for signs of Parkinson's. If Cognito detects signs of the disease it will send an email alerting the user about the issue.
Cognito is a simple background script that doesn't need an internet connection and is simple and hassle free.
Cognito has plenty of potential as typing can not only be used for Parkinsons, but for many other dieases as well such as Huntington's and Alzheimer's Disease.
How we built it
We used the neuroQWERTY dataset and keras to develop an algorithm which detects whether or not a user has Parkinson's.
We then used python to develop a simple keylogger that tracks the metrics which the Algorithm will need to analyze.
Challenges we ran into
Developing the Algorithm was incredibly difficult. It took a lot of time and was difficult to debug. It was the group's first time working with numerical classification in AI.
Accomplishments that we're proud of
We are proud that we got the AI algorithm to work. It took a lot of time and effort, but it payed off!
We were also proud that we could detect such a deadly disease with such a simple metric... typing!
What we learned
We learned how AI works and how to use it and learned how to do key detection with python. For two thirds of the group it was their first time working with any sort of AI at all so this was a new and fun journey for all!
What's next for Cognito
We would like to develop our algorithm even further. Unfortunatley, Cognito has a 50% accuracy, however with the discovery of some new datasets and with the ability to spend more time with the Algorithim we feel confident that we could get the prediction to over 70%.
We then plan to release this so that we can start helping people all around the world!
Demo Videos:
Keylogger:
https://www.youtube.com/watch?v=iiWSOhdJlaA
AI:
https://www.youtube.com/watch?v=YuE35_pRSeE
Discords
CantTouchThis#8155
theaditya24#8701
anishfish#5103
Citation
Arroyo-Gallego, Teresa et al. “Detecting Motor Impairment in Early Parkinson's Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting.” Journal of medical Internet research vol. 20,3 e89. 26 Mar. 2018, doi:10.2196/jmir.9462
We used a few studies for inspiration and we used the neuroQWERTY dataset. The keylogger and the algorithm were our own however.
Built With
keras
keystrokes
machine-learning
python
smtplib
tensorflow
Try it out
github.com | Cognito | Detect Parkinsons with the power of typing and AI | ['Anish Karthik', 'Gaurish Lakhanpal', 'Aditya Tiwari'] | ['2nd Place', 'MacroTech Sponsored Prize', '2nd Place'] | ['keras', 'keystrokes', 'machine-learning', 'python', 'smtplib', 'tensorflow'] | 1 |
10,277 | https://devpost.com/software/privacypedia | Home
Instagram
Facebook
Netflix
Information
Inspiration
Today, no one bothers reading Privacy Policies or Terms and Conditions, and companies can easily gather as much information as they can from us. So I decided to make Privacypedia in order to raise awareness of how these large corporations handle our data.
What it does
Privacypedia summarizes a company's Privacy Policy and gives it a rating between 0 and 10 based. This is done through the PrivacySpy API. The app also provides recourses for the user such as the company's privacy policy and its website.
How I built it
I built the app with Dart and used the Flutter framework. I also used many libraries such as Google fonts, URL launcher, HTTP, and a lot more.
Challenges I ran into
Since this was my first ever Flutter app, I ran into many errors and spent countless hours debugging. One specific problem I encountered was trying to read and parse a JSON file. This was especially hard since I mostly have experience with non strictly typed languages such as Javascript.
Accomplishments that I'm proud of
Walking into this hackathon I had no experience with Flutter, so I'm pretty proud of the end result.
What I learned
I learned how to:
Use Rest APIs in Dart
How Flutter widgets work
How to parse JSON in Dart
Future and async functions
A lot more!
What's next for Privacypedia
In the future, I'd like to add a search bar to make it easier to navigate between companies.
Built With
dart
flutter
Try it out
github.com | Privacypedia | Privacypedia summarizes privacy policies to help people be mindful and aware of their data. | ['Seif Abdelaziz'] | ['3rd Place'] | ['dart', 'flutter'] | 2 |
10,277 | https://devpost.com/software/covid-19-rakshak | NEXTGEN HEALTH CARE DEVICE 2
UVC CHAMBE#R
NEXTGEN HEALTH CARE DEVICE
BEDS FOR COVID 19
BEDS FOR COVID 19 2
HANDSFREE BASIN
Inspiration
During this Global Crisis of COVID -19, Our Doctors, Nurses, Police, etc working on the frontline against this. So, why are we falling back? After all, we are engineers with an innovative mind. Now, we are here with the combined Hardware and Software solution, after analyzing some problems. And, try to make the next generation Healthcare Device for Protecting Vulnerable Population during and after this pandemic situation.
Nowadays, COVID-19 patients are facing issues in finding beds in hospitals. They have to go to different hospitals and check if the bed is available or not. And even if the beds are available then they have to make sure that it is affordable.
During the COVID-19, we are facing a lot of disasters like cyclones in Orissa, West Bengal, Maharashtra, etc. and floods too. Also, many people have lost their lives and many people are missing. Lots of parents have lost their children during these disasters.
What it does
There is a Hardware setup that consists of a self shoe sole sanitation device, health band, and hand-free basin. So, the pedestal comes near to our setup and stands over it through that way the shoe sole is sanitized by UV light (this way restricts the transmission of coronavirus through shoe sole). Then, there is a health for which users connected our app with the setup through bluetooth, which measures Heart Rate, Blood Oxygen Saturation Level and Body Temperature, and get the whole data over the app. In last, there is the contact-free basin to wash their hands in public spaces ( everyone washes their hands without touching the tap, which means restricted the transmission of the Coronavirus through the surface and reduces wastage of water).
We have made an app, to find the number of beds available in the hospitals in the city they live in. The app will show the number of available beds in different hospitals and will tell the price too.
KHOJ will help to find a missing person. The guardian of the missing person will upload the details of that person, so the image will be added to the KHOJ database.
If any person finds a person who was missing, he can also upload the picture of that person through KHOJ.
KHOJ will try to find that person in the database, and if found it will notify the nearest police station from where the person is found and the guardian of the missing person.
How we built it
In the Hardware setup of this project, shoe sole sanitization device by using UV-C type and its choke, contact-free basin by mechanical parts like the pedal, spring, metal wire, cistern, etc and health band is done by Arduino Uno, Max30102 (for Heart Rate and Blood Saturation), Ds18b20 (for body temperature ) & Bluetooth HC-05.
We build our app on Flutter which is a hybrid platform using dart language. Because Flutter apps can run on ios and android phones. Then, we used an API provided by disease.sh for details related to COVID-19 like total cases, active, deaths, etc.and did some other stuff also with our skills.
Challenges we ran into
Due to lockdown, we don’t have NodeMCU (IoT device) to store data over the cloud. So, we try to figure out this with Arduino Uno and Bluetooth. First, we send data over the mobile app than over firebase to store.
Accomplishments that we’re proud of
Working, health band with real-time data functioning backend servers for data management easy to use app which can present real-time data to the user over the app.
What we learned
Learned a lot about that without having an IoT device, how to store data over a server and also, about the new sensors.
Moreover, it built a more functioning mobile app.
What’s next for the team
In terms of enhancing the project, we can identify the user’s state of mind using EEG or GSR reading & Machine Learning. Also, determine blood pressure through self-test kiosk.
In terms of marketing the product, we would like to initially target public spaces in our region.
Built With
android-studio
arduino
bluetooth
bootstrap
django
Try it out
drive.google.com
docs.google.com | COVID-19 Rakshak | COVID RAKSHAK (#atmanirbhar) - Beds for COVID-19; NEXTGEN Healthcare Device; UVC Chamber; Hands free basin; Find, missing people during disasters; | ['Anubhav Sinha', 'Keshav Bathla', 'Kaushal Bhansali'] | ['Best Hardware Hack'] | ['android-studio', 'arduino', 'bluetooth', 'bootstrap', 'django'] | 3 |
10,277 | https://devpost.com/software/tobedecided | Inspiration
Inspired by the situation in Delhi, India, wherein people who get the report of "COVID-positive" are expected to visit a hospital and queue up for hours together for
a chance to get a bed
at the hospital. If they do not get a bed, they go to another hospital, queue up for hours, and
hope
for a bed there too. This movement of COVID-19 positive patients from hospital to hospital and queueing up is troublesome in two of many ways. Firstly, this movement increases the risk of spreading of the virus itself as these patients visit many different hospitals in the hope to get a bed, thereby infecting so many different places. Secondly, these patients do not get immediate care, and are forced to spend time waiting in queues.
An added problem arises in beds being "booked" by people in power and those that can pay the highest for that bed. A news report featured a shocking amount asked by a COVID-19 patient of 1 lakh INR (£1061) per bed per night. During the current times of pandemic, corruption in healthcare must be condemned. Beds must be allotted based on case severity and not on the amount of money.
This inspired us to make an application that would help overcome these issues, and be able to allot a bed to the person, most in need, without them having to queue up and go hospital-to-hospital.
What it does
What if we could automate this system of "queueing-up" for a bed? What if we could have a system wherein COVID-19 positive patients would know exactly which hospital to go for a guaranteed bed, at the ease of their phone?
Keeping this in mind, we created a mobile application that lets:
1) COVID-19 patients look at bed availability in hospitals nearby,
2) COVID-19 patients send one e-application (through the app) for a bed to hospitals within 10km radius, by filling in details (such as age, past illnesses, travel history etc.) and attaching COVID-19 positive report scan,
3) The Machine Learning algorithm predicts and ranks the severity of the case/e-application using these details per bed space,
4) Based on the results of the ML model, hospital officials can be suggested on who the bed should be allotted to instead of allowing officials to indulge in allotting the bed to the highest bidder (the one with most money)
5) A hospital then allots an available bed to the most critical case/application after which the case/application is marked as "Treated" on the database of applications, which would signal to other hospitals that this particular case has already been catered to
6) The person who has been allotted the bed, gets a notification and a set time to arrive at.
In other words, we are creating a database of beds and the applications for those bed spaces, which are then ranked on the basis of severity using questions answered by the patient. The most severely ranked case gets a bed. This process brings about transparency and helps cater to those who need it most. It would aid in removing any corruption that exists in allotting bed spaces.
How we built it
The steps we followed for creating the ML model are:
1) Acquiring the Dataset: We found an appropriate dataset for this particular use case, on Kaggle.
2) Data Visualisation: We tried to visualise the data using various techniques and plots. We built correlation matrices, scatter and density plots, histograms to see which symptoms affected severity the most.
3) Data split: We split the data into 70:30 train:test.
4) Training: We trained the random forest classifier model on 70% of the data.
5) Testing: We then tested the model using the rest of the data.
6) Evaluation: We used various evaluation metrics to judge the performance of the model. It possessed a mean score of roughly 74%.
We then designed the app 'Covey', keeping in mind a simple user interface allowing easy input of data from the user point of view.
Further, we included a code written in JavaScript, which involved the Twilio framework to develop a messaging system to notify a patient if they have been allotted a bed at a hospital.
Challenges we ran into
Finding an appropriate dataset was the hardest task. This is because of the limited research on the ongoing pandemic. Secondly, downloading a few libraries that would satisfy the version requirement, took a significant bit of time and debugging.
What's next for COVID-19 Automatic Bed Allotter
We wish to increase the accuracy of our ML classifier and train it on a more intensive dataset, which includes more combinations of symptoms and other illnesses.
We are hoping to completely integrate the ML model with the app. Also, we hope to automate the notification being sent after a bed is allotted, as currently it requires a prompt to run the code which then triggers a notification.
Try out our App!
https://xd.adobe.com/view/3dbb8b3d-33da-4aca-9b7e-68ef428f888e-68e8/
Built With
adobe
javascript
machine-learning
node.js
python
random-forest-classifier
scikit-learn
twilio
Try it out
xd.adobe.com
github.com | COVID-19 Automatic Bed Allotter | Allotting hospital beds to those who need it the most in a fair and transparent manner. | ['Arun Venugopal', 'Arushi Madan'] | ['Best COVID-19 Hack'] | ['adobe', 'javascript', 'machine-learning', 'node.js', 'python', 'random-forest-classifier', 'scikit-learn', 'twilio'] | 4 |
10,277 | https://devpost.com/software/corona-tracker-d4w803 | coron*A* t*R*acker
Inspiration
COVID-19 has impacted everyone, we wanted to make people more aware about the situation and give them live updates of the cases. This app is built to bring information to everyone by eliminating effort barriers.
What did we learn?
We learn to work with echoAR (augmented reality software).
How did we built it?
We built the app using node.js and echoAR.
Challenges we faced?
None of the group member has experience working with echoAR or augmented reality, so it was challenging at the beginning. But with great team work we overcome the challenge and were able to implement the user stories we had in mind.
How does it work?
coron*
A
* t*
R
acker visualize live updates of virus cases using **A
ugmented **R
*eality.
Scan the QR code from the app ( or print the QR code and paste it anywhere ).
Click the pop-up message to get redirected to echoAR's website.
Keep your camera pointed to QR code to see the 3D model and text appear on the top of the QR code
What's next?
Given more time, we would implement additional statistics, user-location-specific qr codes applicable to other countries and individual provinces/states, and provide additional support on our website for these qr codes.
Contact Us
shagunphw@gmail.com
Built With
css3
echoar
express.js
html5
javascript
node.js
Try it out
github.com
corona---tracker.herokuapp.com | coronA-tRacker | coronA tRacker is an echoAR-powered information delivery tool designed to visualize COVID-19 cases using augmented reality | ['Shagun Shagun', 'Ronald Liang', 'TerryLun'] | ['Best echoAR Hack'] | ['css3', 'echoar', 'express.js', 'html5', 'javascript', 'node.js'] | 5 |
10,277 | https://devpost.com/software/book-drop | Opening screen
Login page
Home page
Search bar
Book Information page
Message page
Chat function
Message widgets
Schedule widget
Profile page
Map page
Inspiration
The rise of COVID-19 cases around the globe has isolated people in their homes. Ensuing social distancing, however, has contributed to a different pandemic: loneliness. According to a Jama Network Journal, adults are three times more likely to report that they're in severe psychological distress during this time. So, how do we connect people to prevent loneliness when isolation is their only option?
What it does
In response, we’ve developed a local book trading app, Book Drop, that facilitates contactless in-person and online social interaction by helping users give out books they no longer want in exchange for books they do want to read. Our only requirement is that users include handwritten notes or drawings of book-related or encouraging content during each exchange.
First, we’ll recruit volunteers interested in starting and decorating a box. In return, they’ll receive service hours and 12 of Book Drop “credits.”
To elaborate on our credit system: New users will start off with 1 “credit” that’s used to request books. Correspondingly, users who drop off the request book with a handwritten/hand-drawn note will receive 1 credit. The note can also be featured on our home page based on their content, appearance, and sincerity. Users with featured notes will receive 1 credit.
When users receive a book request from someone, they can choose what time and which box to drop off the book using the built-in calendar widget in our message function. After users drop off their book, they’ll confirm it through the calendar to notify the requesting user, who will be then required to confirm they have received the correct book and a handwritten note when picking up. Afterwards, Book Drop will reward the dropping user with one credit, and deduct one from the requesting user. Lastly, based on their trading experience, both users will rate each other, which will be publicly visible on both user’s profiles.
How we built it
We built the interface through Figma with some elements designed in Photoshop and Canva. We attempted to implement by coding on Swift.
Challenges we ran into
Idea wise, we brainstormed back and forth to make the idea more comprehensive and feasible. We also struggled to code the app on Swift, since we did not have any prior experience.
Accomplishments that we're proud of
We are proud that we came up with a highly practical design that connects people better than just virtually but stil remains contactless as to protect people’s safety during COVID-19 pandemic.
What we learned
We learned how to brainstorm feasible ideas and how to turn words and descriptions into interfaces and designs on Figma. We also learned about the fundamentals about Xcode on Swift.
What's next for Book Drop
The next step for Book Drop will certainly be implementing the design through programming on Swift. We will also need to do more research on cloud computing, machine learning, and data analysis.
Built With
figma
swift
Try it out
www.figma.com | Book Drop | Sharing books nonstop | [] | [] | ['figma', 'swift'] | 6 |
10,277 | https://devpost.com/software/intheloop-4gjy1o | Twitter feed
Twitter and Youtube feed with several creators
Searching for Youtube Channels (no input for other platforms needed)
Filtering the feed by creator and platform
Inspiration
We were inspired to make InTheLoop after school ended and we were left inside to rot all summer. We found it hard to catch up with entertainment as well as educational content, so we decided to make a web app that would help us with that specific concern
What it does
The web app is an aggregator of several social media pages and posts (such as YouTube and Twitter) of specific creators that can be chosen by the user. The web app will utilize YouTube and Twitter APIs originating from the creator and will be displayed onto a feed in chronological order. All platforms are derived from a single Youtube channel with no user input needed besides the initial search for a creator.
How I built it
We used CSS, HTML, JavaScript, Node.js, as well as APIs to build the web application.
Challenges I ran into
None of us have used such complex APIs such as the YouTube Data v3 API and the Twitter API, so we had to use a complicated method to make it work with our web application. Getting a constant feed of videos in chronological order and sorting them was also challenging.
Accomplishments that I'm proud of
The website looks professional, minimalistic, and our program works smoothly and quickly to deliver feed as well as filter them out.
What I learned
We learned CSS formatting, Modern JavaScript and async functions, how to handle complex APIs, and JSON parsing, as well as Node.js.
What's next for InTheLoop
More platforms (Instagram, Facebook, Reddit). Formatting and porting for mobile with design alterations. Customized feeds (like the YouTube Recommendation Algorithm) instead of checklists.
Built With
css
html
javascript
node.js
twitter
youtube
Try it out
github.com | InTheLoop | This project compiles posts and videos from a content creator from different social media platforms after the input of a single Youtube channel. | ['Jay Patil', 'adrian zhang'] | [] | ['css', 'html', 'javascript', 'node.js', 'twitter', 'youtube'] | 7 |
10,277 | https://devpost.com/software/tutor-hub | Inspiration
We were inspired by a mental health app that supported those with mental health issues such as depression cope by connecting with mentors live through a chat interface. We also were familiar with homework help websites and their short comings, particularly the fact that they did not offer a live chatting service meaning that questions could take days or even weeks to get answered. Furthermore, the lack of distinction on those sites between teachers and students led to numerous incorrect answers. We realized that the live messaging feature could be implemented to improve the homework help space
What it does
Users can sign up to be students, tutors, or teachers. Teachers must be approved by the app and tutors must be approved by an existing teacher on the platform. Both students and teachers interact in two spaces. A hub where questions can be posted for later responses and a chat interface for immediate responses
How I built it
I built this app using android studio and in addition to its sql lite packages. The GUI and for all the parts of the app were coded in xml files while the back end code linking the pages together was coded in java. I also utilized sql lite to safely store log in information.
Challenges I ran into
I had no previous experience with SQL and it took many hours to dully understand all the commands and how to use them.
Accomplishments that I'm proud of
I'm proud of the User interface as I imported many images and focused on small details to get it looking good
What I learned
We learned how use databases for sign up pages and how to create a more professional looking app in general.
What's next for Tutor Hub
We hope to start a business and take our project live in the near future
Built With
android-studio
java
sqlite
Try it out
github.com | Tutor Hub | Connecting teachers, tutors, and students with live chats and calls as well as educational posts | ['Tejas Vissapragada', 'Deep Karjala'] | [] | ['android-studio', 'java', 'sqlite'] | 8 |
10,277 | https://devpost.com/software/virtual-fridge | Home
Sign Up
Login
Recipes List and Search
Virtual Fridge
Publishing a Recipe
Recipe Page
Recipes YOU can Make (e.g. if you only have ingredients for Chocolate Brownie)
Inspiration
Some of our member's families were affected by COVID-19 and they were unable to go to restaurants and eat. So, they were forced to cook at home. However, they were already stressed due to COVID-19 and they didn't want to deal with the extra work of finding a recipe that was to their tastes, as well as possible to make using their stored food. So, we came up with the idea of Virtual Fridge that solves this problem.
What it does
Virtual Fridge provides users with a powerful tool intended to make their favorite recipes given the ingredients that they currently have (Virtual Fridge keeps track of the user's ingredients and can filter out the ones they can make only). As well, we provide users with the option to share their own recipes and experiences! All of these features allow Virtual Fridge to truly become a "smart fridge" that will help you quickly find a recipe that you can make as well as fits your tastes.
How we built it
Python Django Backend and Server Side Routing
HTML CSS front-end, Dynamic Template
Firebase Realtime Database, Storage and Authentication used
Challenges we ran into
No one had any experience with Django! This made it very hard to debug code.
No one had coded a firebase python backend, or used pyrebase either.
Only a few of us knew decent CSS.
We ran into some problems with Repl.it and github, which slowed down our progress.
Some algorithms only worked by itself, but did not work with the project due to not being familiar enough with the django, pyrebase (firebase) datastructures, so had to be left out.
Accomplishments that we're proud of
A social media like network for recipes
Conquered a new framework from scratch
Working algorithm that sorts recipes based on the amount of matched ingredients and the amount of missing ingredients (in reverse)
Amazing team coordination
Features
Login and Sign Up
: Secure OAuth2.0 Firebase authentication system
Dashboard
: Drop down bar on top with options: search, my favorites, share recipe, my fridge, popular recipes and recommended recipes
Search
: just a search bar with a select bar on the side where you can select if you're looking for desert Italian food Chinese etc.
My Virtual Fridge
: A place where the user can input all their ingredients
Publish a Recipe
: A place where the user can share their own recipe, and list of ingredients, also a text box to be filled with a characters description
Featured Recipes
: Top 8 recipes
View All Recipes
: View the entire catalog of shared recipes
Recipes You Can Make
: A list of recipes which are made based on what you have the ingredients for
What I learned
We learned Django from scratch for creating websites!
We learned how to setup routes, making a python backend, setup authentication, connect to the database and handle images even!
Coordination over Repl and system design as well.
What's next for Virtual Fridge
There are multiple ways Virtual Fridge can be improved.
We include a scanning service that scans the receipt and automatically inputs the ingredients that you bought. Alternatively, we include a scanning service for self-checkout
A delivery service that delivers all of the ingredients you need for the rest of the week. The user would choose the dishes that they want to eat, and we get the ingredients delivered from a local grocery store to the address of the user.
A ranking system that ranks recipes based on likes, dislikes, and reviews. Currently, we sort the recipes based on the culture it's from, the time that you eat it, etc. However, we could implement a ranking system to automatically rank the recipes.
Built With
css
django
firebase
html5
pyrebase
python
Try it out
github.com | Virtual Fridge | Virtual Fridge is an online fridge designed to take away the need to ask, whats for dinner? We automatically do this for you, providing you with a meal that you can create and that fits your tastes. | ['Evan Lu', 'Zoraiz Qureshi', 'Marco Kurepa', 'Rayton Chen'] | [] | ['css', 'django', 'firebase', 'html5', 'pyrebase', 'python'] | 9 |
10,277 | https://devpost.com/software/horizon-realty | Logo
Inspiration
Horizon Realty was inspired by the lack of experience people were getting by Airbnb and they are ruining people's privacy and vacation. They also tax up to $200 of fees on top of the original monthly bill paid off the rental property and offers no room for dispute over the pricing of the rent itself. That's where we decided to create an app that requires no cost whatsoever and when renting out a property it gives you the direct cost of the rent in ethereum currency. This where Horizon Realty steps in and makes things easier for the user and the landlord. We decentralize this service with trustless smart contracts and eliminating the middleman and the fees that come along with them.
What it does
Horizon Realty allows users to create rent and rent out places like Airbnb, but quite simply, in the most efficient way possible. Horizon Realty is a decentralized application, that utilizes trustless smart contracts in order to act as the intermediary for Renting. Because of this, we can provide costs for Rents that have virtually a $0 middleman fee. This is revolutionary in the sense that we can sort out disputes and move legal liability away from the Gig Workers, into trustless contracts.
How we built it
We built this decentralized application with Web3, the Ethereum Ecosystem, ReactJS, and Material UI. We used the Web3, to store our user data such that it’s decentralized and it will prevent any external sources from accessing the user’s private information. We also utilized the Ethereum Ecosystem to securely store the smart contracts that we wrote to monitor each user. The Ethereum Ecosystem was necessary for our application to fully flower as it was needed in our proof of thought for our project. We utilized ReactJS to develop our frontend for this application, by creating multiple pages for the user and also develop multiple components. We fetched data that will allow the users to easily type and click the auto-filled address, as well as the calendar when selecting their start and end date for their renting period. We also used the Material UI Library in React to style our components and properly make our application UI and UX friendly.
Challenges we ran into
One of the most challenging things that we had to do was bug fix the incredibly complicated Smart Contract backend. Node and Solidity EVM errors were extremely vague and thus difficult to bugfix. There were so many components and processes going on that we had to really focus on to make sure it all worked together. Many things with the front-end were not showing up, forcing us to reinstall Node Modules, as well as React itself.
Accomplishments that we're proud of
We are really proud of developing a fully functional Decentralized Application by only being introduced to the Ethereum Ecosystem and the Web3 Protocol shortly. Our desire for the entire application was to style it off come on renting platforms but implement it with the ever-growing popularity of blockchain. This was a lot of work for a team of 2 to finish in less than 36 hours. Evan and I are very proud of our final solution and we would’ve never seen this application to fully function.
What we learned
We had to integrate the Blockchain network with Web3 which required several hours of debugging. Solidity was hard to learn for Evan for the first time, as well as integrating Material-UI for the front-end of the app. Vlad utilized React and Material-UI for the very first time. Both of the members of our group had learned and applied new different frameworks and languages for this project while doing our absolute best. We tried our best and accomplished many things along the way when using new languages and created a fully-functional app. We stuck together throughout the entire 36 hours and never gave up the second we started.
What's next for Horizon Realty
The application that we built with blockchain technology performs some functionality, but since we couldn’t launch and deploy it to the main network (which would cost some of our own money), it would be the next main thing for Horizon Realty. We would’ve also loved to add a history feature for our users, so they can review their previous transactions and possible refund them. Allowing some possible way for our users to interact with us so we can provide them with a refund just in case they change their minds.
Built With
blockchain
css
etherium
javascript
material-ui
metamask
photoshop
react
rechart
solidity
truffle
Try it out
github.com | Horizon Realty | Making Renting Easier and Anonymous! | ['Evan Wang', 'Vlad Comsa'] | [] | ['blockchain', 'css', 'etherium', 'javascript', 'material-ui', 'metamask', 'photoshop', 'react', 'rechart', 'solidity', 'truffle'] | 10 |
10,277 | https://devpost.com/software/atlashacks | Inspiration
Our inspiration consisted of our own concern and willingness to help combat the COVID situation, and compounded with the fact that the theme of Atlas Hacks was conducive toward this more general mission of building something that benefits society, the idea came naturally.
How I built it
We used the Figma and Sketch framing and design software to prototype and initially design the app, and we alternated roles in several pair programming sessions to implement the code in XCode.
Challenges I ran into
Navigating remote collaboration in the context of the medium of participation in the hackathon being online. Like for many other people as well, this was our online hackathon. We believe that there is just something about in-person experiences and collaboration that can't be matched at the same caliber, but we were still able to figure out how to collaborate together optimally through online communication.
Accomplishments that I'm proud of
Utilizing the time we agreed upon for collaborative pair programming sessions effectively.
What I learned
We learned to better incorporate numerous technologies into a seamless user interface.
What's next for Snapdemic
To expand upon this application, we plan to pursue additional functionalities such as fully integrating the Stripe Payment Method to process online payments and place orders. We also plan to incorporate a chat messaging feature to contact local hospitals and stores nearby.
Built With
swift
Try it out
github.com | Snapdemic | A general service iOS app tailored to providing first-aid medical supplies and donating funds to front-line workers, that leverages machine learning in image classification and recommendation systems. | ['Bill Xiang', 'Aditya Sharma'] | [] | ['swift'] | 11 |
10,277 | https://devpost.com/software/helply-g7kory | Helply Logo
Item Identification and Processing System
User Donation Profile
Leaderboard for Gamification and Incentivization
User Landing Page with Google Maps Integration
Item Identification Subsystem
Distribution Subsystem with Google Maps Integration
Team
Team Name: Helply
Discord: rsrajan#8591
Inspiration
In 2019, the total generation of solid municipal waste was 267.8 million tons, or approximately 4.51 pounds per person, per day. Of this amount, only a mere 23% was recycled. Additionally, in 2020, over 15%, or 40 million Americans, are affected by poverty nationwide. In the 21st century, with growing wastage and increasing poverty, Helply simplifies the donation and recycling experience for everybody.
What it does
Helply allows users to pinpoint optimal donation and recycling centers, ship, and recycle their old household items, and receive reward points in return for helping their communities while reducing their waste production -- all within the comforts of home.
How I built it
The app’s skeleton was built around Ionic, an Angular.js framework built on top of the Apache Cordova platform. Through Ionic, Helply has been optimized for both iOS and Android devices.
The detection of the item being donated or recycled was built on Google's Cloud AutoML platform. The AutoML backend has been extensively trained to identify the object itself, the state, and the condition of the item in the picture instantly.
The distribution subsystem was built on top of the AutoML backend and uses the weights from AutoML and the user's geolocation to find optimal donation and recycling centers, as well as populating the shipping labels.
Challenges I ran into
Due to the vastness and subjectivity within the identification of the object and the condition, it was difficult to create a catch-all AutoML model that could identify every object being inputted. Another tedious aspect of the development process was getting the numerous APIs and libraries all working together.
Accomplishments that I'm proud of
I'm proud of having a diverse set of subsystems, APIs, and libraries all working in conjunction while maintaining a streamlined and clean front end and user experience.
What I learned
I learned how to: create an Ionic/Angular.js frontend, maintain a responsive and clean UI navigation, create an AutoML model, and integrate different languages, all while supporting various frontends/backends to make a cohesive application.
What's next for Helply
Look into future possibilities of adding features like using gamified reward points to purchase products from companies sponsoring Helply and promoting community outreach.
Built With
angular.js
apache
css3
google-cloud
html5
ionic
javascript
node.js
Try it out
github.com | Helply | An awesome way to donate and recycle | ['Rohit Rajan'] | ['Track Winner: Work and Productivity'] | ['angular.js', 'apache', 'css3', 'google-cloud', 'html5', 'ionic', 'javascript', 'node.js'] | 12 |
10,277 | https://devpost.com/software/voluntero-4g0xvi | Made by
@seancabahug
,
@TechnoDrive
,
@priyanshudasgupta8
, and
@VaaniBhagvath
in 36 hours for the AtlasHacks 2020 Hackathon.
Built With
css
express.js
html
javascript
mongodb
react
Try it out
github.com | Voluntero | A platform for users to find and host volunteering events. | ['Sean Cabahug', 'Hextanium Franklin', 'Vaani Bhagvath'] | [] | ['css', 'express.js', 'html', 'javascript', 'mongodb', 'react'] | 13 |
10,277 | https://devpost.com/software/maskdetech | About
A web application that is geared towards detecting if users are wearing the proper protective coverings or not during the pandemic.
Built With
flask
python
Try it out
github.com | MaskDetech | A web application that is geared towards detecting if users are wearing the proper protective coverings or not during the pandemic. | ['Jeremy Nguyen', 'Nand Vinchhi'] | [] | ['flask', 'python'] | 14 |
10,277 | https://devpost.com/software/no-touch-disinfectant-wipes-dispenser-0qclb3 | Prototype of the project
Code for the arduino
Circuit
Inside the future look
Future look with more materials
Layout for PCB in the future
The problem
Hey, I am Tanya Rustogi and I got the idea of the wipes dispenser when I was thinking of how Covid-19 is affecting developing countries. My first thought was that to open a wipes container like lysol you need to touch at least two surfaces which can spread coronavirus. Additionally, having a container of wipes per person in an office or school is not realistic due to the shortage of disinfecting wipes. Then came the idea of an affordable, easy disinfecting wipes dispenser that can be used for classrooms to day cares to shopping carts everywhere.
The solution
So what this dispenser does is when an object such as your hand comes within ten centimeters of the sensor, the motor starts moving which is connected to a rod with rolled up wipes on it. The rotation of the motor moves the roll of wipes, causing them to unroll and make their may out of the container.
How to build
So, each of the pins except the ground and vcc on the motor driver are connected to pins on the arduino, which we defined in the code. The trigger and echo pin on the sensor are also connected to the arduino which are defined in the code. Then the ground and vcc of both the motor and the sensor are connected to the ground and vcc of the arduino which is connected to the power. The sensor detects the distance by seeing how long it takes a wave to come back. The code on the arduino makes sure that if the sensor detects something within 10 centimeters of it, it runs the function stepper which causes the motor to run. The container is made from the lysol container, hopefully making it cheaper for developing countries. The container has two holes, one for the wipes to come out from and one for the motor. Then we need to connect the motor to the container which I achieved with tape. The rod connects to the motor which is held on the other side through the hole already provided in the lysol container. Now when the motor rotates, the rod rotates as well.
What’s next
This is just a prototype, with more material, the final product would look cleaner with a box covering the circuits and the pcbs and circuits connected to the container.
What did I learn
I think the most important thing I learned through this experience is time-management due to the time constraints of two days to make the whole thing as well as perseverance to be able to try again despite how many times the circuit and the code did not work as it was supposed to.
Built With
arduinoide
arduinouno
python
steppermotor
ultrasonicsensor
Try it out
github.com | No-Touch Disinfectant Wipes Dispenser | A prototype of a no-touch dispenser that is easy and affordable to make and could be used from cleaning tables to disinfecting carts. | [] | [] | ['arduinoide', 'arduinouno', 'python', 'steppermotor', 'ultrasonicsensor'] | 15 |
10,277 | https://devpost.com/software/rationghar | Homepage
Registration Form
Submitted Requests View for people
Login Page
NGO Sign Up form
NGO Dashboard
Change Password Form for a NGO account
All Submitted Requests View for NGO's
Inspiration
Pakistan one of the most deadly affected countries with COVID'19, having almost have of it's a population living under the poverty line. However, Pakistan is one of the most philanthropist nation as well, in which the Development sector is working with Non-Government Organizations to uplift the poor.
In addition, the Ration distribution usually works in way where NGO's go to a public place and ask the people to gather in large groups to receive their ration bags. Given the COVID'19 situation, everyone is
strictly advised not gather in public and in large groups to limit the spread of the virus
, so we tend to tackle this problem. We are aiming to let the people stay at home, prevent attending large gatherings, and at the same time
receive their ration packages at their doorsteps
. This way
quarantined and disable
people can easily register for ration bags and get save themselves from a potential virus infection.
Like all the world, Pakistan is also in Lock down but here already malnutrition people are not even getting basic food items. In addition, to this, there are many people who are underprivileged and have physical disabilities, which restrain them from working and earning for themselves.
What it does
RationGhar is a platform which is linking Non-Government organizations to underprivileged people and people with physical disabilities. It allows people to ask NGO's for ration with the comfort of their home. The people do not necessarily need to own a laptop, all they need is a mobile device with internet connection, to make a submission. A person can, then, fill in a form and make request for NGO to review. The NGOs' can view the submission and assign it to themselves. Once assigned, the form will be available in the Assigned List of the NGO. From this list, the NGO can change the status of the form between "In Progress" and "Fulfilled". People can track their form by tracing their CNIC.
How we built it
We built it using React, Firebase, Material-UI, CSS, HTML.
We also deployed the app on
heroku
.
deployed app link
Challenges we ran into
We learned Firebase from scratch and implemented an idea that initially seemed difficult.
In addition to this, we faced internet connectivity issues at some points, which made the collaborative work a bit difficult. However, we tried to come up against all the odds to complete the project.
Accomplishments that we're proud of
We are proud that RationGhar will someday serve the community for both the people in Pakistan and other countries too.
What we learned
We learned a lot of new skills. Some of these include time management, collaborative working and competitive website development. In addition to this, we learned how to come up with a fully functional web app in just 36 hours.
What's next for RationGhar
We will try to launch it in our local community and try to expand it in the country. In addition to this, we intend to make it more feasible for all types of people and improve the UI even further. We are also planning to make this platform, more user friendly and add another feature of
NGO Portfolio
. This additional feature will help the NGO's to showcase their work and dedication to potential sponsors, who can in return provide the deserving NGO's with funds to extend their community service tasks.
Built With
css
firebase
heroku
html5
javascript
material-ui
react
Try it out
github.com
ration-ghar.herokuapp.com | RationGhar | RationGhar is a ration distribution platform to connect NGO's and community service organizations with underprivileged and people with any sort of physical disability in the time of COVID'19. | ['Farrukh Rasool', 'Hamza Farooq'] | [] | ['css', 'firebase', 'heroku', 'html5', 'javascript', 'material-ui', 'react'] | 16 |
10,277 | https://devpost.com/software/lectureline | App (login page)
App (record a lecture)
App (condense into notes)
App (home page-store/organize notes)
Here
is the link to our business plan,
here
are our slides,
here
is the code demo video, and
here
is our Framer prototype!
Inspiration
As fellow students, we have firsthand experience with the struggles of trying to keep up with fast-paced lectures. Students are trying to take detailed notes that they can use to study and review while also trying to pay attention to the lecture and understand the key concepts. It is difficult to get down all of the information with this kind of stress, and students often return from lectures with incomplete notes that they are not able to understand because they were not able to learn much during their time in the lecture. We realized that the best way to learn efficiently is to pay attention to what the lecturer is saying and observe the visuals during the lecture so that when you leave the lecture, you are able to further review and study on your own with some basic understanding of the concepts. However, this isn’t ideal because you leave the lecture without any notes. We tried taking audio recordings of the lecture so that we could refer to it later, but that was time-consuming as we would have to listen to the entire lecture again in order to review. This inspired us to create LectureLine, so that students are able to learn as efficiently as possible by paying attention during lectures and reviewing information with the LectureLine notes.
It’s not just us! Students across the globe struggle with note-taking and the lack of absorption in fast-paced lectures. A recent study demonstrated that 72% of students have difficulty in taking adequate notes and can’t record information fast enough. After conducting a survey of 96 individuals this weekend, we discovered that 83.3% had a heavy increase in self-learning due to COVID-19, 90.6% felt rushed in lectures, and an overwhelming 92.7% said that they would love to see an application that creates notes in real-time and adds resources.
What it does
LectureLine is a clean and efficient mobile application that revolutionizes the process of notetaking with real-time transcription and summarization with links and visuals. Features of LectureLine include fluid note-to-note linking, real-time transcription, compatibility across all devices, notes storage and organization, and offline capabilities.
The application utilizes the process of real-time transcription, but also contains the feature of summarizing the information into bullet points that capture key points and concepts, which none of its competitors include. This is vital in crafting efficient and easy-to-study notes that are more helpful for students in high-stress situations. The application goes far beyond the simple transcription and summary. Along with this recording and transcribing process, the application detects and categorizes key terms and concepts in order to generate images and visuals that may help the student. Along with visuals as a resource, the application will also take these key concepts and display helpful links and resources in order to allow the student to delve deeper and explore the concept further.
How we built it
Using Framer, we developed a virtual prototype that demonstrates the UI/UX aspect of LectureLine. This includes a clear process of how the mobile application works, and what the desired interface of LectureLine looks like. Along with simply demonstrating the interface of note-taking, our virtual prototype shows a clear demonstration of how an individual can create an account, organize and store their notes, and change their type of subscription. Small and desired features that we hope to implement in the future are also included to display the full workings of LectureLine.
Additionally, we created a code demo as a proof of concept for LectureLine. This program, written in Python, utilizes the user’s device’s microphone to listen for information and then transcribes it into written notes. The program then identifies the key concepts of what the speaker is saying through natural language processing and includes links and images into the notes. Then, the user can save their notes onto their own device.
Challenges we ran into
Due to the time pressure of this project, we were not able to include all desired aspects of LectureLine into our prototype. Although our code demo demonstrates the basic workings of our product, we hope to fully implement these desired features in the future with more time. One of the biggest challenges we faced was incorporating the use of punctuation into our transcribed notes. It became difficult to analyze verbal diction in order to process punctuation and capitalization. To overcome this challenge, we utilized source code for punctuation and were able to adapt it into our situation and program.
Additionally, we were hoping to incorporate more features into our prototypes such as offline capabilities, note-to-note linking, and textbook recommendations. With more time, we hope to incorporate these features, as well as machine learning so that the app would, over time, be able to recognize a voice and adapt to the accent and speaking style in order to make more accurate notes. We also plan on using machine learning and natural language processing so that LectureLine can identify the subject of a lecture and take more precise and helpful notes based on the subject (for example: in science subjects, LectureLine would include more labeled diagrams).
Accomplishments that we're proud of
Although we had little experience in Python and natural language processing as a team, we were able to work together in order to understand these concepts. We are extremely proud of our working project and the new concepts we were able to learn. In order to incorporate these new concepts, we conducted a lot of research and went through a lot of trial and error.
Additionally, this was our first time using Framer to prototype our mobile application, and we feel accomplished with the professionalism and efficiency of our given model. Although we felt pressured under time, we are super excited to showcase our working prototype and code demo!
Another thing that we are proud of is our business plan and slides. We did our best to create professional and clean materials that showcase our company, product ideas, and strategies.
What we learned
During this process, we were able to learn a lot about emerging technologies such as natural language processing in Python and how they can be implemented into a situation as basic as note-taking. We also conducted research on efficient learning and note-taking strategies in order to maximize the potential of our product, so we were able to learn about how we can improve our own habits and hopefully help others as well!
We experimented and learned the use of UI/UX design as well as the importance of market analysis, which allowed us to better improve LectureLine in comparison to our competitors. Most importantly, we learned the importance of time management and efficiency, which allowed us to successfully complete this project!
What's next for LectureLine
LectureLine is a mobile application as of now, but we plan to expand to browser extensions and other technologies in order to increase compatibility. This provides the user with much more accessibility, as they can use any device to access its features. We hope to partner with educational institutions, such as schools and universities, in order to reach a larger portion of our main target consumers, students. The team will run various marketing strategies and promotions on numerous websites and university platforms in order to promote the use of this time-efficient and user-friendly product.
LectureLine also has the potential to benefit working professionals, and we plan to maximize that potential through an additional work industry version. This version of LectureLine would have features that are specific to taking notes for meetings and informational sessions. For example, LectureLine would take notes during a meeting and automatically send those notes to meeting participants in order to ensure that everyone is on the same page and that there is no confusion. Through further development, LectureLine would be able to create timelines and assign tasks to individuals based on meeting notes.
Further down the road, the LectureLine team hopes to provide new developments and features in order to increase the productivity and efficiency of our application. For further development of LectureLine, technologies such as natural language processing and machine learning will further be implemented to maximize the functions of LectureLine. This includes textbook recommendations, access to multiple languages, and browser compatibility. Additional features will be added as well, such as saving and condensing the lecture audio by increasing the speed and reducing the time when the lecturer is not speaking so that users may listen to it efficiently.
Built With
framer
natural-language-processing
python
pyttsx3
speech-recognition
Try it out
github.com | LectureLine | Revolutionize note-taking: every line counts. | ['Sasha Mittal'] | ['Best Beginner Hack'] | ['framer', 'natural-language-processing', 'python', 'pyttsx3', 'speech-recognition'] | 17 |
10,277 | https://devpost.com/software/simplitize | Home Page
UI of the Summarizer Form
UI of the Question Answering Form
You can see the POST requests sent to our API here
Page shown after user submits
Our model got the right answer!!!
Inspiration
As students interested in Data Science and Machine Learning, we've found that a great way to stay up to date with this rapidly changing field is to read academic papers recently published. However, many of these papers were extremely long and tough to comprehend, and the abstract of a paper was often missing, and if it was present it wasn't informative. Furthermore, we often spend a lot of time going through papers that were similar to something we read before, but we didn't know that beforehand due to the sheer length of the paper. Also, we often were looking for an answer to a specific question, but we didn't know where to look for an answer, as the answer was often buried in 80 pages of technical terminology. To solve this, we developed Simplitize, a web app that helps you understand academic papers via NLP Question Answering and Document Summarization.
What it does
There are two features of Simplitize. First, the user can copy and paste a paper into our webpage, and we'll summarize it in
under 10 sentences
. Second, the user can copy and paste a paper into our software along with a question about the paper, and we'll provide them the answer to their question (or "None" if the paper does not contain the answer). I'll go more into how this works below.
How We built it
We built the frontend with HTML, CSS, and JavaScript and used the Mobirise builder to beautify it. Our backend is written in python with the flask framework. We also used Pytorch and BERT for question answering and NLTK for document summarization.
Document Summarization
There are two types of document summarization, abstractive summarization, and extractive summarization. Abstractive summarization is where we try to provide a summary by focusing on the big picture, but keep most of the main sentences intact. Extractive summarization is when we break down most of the sentences to summarize the document, however, there are often many grammatical errors and it is tough to understand. We chose to use abstractive summarization as the purpose of our project was to make these papers easier to understand. We used Natural Language Processing to give each sentence a "rating" to how essential it was to the "big idea" of the paper, and then ranked the sentences. We then presented the user with the most important sentences in their paper constructed into a holistic summary.
Question Answering
We wanted to go beyond the typical hackathon project of an article summarizer, so we integrated an extremely new deep learning algorithm to provide question answering: a transformer. A transformer is an algorithm used for seq2seq modeling, and we wanted to train a model that could extract information from text. We then found the Stanford QUestion Answering Dataset (
SQuAD
), and planned on training a transformer on SQuAD. However, training a model from scratch on SQuAD would take four days to train, and we had only had 20 hours to go. To solve this, we applied
transfer learning
and used a pre-trained transformer and performed hyperparameter tuning locally, which took ~4 hours. We then saved our model and integrated it with our flask API to connect it to the frontend.
Challenges We ran into
There were two major challenges we ran into (in addition to a gazillion bugs):
As stated earlier, we ran into time constraints, preventing us from training a transformer on SQuAD from scratch. However, we solved this through transfer learning. We learned that transfer learning is used very commonly in the field of Natural Language Processing.
We had issues connecting our Flask API with Heroku, which is where I normally deploy flask APIs which I've written. Unfortunately, I didn't have time to debug this issue, so I ran the API on localhost and used ngrok tunneling to get an endpoint URL. When we put this into production, we plan on deploying it on either Heroku or PythonAnywhere as those are more scalable.
Accomplishments that We're proud of
We have a fully functional web application that can be deployed, which can help many students get a better understanding of deep learning.
At the point of publishing this project, I believe we are the only software that provides high-quality question answering specifically for academic papers; our project is novel and hasn't been repeated!!
We learned about how we can apply transfer learning to natural language processing, something that neither of us had much experience with. This is applicable in the future, as most NLP algorithms are built via transfer learning.
What We learned
We learned how to apply transfer learning to Natural Language Processing, which neither of us had done before. We plan on continuing to use transfer learning when working on other projects.
We learned a lot about the applications of question answering, which is a relatively new field in NLP. We hope to apply this to other fields in the future.
What's next for Simplitize
We plan on hosting our API on PythonAnywhere, as it is clearly more scalable than running it on a local server. After that, we hope to deploy our website on simplitize.tech (in process of buying domain right now). We hope to get feedback on our project, and then reiterate.
Built With
bert
css3
flask
html5
javascript
nltk
python
pytorch
Try it out
github.com | Simplitize | Helping you understand complex academic papers via NLP Question Answering and Document Summarization | ['Kshitij Rao'] | [] | ['bert', 'css3', 'flask', 'html5', 'javascript', 'nltk', 'python', 'pytorch'] | 18 |
10,277 | https://devpost.com/software/covid-relief-journal | Journal Page
Quotes/COVID
Journal/News
Inspiration
For AtlasHacks, we created a mobile application dedicated toward providing relief for people fearful of COVID-19. Recently, the global pandemic has been sparking panic and fear across the world, and many people have been living in a terrified state for months. Thus, we wanted to create an app that would help alleviate the user’s mood to make them feel better about the upcoming months regarding COVID-19.
What it does
The application includes a positive news section, a journal entry section, a positive quotes section, and a live tracker of COVID-19 case recoveries. In the positive news section, the app is continuously updated to show the latest news articles. We specifically chose to show only positive news because this would help brighten the user’s mood, as every day they can learn about the good things that are happening in the world rather than of the devastating impacts of COVID-19. In the journal entry section, the user can submit a few sentences about their day for future records. This will allow them to record their thoughts and emotions, which is a scientifically-proven beneficial and therapeutic activity. The positive quotes section generates a positive quote every time the user clicks the refresh button. There are tens of thousands of positive quotes that our app can generate, which will ensure a lack of redundancy, boosting the user’s experience with the application. Finally, the live tracker of COVID-19 case recoveries will allow the user to feel better about COVID-19 as they will see only the positive aspect of the pandemic.
How we built it
We created this application on Flutter. Design-wise, we decided to create a light-themed app. We chose color schemes that are warm and appealing in order to evoke greater relief from the user. We connected to a quotes database, a positive news api, and the NovelCOVID api features on postman. We presented our app with many animations to create a pleasing experience. We made sure to target the app toward positivity by only displaying POSITIVE news, and for the COVID tracker, only displaying RECOVERED cases rather than deaths or total cases. Overall, the experience was challenging; however, we believe we produced a great app that provides a sense of relief.
Challenges we ran into
A challenging component of our app development process was implementing and writing in the api's to our app. Additionally, we had issues with connectivity of app among multiple devices when editing. To fix these issues, we used GitHub where our members could commit their changes and pull updates made during development.
Accomplishments that we're proud of
Having been our first hackathon, we are proud to have successfully finished an entire app within the restricted time. Through our efforts we were able to gain a greater and more in-depth knowledge of app development by implementing api's, using toolkits like Flutter, and learning from our challenges throughout our development.
What we learned
Overall, the process of creating this project was difficult, but fun. Time-consuming, but also enlightening, as we learned a lot about app development while creating our mobile application.This new understanding we gained taught us the foundations and components that go into app development, allowing us to take these skills further past just this hackathon. With our design and code, we not only hope that our application is impressive to you, the judges, but we also plan to actually publish this application in the future after further refining so that people afraid of COVID-19 will be able to find relief in tough times.
What's next for COVID Relief Journal
In the future, we hope to publish our application after further refinements within our app. We hope that through its publication, we can reach a larger audience in which we can provide relief for those afraid of COVID-19 during these tough times.
Built With
dart
good-news-api
html
kotlin
novelcovid-api
objective-c
quotes-free-api
swift | COVID Relief Journal | COVID-19 has been sparking panic and fear across the world for months. We wanted to create an app that would help alleviate the user’s mood so that they feel better about the upcoming months. | ['Philip Vu', 'Kathie Huang', 'Madhavi Vivek'] | [] | ['dart', 'good-news-api', 'html', 'kotlin', 'novelcovid-api', 'objective-c', 'quotes-free-api', 'swift'] | 19 |
10,277 | https://devpost.com/software/stance-taking-a-stand-against-hate-speech | Title
Data Visualizations
Tools Used
Main Chart
Inspiration
In todays hectic online landscape, toxicity and harassment can stop people from expressing themselves. I want people to be able to have conversations online, without feeling like they are being harassed.
What it does
This application takes in comments that the user wants to categorize. It can tell the user how likely it is that the comment falls under certain categories that are toxic.
How I built it
I built the machine learning model using sklearn, a python library. For the front end, I used flask to create a web interface to interact with the model. The visualizations were created using LIME (
https://arxiv.org/abs/1602.04938
).
Challenges I ran into
There were issues with the front end, especially with displaying the data visualizations. I was not able to get all the visualization to display on 1 page and resorted to using separate pages. There was also some difficulty with sklearn, but this was solved fairly easily due to the large online community on stack overflow and etc.
Accomplishments that I'm proud of
Getting the machine learning portion to work was something I am quite proud about. I am also very happy with how my front end turned out, particularly with how my data is shown.
What I learned
I am very new to machine learning, so I am very happy that I know how to use sklearn for machine learning , as well as using flask to interface with my back end.
What's next for Stance: Taking a Stand against Hate Speech
The next step would be to port it into an app. Another possibility would be to have it as a browser extension, or even a moderating tool that online forums can use to curb hate speech.
I also definitely want to try other more complex machine learning algorithms to improve the performance.
Built With
flask
html5
javascript
lime
pandas
python
sklearn
Try it out
drive.google.com | Stance: Taking a Stand against Hate Speech | In todays hectic online landscape, toxicity and harassment can stop people from expressing themselves. Stance is my solution. | ['Michael Li'] | ['Best Data Visualization'] | ['flask', 'html5', 'javascript', 'lime', 'pandas', 'python', 'sklearn'] | 20 |
10,277 | https://devpost.com/software/rebel | Benefits
Inspiration
Twitter Output
Inspiration
Due to the ongoing pandemic, everyone is working remotely!
This puts immense pressure on Internet services and often leads to slow internet connection bandwidths. The pandemic has given us enough trouble already where in slow internet just makes it worse :- halted work zoom calls, repetitively cut and unclear voices, connection dropping just at the time of payments or exactly when you're about to submit a project for a hackathon. To top that, getting in touch with your internet service provider to complain and actually getting your problem resolved is next to impossible, taking up another half of your day.
What it does
'Rebel'
, a python based program, which checks your internet speed every 2 hours and if the current speed (inclusive of both download and upload speeds) is less than 80% of what the user is actually paying for to the internet service provider: The program tweets and tags the service's twitter handle, notifying them of the actual current speed and expected speed, all on its own. The user only inputs the expected speed one time; rest is taken care of by the program. Thus the program removes the hassle of contacting your internet service provider every time you use the internet, keeps the company in check, makes working remotely more efficient and saves half your day!
Challenges we ran into
-The most troublesome challenge was building and communicating via skype with slow internet speed, lagging videos and muffled voices motivated us further to make this program.
-Secondly, running a certain part of code without asking for input from the user required us to use a python library we weren't familiar with. (Advanced Python Scheduler)
-The url for the speedtest image was generated only when we ran the speedtest code on the command line interface. Thus we needed a way to collect the output generated by the command line in Python.
-Initial script of the main code was written in a linux based computer so some parts were coded in bash. To integrate those ideas into the project and make the whole code pythonic was challenging.
-One person in the team was new to python so others got the opportunity to mentor him and that was challenging for the person to digest such information in a small amount of time.
Built With
api
apscheduler
linux
os
python
speedtest
tweepy
twitter
urllib.request
Try it out
github.com | Rebel | Your unconventional internet care-taker | ['Charu Tyagi', 'Kushagra Goel', 'Ajeya Madhava Rao Vijayakumar'] | [] | ['api', 'apscheduler', 'linux', 'os', 'python', 'speedtest', 'tweepy', 'twitter', 'urllib.request'] | 21 |
10,277 | https://devpost.com/software/ezpcd | Inspiration
What it does
EzPCD is an introduction to electronics and printed circuit design.
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for EzPCD
Try it out
bitbucket.org | EzPCD | EzPCD is an introduction to electronics and printed circuit design. | ['Warp Smith'] | [] | [] | 22 |
10,277 | https://devpost.com/software/linked-help-public | Our project name!
Check out all the events posted!
Create your own event!
View events in detail!
Inspiration
This project was inspired from our desire to make a more organized way to create and host volunteer events for the betterment of society.
What it does
Our application allows users to register a account from which they can view events made by other users or create their own for others to join. In these events, other people will be able to see the event details directing them to the location of the event if they so choose to participate.
How we built it
Our application was created with Vue.js for the frontend and Firebase for the database. Firebase was much quicker to create and saved us a great deal of time. Vue.js was used because one of our group members was proficient in it.
Challenges we ran into
We had one extra member on our team, who left unexpectedly which ruined our pacing (The person was going to make a backend). We had to improvise, and decided on Firebase for it's simplicity and how quick it is to implement. In addition, one of us did not know how some program some things, which further decrease the amount of time we had left.
Accomplishments that we're proud of
This application was our first project together and we managed to create a fully functional web application which we consider remarkable. We believe this program will truly benefit the world.
What we learned
This project taught us how to plan out our project in the most efficient way possible. In addition, it taught us to improvise in order to overcome any hurdle. We also learned more about the usage of Vue and Firebase. In addition, we were also able to boost our understanding of GitHub.
What's next for Linked Help
We plan to add more features such as a forum where people can create posts there to talk and discuss, and implement a google maps in order to have a more accurate location. We also plan on allowing text to be decorate with bold, underline, italic, etc.
Built With
css3
firebase
html
javascript
vue
Try it out
github.com
nastalgua.github.io | Linked Help | Meet up with others who also want to change the world | ['Matthew Chen'] | [] | ['css3', 'firebase', 'html', 'javascript', 'vue'] | 23 |
10,277 | https://devpost.com/software/test-together-yjzsuf | Inspiration
After Covid-19 lockdown restrictions have loosened up in some states in the US, I realized how more people might need knowledge of where testing sites were
What it does
How I built it
I used Figma to design the UI and exported it over to Android Studio XML files. Then I tried to figure out a COVID-19 Testing Center API and implemented it into my app.
Challenges I ran into
This was my first time focusing on UI and working with Figma and also the first app I've made in Android in about a few years, so it was a bit difficult to relearn the interface and the code.
Accomplishments that I'm proud of
I'm very proud that I was able to learn a new way to design applications and also for making a semi-functional android app. I also typically make web applications with APIs, so this was a fun new challenge.
What I learned
I learned how to work with Figma and also learned how to implement an API in Android and making JSON calls in the Android Java language.
What's next for Test Together
Implementing Google Firebase Authentication and allowing users to save certain test centers. Also working on creating a map for users to visualize the location in relation to themselves.
Built With
android-studio
api
figma
json
Try it out
github.com | Test Together | An android app seeking to inform the public about COVID-19 testing sites in their state | ['Fay Lin'] | [] | ['android-studio', 'api', 'figma', 'json'] | 24 |
10,277 | https://devpost.com/software/covid-19-help-space-rhsjko | Inspiration
During this time, we realized that even though there are so many resources online, the millions of options to choose from for useful information can get overwhelming super quickly. That's when we realized we wanted to make life, which is already very challenging for most people, a lot simpler by providing them with a central tool that will lead them to useful and reliable resources quickly and easily. We thought that this was especially important to have for people searching for help within self-care, food, news, jobs, and education
What it does
Our website allows people to find useful resources quickly and go straight to doing what they need to do without the stress of looking through all the options that pop up after one Google search. We have included five sections of information: Self-Care, Get Food, News, Job Support, and Education. Each page features a list of sources that are visible as icons until the user hovers over them to find more information about the resource. The user then has the option to click on the resource and get directed right to the site. In addition to the resource lists, we included a data visualization of confirmed COVID-19 cases by county (data from USA Facts) in the 'News' section and a spreadsheet of job listings in the 'Job Support' section.
How we built it
We built our website using
HTML
,
CSS
, and
Javascript
. We used Glitch to run our code. For the data visualization, we gathered the data from USAFacts and used Domo to make the visualization of confirmed COVID-19 cases in the United States by county. For the spreadsheet of job listings, we used
UIPath Studio X's Data Extraction
tool and created an automated tool that collected the title, description, and URL of the listing of job websites, so that we could create a spreadsheet that had job listings from different pages/websites all on one page.
Challenges we ran into
We ran into some challenged with the CSS format, but we were able to overcome them by referring to online resources and playing around with our code to see which parts were conflicting with others. Another challenge was that UI Path only saves to an Excel sheet and we do not have Excel, but we were able to remedy that by copy and pasting the preview of the data extraction onto an AirTable, which in the end made it easy to embed the data into our website.
Accomplishments that we're proud of
We are proud of the fact that we made a website with multiple pages and ways that the user can interact with, not just a static webpage. This is our second-week coding and we were really happy with how the layout turned out. To be honest, we were a little bit intimidated by the thought of using
UI Path
and
automation
, but we were able to actually use the product! Something else that intimidated us was the thought of creating a data visualization because they look so complex, but we were really happy with our data visualization of confirmed COVID-19 cases by county.
What we learned
We learned a lot more about using
CSS
to style web pages. We also learned how to use
UI Path
to automate data extraction from web pages. This was a super cool experience because initially, we did not know that
UI Path
could do something like that, and we were going to manually compile everything onto a spreadsheet. We saved so much time and we would definitely use
UIPath
again for that purpose. We also want to explore what other ways we can utilize automation to save us time. Lastly, we learned how to create data visualizations. It was amazing as well since the data from USAFacts is a massive repository and we were able to make a detailed and informative visualization of the whole country!
What's next for COVID-19 Help Space
We think that making everyone's life easier is always a plus, especially during this time, so we would love to keep adding more resources for everyone to use, as well as use our code to publish a real website. Also pivoting the site to host an online community where people could support each other during these challenges times would be something we are very interested in.
Built With
css
domo
glitch
html
javascript
uipath
Try it out
covid-19-help-space.glitch.me | COVID-19 Help Space | A easy to use platform with resources to help navigate life during the COVID-19 pandemic. | ['Genevieve Chin', 'Roselyn Chin'] | [] | ['css', 'domo', 'glitch', 'html', 'javascript', 'uipath'] | 25 |
10,277 | https://devpost.com/software/interstellar-hpiyzj | Inspiration
Manned space programs from around the world have led to hundreds of spin-off inventions used to improve our everyday lives. Science education is absolutely vital to continuing this progress. Unfortunately, COVID-19 and the lockdowns used to combat it have closed science centers, museums, and schools all over the world, depriving millions of children of valuable (and potentially life-changing) educational experiences.
That’s why I built InterstellAR. I wanted to encourage today’s students to grow into the scientists of tomorrow. I wanted to show them the majesty and grandeur of the cosmos in a way they can’t get from books and ordinary videos. So I created InterstellAR to fuel students’ imaginations by bringing astronomy to life with augmented reality!
What it does
InterstellAR provides users of all ages with an interactive way to learn more about space from the comfort and safety of their own homes. By combining pictures, text, and 3D models, InterstellAR lets users experience a unique learning experience that can’t be recreated with traditional media like articles, books, and videos.
How I built it
I wanted to make sure that anyone could access InterstellAR without needing to acquire specialized hardware or software, so I decided to make InterstellAR as a web app. Also, I figured that most of InterstellAR’s users would be on phones or other mobile devices, so I decided to make my website using React and Material UI because they already have many responsive features built in. I also used EchoAR to store and deliver the 3D models.
Challenges I ran into
This was my first time using AR, so one of the hardest parts for me was determining which platform I could use with my device. I wanted the end product to be a simple website app so that anyone could use InterstellAR without needing to download any specialized software. I spent a lot of time trying different AR solutions to find the one that was the easiest to use, was rendered in large scale, and was the most accessible.
Accomplishments that I'm proud of
I’m really proud of how the end product turned out! I’m not super experienced with React, so this was the first “real” website I’ve ever built with it, and I really like the end result! I’m also super proud of how the AR turned out! I think it looks really cool, and creates a great experience for the user.
What's next for InterstellAR
In the future, I would like to expand the 3D model library by adding more planets, spaceships, shuttles, etc. I would also like to add interactive learning activities, such as Trivia Fun Facts, quizzes, etc.
Built With
echoar
react
Try it out
github.com | InterstellAR | Bringing astronomy to life with augmented reality! | ['Julia Jones'] | [] | ['echoar', 'react'] | 26 |
10,277 | https://devpost.com/software/virtual-student-counselor-4podjm | CAYA face
Inspiration
Our life, and the present times were my inspiration. After the COVID 19 outbreak, millions of kids, forced into seclusion with school closures, were faced with loneliness, boredom, and stress. Those with both parents working suddenly had almost no one to talk to. That’s why I built CAYA, the Computed Automated Youth Advisor.
What it does
CAYA uses Machine Learning to act as an online counselor and friend to the millions of kids who have no one to talk to. It learns while the program is running by using a data set composed of conversational text inspired by child psychology papers. Though CAYA is not always perfect, it can offer great advice or just act as a friend to kids who feel lonely. CAYA also promotes children to talk through their worries.
How I built it
I built this app with ReactJS, Brain.js, and the web-text-to-speech API. I created a training set to understand the context of the conversation and what the user is trying to say in Brain.js. I used new CSS features to animate a human-looking face that could blink and move its lips. I also looked at real psychology papers to train my neural net. Finally I experimented with the text-to-speech API to create a personality and a tone that kids will feel comfortable with.
Challenges I ran into
I ran into many challenges in the process of building this project:
Synthesizing text into speech and changing the voice
Adding personality to the bot, animating the face
Training the neural net, deciding how many hidden layers and iterations we should have
Making CAYA conversational and carrying context throughout the conversation.
Accomplishments that I'm proud of
Overcoming the challenges I listed above is something I take pride in. However, what gives me most joy is that I was able to create a full machine learning program with new technologies and a low error rate in a little more than a day. I am also proud that I could construct a complex face using CSS.
What I learned
CAYA was a personal learning process too. I learned several things while building her. On the coding front I learned how to use the web-text-to-speech API so my web app could talk. I also learned about how a neural network trains and works, what an LSTM (Long Short Term Memory network) is, and how to get good results from the neural network. But I learned more than coding. While reading the psychology papers in order to train CAYA I was able to learn much about child and youth psychology that I hope to be able to use more in helping my generation deal with issues that surround us.
What's next for Computer Automated Youth Advisor
There are still definitely things that can be improved. I think what would make the CAYA a lot better is smoother conversation with more training, and able to understand the context more(understand what the user is talking about).
Built With
brain.js
css3
html5
javascript
machine-learning
react
text-to-speech | CAYA: Computer Automated Youth Advisor | A virtual student counselor to help kids deal with loneliness, school closure, grade fears, etc. during the COVID 19 crisis. | ['Siddhartha Chatterjee'] | [] | ['brain.js', 'css3', 'html5', 'javascript', 'machine-learning', 'react', 'text-to-speech'] | 27 |
10,277 | https://devpost.com/software/handright-q6z07k | First paragraph from my blog post http://kaushik.me/posts/onChaos.html handwritten
This might sound selfish but the idea of a handwritten document generator first struck me when I was thinking about how I could make something to improve my own life. Personally, I have slaved away countless hours just mindlessly copying from online articles only to upload a scanned version of the handwritten material later. This has always struck me as absurd and illogical and as
effort
just for the sake of it. It has no meaning and is simply a waste of time. So I sought out to automate this process as this hackathon seemed like the perfect opportunity (i.e excuse) to build it, as I myself do not possess the necessary skills to build the entire thing. I roped in three of my college mates and convinced them to build it with me. This was when I wasn't even sure such a thing could be possible. Then I stumbled across some other people's work on the same subject, such as
Alex Grave's paper
and a github repo of
theSage21
who used an api of a service built by Alex Graves which is now broken. However I wanted an intuitive tool which was self sufficient and was easy to set up and use. My teamates understood this and did an amazing job both training the tensorflow model and designing the vibe of the site, neither of which I am smart enough to do. Most of the gui is vanilla css and bootstrap cooked together by my friend
Rithwik
. Towards the end I struggled to seamlessly link the django frontend with my python scripts that acted as a bridge to tensorflow. But somehow towards the end of the marathon all the coffee was churned successfully into working code. And regardless of whether we win anything, I am proud both of our brainchild, handright.
Built With
css
html
python
shell
Try it out
github.com | HandRight | Convert your normal pdf into a realistic, handwritten form. | ['Kaushik Sivashankar', 'Ritika Sarkar', 'Rithwik Chithreddy'] | [] | ['css', 'html', 'python', 'shell'] | 28 |
10,277 | https://devpost.com/software/coronavirus-in-the-us | Inspiration
I live with my aunt and she asks me about the number of covid19 cases in the United States almost everyday. In order to save time searching on Google, I have a solution for myself now.
How I built it
Using the api from covidtracking.com, I created a table which is used to display the overall information about the number of coronavirus cases in the United States.
Challenges I ran into
The Covidtracking team updates their API frequently and they are also adding some constraints to their API URL. I need to keep checking the website to see if it works and fix the API URL if anything wrong happens.
Accomplishments that I'm proud of
This is my first website Ive ever built using Angular framework.
What I learned
Understood dependency injection concept.
Utilized Google GeoChart to implement an interactive map.
How components interact in Angular Framework.
What's next for Coronavirus In The US
After I made this website, my aunt asks me if there is any testing site nearby my place. I think I should add this feature into my website and some more information in regarding to how to protect yourself from getting infected.
Built With
angular.js
bootstrap
css3
html5
javascript
typescript
Try it out
covid19-in-us.herokuapp.com | Coronavirus In The US | Let's keep yourself posted with the number of Coronavirus cases in the United States | [] | [] | ['angular.js', 'bootstrap', 'css3', 'html5', 'javascript', 'typescript'] | 29 |
10,277 | https://devpost.com/software/atlashacks_2020 | Inspiration
I was inspired by my definite lack of productivity over the course of the lockdown and the steps I took to improve my productivity. I used the Pomodoro technique extensively to help boost my daily output. I'd like to make a website to help others be more productive in this challenging time!
How I Built It
I employed my existing skills in Flask, HTML/CSS and Js to build out the majority of my website. Bootstrap definitely helped me make a better website and reduced the time it took to implement my website design.
Challenges I Faced
The biggest challenge was making the Pomodoro timer and making it look nice. Initially, I tried to figure it out myself, but this proved quite challenging. I looked at a few tutorials online and was able to learn how to make a timer in Js. I'm far more confident in my Javascript abilities!
Demo URL (also in Github README)
https://pomm.herokuapp.com/
Built With
bootstrap
cs50
css
flask
font-awesome
html
javascript
jquery
python
Try it out
github.com | Pom. | A website to improve everyone's productivity! For now, its sole feature is a Pomodoro timer. | ['krishnarao22 Rao'] | [] | ['bootstrap', 'cs50', 'css', 'flask', 'font-awesome', 'html', 'javascript', 'jquery', 'python'] | 30 |
10,277 | https://devpost.com/software/calendar-cnojrt | -- | - | - | ['Mualla Argin'] | [] | [] | 31 |
10,277 | https://devpost.com/software/dontstealmycode-console-web-code-encrypter-decrypter | dsmc.herokuapp.com website's screenshot - mainpage
mainpage completed
mainpage loading the encrypted or decrypted code
mainpage loading and encryption or decryption complete and waiting for the download
Console view
Console Example
Example .py file
.py example file encrypted
example .json file
.json example file encrypted
dsmc python module screenshoot on PyPi
dsmc-web python module screenshoot on PyPi
Github repository screenshoot
Inspiration
We can see coding stealing everywhere and that's not for the good of computing, for sure !
This is why I have built Don'tStealMyCode framework !
What it does
dsmc is a module, console, program and web-based application which allow you to encrypt a decrypt code of whatever files encoded with utf8 and python-readable !
The module
allows you to use the program to code others programs, so the possibilities are numerous.
The console program
is to help you quickly encrypt and decrypt your programs or files.
The web application
is hosted on Heroku and encrypts and decrypts very easily the code you submit and allow you to download it or read it online if it's allowed by the browser.
How I built it
First of all, having the idea to develop dsmc, I have developed the console module in python and some bash ( the all backend ).
Secondly, I have learnt Heroku serving with Flask in order to submit my work on Heroku.
Then, I have developed the frontend in Html, Css, Javascript with the help of FontsAwesome and Google Fonts.
After that, building the controllers was a little hard because of non-matching for example between Dropzonejs and Flask. In this way, I was obliged to build my self dropzone model in pure Css ! The other problem at this state was that I wasn't able to import my local module. So, I completed the remaining tasks to submit my module to Pypi and then be able to install and import it in Flask as a requirement.
Finally, it was it ! All things were pretty good after correcting some of the remaining bugs !
Challenges I ran into
Developing a full dropzone system in pure vanillajs
Developing all this features in 24hours
Accomplishments that I'm proud of
I am proud of the challenges I have met
What I learned
Flask hosting on Heroku
Python packages good development way
What's next for DontStealMyCode - console & web code encrypter & decrypter
I think that this dsmc can be very useful for many persons, maybe enterprises if it's improved seriously and may become a reference (with the fonctionnal two factors algorithms I have developed for that) in the domains of the cryptography !
Built With
bash
css3
flask
font-awesome
google-fonts
heroku
html5
javascript
python
Try it out
github.com
dsmc.herokuapp.com
pypi.org
pypi.org | DontStealMyCode - console & web code encrypter & decrypter | Encrypts and decrypts your code or files with a console, module and/or web-based application to keep them safe ! | ['Nongma Sorgho'] | [] | ['bash', 'css3', 'flask', 'font-awesome', 'google-fonts', 'heroku', 'html5', 'javascript', 'python'] | 32 |
10,277 | https://devpost.com/software/voyageur-q04b1h | Inspiration
We had won the grand prize at an APAC-level hackathon and he got a chance to go to a startup conference in Barcelona this summer. But due to the pandemic, it was canceled. Now, Bhavya is not sure if he’ll go even if the conference is next year. We realized this would be the case for many travelers, both leisure and business. One of the major problems would be making travelers gain the confidence to travel again.
We decided to do something to encourage people to travel, by assuring them of safety.
Our solution solves these problems:-
Hygiene & Health
Hack the very definition of travel in ways that address the health concerns long after the COVID-19 slowdown has passed. These inventions must demonstrate how the well-being of travelers and businesses is preserved or improved during travel rather than put at risk.
Sustainability & Relief
With pre-pandemic travel practices as your starting point, and new business models and social/environmental impacts as your guide, invent new responsible, socially impactful products and services that drive exceptional travel experiences and economic growth. Also, with public health and employment concerns at the forefront now, demonstrate how your invention measurably enhances economic conditions in regional and local destinations around the world.
What it does
We have created software services for hotels, airports, parks, restaurants, museums, theatres, and other enclosed private tourist spots. Our system will automatically detect whether people are following social distancing and whether they are wearing masks or not, from CCTV footage. The owners of the place will be alerted if someone is not following the rules.
These places can advertise that they’re using an automated system to ensure safety, and this will attract more tourists.
The other facet of our solution is an Android app for travelers/tourists. Users can pick a destination and a date of interest. We will show them the updates of that area, and give the estimated number of cases. This estimation is based on a predictive ML model.
This will help users make an informed decision and they can postpone their trip well in advance, without losing out money on cancellation charges. This will also help air travel companies and hotels, who have to bear losses if a person cancels their stay.
How we built it
We have taken a sample recording of the CCTV camera footage. An image processing model detects and classifies various bounding boxes based on the distance between people in the video. Also, we have the Mask detection algorithm which was built using CNN and it checks whether people are wearing a mask or not and creates a bounding box around the face. So the viewer knows the number of people violating the norms.
These models were built in Python.
The website for private owners (of the hotel, market, tourist spot) was built using React, Firebase, and Node. The mobile app for users (tourists) was built using the Android Studio and Firebase.
Challenges we ran into
One challenge was Data privacy. For that, we will ensure that the output of our machine learning model that will run on the CCTV frames will only number: that is the number of the red bounding boxes and the number of the green bounding boxes. This will be stored and updated on the cloud database dynamically. These stats will be made available to the websites of the private tourist places. From this, the private tourist authorities will get an idea about the number of people maintaining and following the social distancing norms.
Accomplishments that we're proud of
We are proud of the fact that our project will help many travelers, both leisure and business in the aftermath of this pandemic. We will be providing one of the major strengths to travelers that is gaining confidence to travel again. We are really happy to be part of the change that will boost & encourage people to travel safely.
Technology Used
We have used Machine learning to detect if people are following COVID19 norms- social distancing and wearing masks. We have used the YOLO model to detect people. Once that task is achieved we have calculated the euclidean distance between the bounding boxes(output of the ML model). We check if the distance has been above a threshold that we have defined. If so, we attribute such a group of people with a red bounding box. For mask detection, we have made a custom CNN model wherein we have annotated the mask image and trained the convolutional neural network for the mask image. The model detects the presence of masks in the frame and draws a bounding box around it.
For COVID19 trend prediction, we have used data of a place named Mumbai in India. We have used Recurrent neural networks(RNN) for such prediction because of the fact it can remember past trends and predict future trends on the basis of past knowledge.
For the website, React, Node, and Firebase were used. For mobile apps, Android Studio, Google SDK, Covid19 API, and Firebase were used.
What's next for Voyageur
The next plan would be to host our entire application on the cloud. The ML models and the backend will be deployed on the cloud. In phase 1, we would like to try out this solution locally. We will tie-up with local hotel chains and tourist spots in Mumbai and devise a basic billing plan to start earning revenue. We will also release our app for tourists on the play store. After these iterations and learning from the results, we would like to partner with more places and or a company like Trivago which can in turn sell these services to its partners.
Built With
android-studio
machine-learning
Try it out
github.com | Voyageur | Make people confident to travel again | ['Vedant Kumar'] | [] | ['android-studio', 'machine-learning'] | 33 |
10,277 | https://devpost.com/software/foober-rld47h | Inspiration:
Our team has adjusted to the COVID-19 environment pretty well, however many others are not as fortunate as us. Employment issues, health issues, money issues, and food shortages have caused a substantial amount of Americans to be unable to afford basic necessities such as food. It was hard for us to watch all these people struggle, so we decided to do something about it.
Thus, we created Foober. COVID-19 Pandemic has caused millions to lose their jobs, and many cannot pay for food anymore. Watching food banks run out of food constantly on the news got us thinking what we could do to. We decided to create a website which people can donate and receive food and other necessities.
What it does:
Through Foober, users can make postings of necessities and foods they are willing to donate, they can then set a location on the map as a meeting place. Those in need can see these postings on the website's map and meet up with the donators to receive the items. A person in need can click on a marker created by a donator, and the person in need can get into contact with the donator, and they can meet up at the address given, and the food can be donated.
How We built it:
The Foober website was built using Javascript, HTML, CSS, and the Google Maps API. We used HTML, CSS, and JS to write the code for the website and its animations. We used JS and the Google Maps API to create our donation map which has the postings. The JS scripts take the user input, and create a marker on the map with the information given.
Challenges We ran into:
Our team struggled with getting the forms on the website to create postings on the map. We had all never used the Google Maps API before so learning it together really helped us bond as a team. To start off we originally did not realize we needed latitude and longitude to make a marker in the google maps. We tried converting an address to lat and long coordinates, however we were unsuccessful in our attempts. We decided to have a link in the form to a website which will convert ones address to lat and long, and have the user input their results. Another issue we faced concerned getting the user inputs and creating the marker. We faced many issues with variables being considered null, however it took us a while to fix this issue. Eventually, we were able to get the user input and create a marker. It took many long debugging sessions until we were able to fix all of the issues with our code and get it to run properly.
What we learned:
We learned quite a lot about HTML and CSS, as there was quite a bit of code in these formats. This was also our first time working with JS and animations, and we thought we did a pretty good job. On top of this, we also learned how to use the Google Maps API integrated with user inputs. We were able to make a very nice looking site with the works of a working maps api which takes user input and creates a marker with information given by the user.
What's next for Foober:
Foober can easily be formed into a public website suited for the real world. We plan on adding a better looking marker for donation posts, and then hosting it on servers, so anyone can use it. To do this we would also need to implement a database, something which we look forward to doing.
Built With
api
css
google-maps
html
javascript
Try it out
github.com | Foober | Foober is a website where those who need food can get it, and those who have more than enough can donate. | ['Arnav Garg', 'Shafin Haque', 'Neel Dankar', 'Ishir Lakhani'] | [] | ['api', 'css', 'google-maps', 'html', 'javascript'] | 34 |
10,277 | https://devpost.com/software/datadaygrind | HeartTrends Logo
Home page, displays the various analyses performed.
Depicts the age distribution among those affected by heart disease.
Proof for domain name, hearttrends.tech
Inspiration
Cardiovascular diseases, resulting in compromised blood vessels, clogged blood clots, and weakened hearts, are the leading cause of death for men, women, and the most racial/ethnic groups in the United States. One person every 37 seconds die from heart disease. HeartTrends offers an eye-opening data analysis that delves into the multiple factors and variables behind those affected.
What it does
HeartTrends is a simple yet immersive web application that discovers interesting trends and distributions from a UC Irvine database. The website depicts 5 novel factors behind cardiovascular diseases -- age, chest pain type, maximum heart rate, resting blood pressure, and serum cholesterol. Initially greeted with the home page, the user can choose from a variety of selection cards that link to a full-page exploratory analysis of previously mentioned factors behind the disease. Each plot offers an interesting relationship between general heart health and variables that can be easily measured at any time. The dataset used is primary data from people hospitalized for cardiovascular disease. Thus, the user can compare their own heart rate and blood pressure to the distribution, serving as a predictive model for future heart attacks and resulting symptoms.
How I built it
I built HeartTrends using R and NextJS. To generate all of the plots and charts that are displayed on the website, I coded a command script that reads in a CSV file taken from the UC Irvine Dataset on Kaggle. Then I sorted the file into the corresponding variables and created 6 ggplots of the age, heart rate, chest pain, blood pressure, and serum cholesterol. The y-axes display the frequency and the x-axes are the numerical distributions. After I created a plot of each of the factors, I combined them into one image, shown in the "All Plots" card, by using the grid.arrange function. I used NextJS and used CSS styling to create an easily navigable UI. The 6 cards redirect the user to their chosen analysis, serving as an informative and effective web application.
Challenges I ran into
This was one of my first times analyzing data and creating meaningful plots in R Studio. It was challenging to build and arrange the plots, but after reading more R documentation, it was awesome to see such interesting trends come out of a complex CSV file.
Accomplishments that I'm proud of
I'm proud of providing an easy-to-use predictive model for such a prevalent and dangerous condition.
What I learned
I learned how to data-mine and plot interesting graphs. I also discovered the impact that a good CSS style can make on a website. Initially, my website was composed of radio buttons and default fonts. But after creating new text formats and designs, I was surprised to see how great the UI appeared.
What's next for HeartTrends
I plan for HeartTrends to be expanded to include more diseases, such as different cancers and viruses. With the widespread COVID-19 chaos, I want to provide an exploratory website that can show the distribution of the virus around the world.
Built With
javascript
nextjs
r
react
Try it out
github.com
hearttrends.tech | HeartTrends | Predictive models for cardiovascular diseases through an exploratory UI. | ['Danny Zhang'] | [] | ['javascript', 'nextjs', 'r', 'react'] | 35 |
10,277 | https://devpost.com/software/deliver-safe | SIgnUp View
Login View
My profile shows the user home address, name, email, and the balance coin.
Adding location of the users home.
Creating Request which will be visible to all the user within 3 Kms radius.
Request List that contains all the request with 3 Km range of the users current location
My Activity view shows the request that is created by user and the request accepted by the user.
Error message if someone tries to accepted his own request.
Inspiration
In COVID-19 pandemic people are quarantined but they still have to be in queues at different locations, such as doctor’s offices or in supermarkets which is not the best practice to avoid COVID-19 pandemic. Social distancing is the best way to protect yourself and others from COVID-19 infections. However, avoiding crowds in waiting rooms is not easy.
The challenge of “social distancing” and waiting lines has not been a relevant use case in the past. Our services solve these problems brought forward by the pandemic: Exchanging resources, stop unnecessary queueing, and overcrowding.
What it does
I wanted to create an easy to use and understandable system/service which could be used to avoid the unnecessary crowd.
It is very important that I create a very easy platform to use which could be developed and implemented within two weeks or so. This pandemic we saw how people are facing difficulties to get things done. We have also seen many situations where the government was not sure whether they should implement/increase the lockdown. Social distancing is one of the best ways of protection against COVID-19 infections.
Our vision is to let the user exchange services such as going to the market, visiting the doctors for appointments, and many more.
Users can create a request for service that they want such as the requirement of the food supply. The request will be visible on the request list of the local area (3 km radius). All the users of that local area would be able to see the request. The request can be full filled by another user who is able to do the job.
After completing a particular request the user who full filled the request will receive coins from the user who created the request. The number of coins received will depend on the request. Users can also cash the coins if wanted.
Users can buy more coins if they are out of coins and want to make more requests. This will not only decrease unnecessary crowding and violation of social distancing but also will help the local business to function properly during the pandemic period.
Use Cases:
Let’s say a user ‘X’ creates a request for a food supply. The request will be visible in the request list of the local area. Let’s say another user ‘Y’ of that local area was near a market and notices the request. He could full fill the request made by the user ‘X’ by buying the food and delivering it to the user ‘X’.
2. Let’s say user ‘X’ creates a request for a local doctors ‘Y’ appointment. Let’s also assume that doctor ‘Y’ is also a user. Then doctor ‘Y’ could full fill the request and call the patient i.e user ‘X’ whenever he fill free.
How I built it
Since the app is created with user-centered design in mind so, I started with the sketch of the app. After completing the basic sketch. I started deciding responses of the APIs that I would use in the iOS app. Once the responses were decided, I started creating the actual APIs using Python and Flask. After the APIs were completed I deployed the server app on Heroku and tested if everything is working as expected.
After completing the server app I started creating the UI using the storyboard of Xcode. Once all the UI was completed using dummy data I integrated the APIs that were created earlier and were deployed on Heroku. Then I test the app for any possible bug and fixed it.
Challenges I ran into
The main challenge was the user-centered design. As the app was made from a user point of view. It was very important that the app was easy to use and understand.
Accomplishments that I'm proud of
The system could really be used in the real world as it solves one of the real-world current problems. This system could also produce new opportunities for local business to reach their customer.
What I learned
I learned a lot about database and backend.
What's next for Deliver Safe
There are many things to be improved:
The users will be able to buy coins that will be implemented using ethereum cryptocurrency.
I also want that along with the exchange service, the system should also monitor each user's daily activity i.e the number of people they are interacting to get their request done, to provide them and the government the necessary data about the condition of the locality.
This will not only decrease unnecessary crowding but also will increase the local business. Also, the government and users will get proper data on the condition of the locality which will help them in taking better decisions regarding the pandemic.
Built With
alamofire
bcrypt
flask
flask-mail
flask-sqlalchemy
heroku
python
swift
uikit
Try it out
github.com | Deliver Safe | Social distancing is the best way to fight against COVID-19. My vision is to let the user exchange services such as going to the market, visiting the doctors for appointment and many more. | ['Dhrubojyoti Biswas'] | [] | ['alamofire', 'bcrypt', 'flask', 'flask-mail', 'flask-sqlalchemy', 'heroku', 'python', 'swift', 'uikit'] | 36 |
10,277 | https://devpost.com/software/find-a-peaceful-protest-fi9ka2 | Inspiration
When I watched the news, I noticed how many protests around the world support different communities and movements. However, I also noticed many protests had violence, which often was not related to the movement itself. Violence is a reason many people who want to support their movement don’t attend these protests. For this hackathon, I decided to build something to help people connect and find peaceful protests.
What it does
Find a Peaceful Protest is an interactive map with user-generated content. It allows users to add new protests and find existing ones. It also has a review system where users can add their own account of the protest and images of the protest.
To reduce the amount of fake protests and reviews, Find A Peaceful Protest has a smart system where it calculates your reliability. The more reliable you are, the greater the impact is of your new protest or review.
Additionally, a color-coded map navigation system makes it easy to see which protests are right for you. Markers on the map are color-coded according to how peaceful the protest is rated, and the opacity of markers are set according to how reliable it is.
How I built it
For the map, I used Leaflet.js for the user interface, OpenStreetMap for the map content, and ESRI for geocoding and reverse geocoding. For the backend, I used Firebase Realtime Database to store data and Firebase Storage for image storage. For the general structure of the website, I used HTML/CSS and JavaScript, as well as W3.CSS. I used Firebase Hosting to host my site.
Challenges I ran into
I was not familiar with the Leaflet.js library when starting the project, so it took some time to understand and learn it. Additionally, I had some problems with getting an image URL from Firebase Storage, but eventually figured it out after reading the documentation.
Accomplishments that I'm proud of
I am proud of figuring out how to implement the Leaflet.js map without prior experience in using the library.
What I learned
I learned a lot about Leaflet.js, as well as Geocoding and accessing geolocation in the browser.
What's next for Find A Peaceful Protest
I plan to implement an account system for Find A Peaceful Protest to further increase reliability of data and repeated reviews from the same person.
Built With
esri
firebase
html5
leaflet.js
openstreetmap
Try it out
github.com
find-a-peaceful-protest.web.app | Find A Peaceful Protest | Not attending protests because of violence? Find a Peaceful Protest today. | ['Benjamin Man'] | [] | ['esri', 'firebase', 'html5', 'leaflet.js', 'openstreetmap'] | 37 |
10,277 | https://devpost.com/software/daily-putnam-math-challenge | Inspiration
Math can often feel boring or mundane because students are often just solving math problems from a textbook where there is a list of similar problems that you keep solving like a robot. Daily Putnam Math Challenge is a website to get students interested in competitive mathematics at a slow and easy pace. Only 1 (very difficult) Math Problem every day.
What it does
Daily Putnam Math Challenge is a website where every day a Putnam math problem is uploaded, along with the official solution to yesterday's Putnam problem. Users can upload their solution to the math problem by either using LaTex or uploading a picture of their working. Once they do, they are led to the Discussions webpage where they can see all the other solutions that were posted by users around the world. Users can upvote solutions they feel have a good explanation and they can even comment under solutions to ask specific questions about a solution.
How I built it
I built the website using Python 3 and the Flask micro web framework.
What's next for Daily Putnam Math Challenge
The immediate goal is to implement user accounts in this system where users can register with their email/username and password. Right now there is a massive bug in the system where a user can upvote his/her own solution as many times as he/she wants. I need to implement a feature where a user can't upvote his/her own solutions and a user can only upvote a solution once. User accounts can also make the comment section of each solution much more descriptive.
Built With
flask
mathjax
python
Try it out
github.com | Daily Putnam Math Challenge | This is a website where a Putnam Math Problem is uploaded everyday and users can post their solutions to the problem and then discuss and upvote each other's solutions. | ['parthiv2048 Ganguly'] | [] | ['flask', 'mathjax', 'python'] | 38 |
10,277 | https://devpost.com/software/book-barter-okdisv | Inspiration
In this hackathon, our team is inspired to create Book Barter to empower people to read books by enabling people to engage in a community of bookworms and allowing people to trade books with one another with ease. Statistically speaking, there has been a significant decrease of the number of people who read books. According to CNBC, 24 percent of American adults haven’t read a book in the past year. In addition, a person from a low-income background with lower levels of education is less likely to consume books. Henceforth, Book Barter is a free e-commerce trading platform for all people from different walks of life.
These are the questions we pondered about:
I want to read books but I don’t have the money to buy a new one. However, I have some spare books. How can I read new books to stimulate my brain?
How can we empower the disadvantaged and underprivileged people to buy books free of charge?
What if you want to read a new book without paying for that one?
How to meet and interact with other bookworms through an e-commerce platform?
How can I try out fresh genres from people who have loved their books?
What it does
Enables users to trade books in an e-commerce platform with ease
Allows people to handle trade requests by allowing users to send, accept and decline these requests
Matches book requests based on user’s preferences
Challenges we ran into
Our team has difficulty connecting the middleware to the frontend
Our team faced difficulties in communicating with each other due to time zone differences
With the time zone difference, some of us had to compromise by sacrificing our sleeping schedules
However, we did not want time zone differences, sleep deprivation and a bad internet connection to hold us back from participating at Atlas Hacks 2020
Another challenge that we ran into was that that we had difficulties pulling down parts metadata about the user and allowing it to be apart of the listing and therefore provide contact information to actually complete the trade.
Finally, we had extreme difficulties with the loading of Angular components into the DOM after it had initially been loaded. We had to allow the dynamic parts of of the Angular to be responsive within the website so that users could click the buttons in order to make trade. With great difficulty, we were able to solve the issue.
What we learned
We learned how to use PHP and the MongoDB database to store information in collections and documents that we could then store and manipulate.
We learned to use online APIs in order to extract information, specifically geolocation and various book information.
We also learned the difficulties of connecting this middleware and backend to the frontend which needed to be more responsive to fit our needs.
We used Angular for the frontend responsiveness and that was something we had to brush up on.
Built With
angular.js
bootstrap
css3
dockerfile
html5
javascript
mongodb
php
typescript
Try it out
github.com | Book Barter | Online Book Trading Platform For All | ['Avaye Dawadi', 'Maya Dickson', 'Owen Oertell', 'Arianne Ghislaine Rull'] | [] | ['angular.js', 'bootstrap', 'css3', 'dockerfile', 'html5', 'javascript', 'mongodb', 'php', 'typescript'] | 39 |
10,277 | https://devpost.com/software/pie-rooms-contactless-private-restaurant-in-a-private-room | Inspiration
No Safety in open Restaurant: Post covid-19, people will be more concerned about safety & it will become huge when they will have to go to an open restaurant to have their dine-in experience where they will have to touch menus, interact with other people, will sit in the used couch, will be near to other people, do the billing in the counter & will have to interact with others also no idea about how the food in prepared inside the kitchen.
No Private space to enjoy: Most of the time Travellers or general people wanted to get a place where they can freely enjoy or chill-out for few hours with full privacy. When people generally got stuck in a city & have some free tiem to spare.
Judgement Issue: Mostly couples,party goers or even families get judged/stared by other people in an open restaurant, which creates an discomforting/embarrassing moment for the people who are being stared. This simply spoils the mood to enjoy.
What it does
It provides a private space in a hotel/guest house to couples,party goers & families to have their dine-in experience, food, some fun & us time together with zero disturbance or interaction with others with complete privacy,& a single centralised kitchen in the same building to serve in those rooms.
they need our solution because
They need to get private dine-in experience with their loved ones.
For Group party, birthday parties etc.
For lunch/dinner Date
For Gossiping & spending time together.
Chillout
Safety & enjoyment in corona times
How we built it
We built a Web app with the help of various frame works. We used ionic for frontend. Ruby & rail for backend. We used mysql for database support.
We deployed the frontend in firebase & backend in heroku.
Challenges I ran into
Finding a good team to make our video & software.
Restructuring of the plan.
Lack of good internet connection
Got to add too many things in the website in a limited time.
Had to remove a lot of bug from the website.
Accomplishments that I'm proud of
1.We successfully completed our task in such a less time.
2.Got an amazing hard working team to work with in future.
3.We are proud of coming up with an idea which has the potential to change the world
4.We are proud of creating a service which can restore hospitality industry with more customer satisfaction.
What I learned
Team work is necessary if you want to create something amazing.
Working with calm minded in rush or hurry situations can really help in good thinking, executing & managing the team.
Creating value in a business is the key to success.
Always focus on the big goals you want to achieve. It really helps in keeping you focused.
Accomplish more in less time.
What's next for Pie Rooms:Contactless Private restaurant in a Private Room
We are going to implement it in some properties by modifying them. After that we are going to test our different assumption by taking customers review & will do some modifications if necessary. Now that we tested the product & customers liked it, we will expand our branches in multiple cities with some external funding.
Built With
heroku
ionic
mysql
ruby-on-rails
Try it out
piehotelodisha.firebaseapp.com | Pie Rooms | Contactless Private Restaurant in a Private Room | ['Sourav Prajapati', 'Rishab kumar shah'] | [] | ['heroku', 'ionic', 'mysql', 'ruby-on-rails'] | 40 |
10,277 | https://devpost.com/software/fund-predictor | poster
Analysis of Wildfires in USA
Analysis of number of burned acres every year
Analysis of total of funds have been allocated in each activity in millions
Analysis of funds allocated to Fire Operations every year
Analysis of funds allocated to fight wildfire every year
Analysis of funds allocated to Preparedness every year
Analysis of funds allocated to Other fire Operations every year
Inspiration
There are more than 50,000 wildfires in America every year. The recent wildfires in California and Australia showed how important it is to have a disaster plan handy. While analyzing the wildfire data from past 15 years including number of fires, area burnt, wildlife damage, structural damage and funds required for suppression and fire operations, we found that the data followed a certain pattern.
We trained a Machine Learning model using python to learn this pattern and Predict how much damage will be there in the current year and how much funds will be required for the same.
Also, one of the major problem people have while donating for a good cause is that they don't know where their funds are being used. To solve this, we added a funds tracker so taxpayers and donates can see exactly how and where their money is being used.
Apart from this, we made a wildfire detector that can alert the Forest Service as soon as a fire starts.
What it does
The front page contains analysis of data from wildfires from past 15 years including Heat maps, Bar graphs and Pie charts. On the Funds page, you can see how much damage is predicted from wildfires this year and where the funds were used last year. Also, you can view ongoing wildfires and the funds that are predicted will be necessary to contain and repair any damage caused by those fires along with a distribution of funds in the following categories:
Fire Operations
Preparedness
Suppression
Other fire Operations
Hazardous Fuels
Other activities
FLAME Account
Additional Wildfire Appropriations
Users can donate using the donate button and see how their donations will used in a fair and transparent way.
The fire sensors can be installed at strategic locations throughout the forests so that if there is a wildfire, Forest Services get notified as soon as possible. Since the wildfires spread easily, a quick alert system can help reduce the damage and provide rapid response.
How we built it
We used
Python
for cleaning the data and making the Machine Learning models.
D3.js
and
Matplotlib
to make graphs, heat maps and pie charts.
Figma
for UI designing and
Netlify
for hosting services. Also, the fire sensor was made leveraging the thermistor on
Circuit playground express
board.
Challenges we ran into
We had trouble collecting and cleaning the data as most of the data for funds allocated was in form of pdf files so we had to convert it to csv format for proper usage.
Accomplishments that we're proud of
This was the first hackathon for two of our teammates. We're proud of how the website looks to be quite honest - for us, once it started coming together , it was so gratifying seeing it work together as a coherent whole. We learnt how to collaborate with each other smoothly despite being in different timezones.
What we learned
We learnt Data Visualization, Machine Learning, Data Analyzing, hosting websites and using Figma and Netlify.
What's next for Fund Predictor
We'll add a way for people to volunteer in case of calamities and to provide non-monetary donations.
Domain
Our entry for best domain name is
FundFireFrom.space
Built With
circuitplayground
d3.js
figma
heroku
kaggle
matplotlib
mu
netlify
python
Try it out
fundfirefrom.space
www.kaggle.com
www.kaggle.com
github.com
fundfirefromspace.netlify.app | Fund Predictor | Analyses and Predicts required fund for a disaster via a Machine Learning Model trained past 15 years of data. | ['Vishal Kumar', 'Jatin Dehmiwal', 'Luis Silva', 'Saad Rehman'] | ['Second Overall'] | ['circuitplayground', 'd3.js', 'figma', 'heroku', 'kaggle', 'matplotlib', 'mu', 'netlify', 'python'] | 41 |
10,277 | https://devpost.com/software/smarttracker-covid19 | Inspiration :
Now a days whole world facing the novel Corona Virus, to track the spread of novel Corona Virus country-wise, details of confirmed cases, deaths and Recovered, awareness regarding COVID-19. This Android app was created to spread awareness about the covid -19 virus.
What it does :
The Android app named as ‘SmartTracker-Covid-19’ created to spread awareness about the COVID -19 virus. App includes following functionalities:
CoronaEx Section -
This section having following sub components:
• News tab: Having latest new updates. Fake news seems to be spreading just as fast as the virus but as we have integrated from official sources so everyone will be aware from fake news.
• World Statistic tab: Real-time Dashboard that tracks the recent cases of covid-19 across the world.
• India Statistic tab: Coronavirus cases across different states in India with relevant death and recovered cases.
• Prevention tab: Some Prevention to be carried out in order to defeat corona.
CoronaQuiz section - quiz that will help people know about the Corona virus and its effects on human body. It chooses random questions and show the correct answer for the questions and at the end user will get to know their highest score.
Helpline Section - As this application particularly made for Indian citizen to use, all state helpline number of India included.
Chatbot Section - A self-assisted bot made for the people navigate corona virus situation.
Common Questions: Start screening,what is COVID-19? , What are the symptoms?
How we built it :
We built with using Android studio. For the quiz section we have used sqlite database and live news data we have integrated from the News API. For the coronavirus statistic we have collected data from worldometer and coronameter.
Challenges we ran into :
At time of integrating the chatbot in application.
Accomplishments that we're proud of :
Though , It was the first attempt to create chatbot.we have tried to up our level at some extent.
What's next for SmartTracker-COVID19 :
For the better conversation we will be looking to work more on chatbot.
Built With
android-studio
chatbot
java
news
quiz
sqlite
Try it out
github.com | SmartTracker-COVID-19 | Android app to track the spread of Corona Virus (COVID-19). | ['Pramod Paratabadi', 'Supriya Shivanand Madiwal .'] | ['Best Use of Microsoft Azure'] | ['android-studio', 'chatbot', 'java', 'news', 'quiz', 'sqlite'] | 42 |
10,277 | https://devpost.com/software/reduced-gy54du | Reduced
🔗 Reduced is a powerful modern custom URL shortener with a minimalistic design made with MEVN stack by
Sumit Kolhe
✨ Features
:heart:
Lightweight and minimalistic design :
Modern minimalistic design that is a treat for the eyes.
:zap:
Easy to use :
Simple and intuitive design thats easy to use.
:rainbow:
Support for Custom Aliases :
Support user defined custom aliases as well as randomly generated ones.
:iphone:
QR Code Support :
Generates QR Code for shortened links instantly.
:card_file_box:
Store previous links :
Stores previously shortened links in
localStorage
of the browser for easy access.
:rocket:
Performance :
Reduced is built using the MEVN stack to ensure lightning-fast speeds and great performance.
:pencil2:
Public API :
Free public API that can be used to shorten links quickly or implemented on any other frontend.
:wastebasket:
Auto link deletion :
All shortened links are automatically deleted affter 10 days of creation.
:lock:
Secure :
We don't collect any data about you or store logs in our server.
🖥️ Demo
https://reduced.me
🧰 Built with
VueJS
: Frontend framework
Vuetify
: Vuejs Framework
Express
: Backend server
Nodejs
: Javascript runtime engine
MongoDB
: Data storage
:construction_worker: SETUP
Clone the repository or download the latest
release
to a folder of choice.
$ git clone https://github.com/sumitkolhe/Reduced
:building_construction: Backend Setup
Install the dependencies for the backend
$ cd Reduced
$ npm install
Rename the
.sample-env
file to
.env
and fill all the required fields
To start the app
$ cd Reduced
$ npm run dev
NOTE :
Running only the backend server will use previously generated static files ( from server -> static ) for the frontend.
:art: Frontend Setup
Make sure you have Vue-CLI installed, if not
$ npm install -g @vue/cli
Install the dependencies for the frontend
$ cd client
$ npm install
Rename the
.sample-env
file to
.env
and fill the required fields
To run frontend only
$ cd client
$ npm run dev
To build frontend
$ cd client
$ npm run build
NOTE :
All frontend builds will automatically be placed in
server -> static
. You can edit this in
client -> vue.config.js
:pencil: REST API Documentation
Reduced comes with a fully functional API that can be used to create short links with support for custom Aliases. As of now no authentication is required for using the API.
The API resides in
Reduced -> server
and can be modified as per one's use case
:alembic: Features of the REST API
Allow creating short URLs with or without custom aliases.
GET link statistics for shortened URLs. This includes -
Total number of clicks
Date / Day of Creation
Time of Creation
Original link
Time / Date of link expiration
The API comes with
Rate-Limiting
by default. The settings can be changed as per one's requirements.
CORS
is also enabled by default
:triangular_flag_on_post: REST API
The REST API requests and endpoints are described below.
# Create a short link
POST /api/shorten/
Creating short URL
without
custom alias
curl --header "Content-Type: application/json" \
--request POST \
--data '{"longurl":"google.com"}' \
http://localhost:80/api/shorten
Response Object
{"clicks":0,
"stats":[],
"_id":"5ef749408887c725bc489620",
"alias":"ejrf",
"shorturl":"https://reduced.me/ejrf",
"longurl":"http://google.com",
"created":"2020-06-27T13:27:28.374Z",
"expire":"2020-07-07T13:27:28.374Z",
"__v":0}
Creating short URL with custom alias
curl --header "Content-Type: application/json" \
--request POST \
--data '{"alias:"sample","longurl":"google.com"}' \
http://localhost:80/api/shorten
Response Object
{"clicks":0,
"stats":[],
"_id":"5ef74ae98887c725bc489621",
"alias":"sample",
"shorturl":"https://reduced.me/sample",
"longurl":"http://google.com",
"created":"2020-06-27T13:34:33.903Z",
"expire":"2020-07-07T13:34:33.903Z",
"__v":0}
Failed Requests
Alias already exists :
API throws error if a custom alias is provided but it already exists in database.
curl --header "Content-Type: application/json" \
--request POST \
--data '{"alias":"sample","longurl":"google.com"}' \
http://localhost:80/api/shorten
Response Object
{"status":"AAE",
"message":"Alias already exists"}
Invalid link provided :
API throws error if an invalid link is supplied
curl --header "Content-Type: application/json" \
--request POST \
--data '{"longurl":"google"}' \
http://localhost:80/api/shorten
Response Object
{"status":"IURL",
"message":"Invalid URL"}
# Get Link Statistics
POST /api/check/
curl --header "Content-Type: application/json" \
--request POST \
--data '{"linktocheck":"reduced.me/sample"}' \
http://localhost:80/api/check
Response Object
{"clicks":0,
"stats":[],
"_id":"5ef74ae98887c725bc489621",
"alias":"sample",
"shorturl":"https://reduced.me/sample",
"longurl":"http://google.com",
"created":"2020-06-27T13:34:33.903Z",
"expire":"2020-07-07T13:34:33.903Z",
"__v":0}
Failed Requests
Link does not exist :
When the supplied link to check does not exist in database.
curl --header "Content-Type: application/json" \
--request POST \
--data '{"linktocheck":"reduced.me/sampleinvalid"}' \
http://localhost:80/api/check
Response Object
{"message":"Link does not exist"}
Invalid Link :
When the supplies link is invalid
(is not an actual link)
.
curl --header "Content-Type: application/json" \
--request POST \
--data '{"linktocheck":"invalidlink"}' \
http://localhost:80/api/check
Response Object
{"message":"Invalid Link"}
# Check Server Status
GET /api/status/
curl --header "Content-Type: application/json" \
--request GET \
http://localhost:80/api/status
{"status": "OK"}
✍️ Authors
Sumit Kolhe
-
Author
📜 License
This project is licensed under the
MIT License
- see the
LICENSE
file for details.
Built With
express.js
html
javascript
mongodb
node.js
vue
Try it out
reduced.me
github.com | Reduced | Reduced is a powerful modern custom URL shortener with a minimalistic design and a public API made with MEVN stack | ['Sumit Kolhe'] | [] | ['express.js', 'html', 'javascript', 'mongodb', 'node.js', 'vue'] | 43 |
10,277 | https://devpost.com/software/c-care | When our app worked, Satisfied
Inspiration
During this current COVID 19 pandemic, I see health worker is curing the patients, doctors are innovating new medicine, the police is controlling the crowd movement and even bus drivers are helping people to get back to home. As a future engineer, I felt like my contribution is none, so I felt motivated to do my part and try to bring a positive change and to make sure my product can also be used in a future pandemic.
problem our project solves
Offices and workplaces are opening up and as the lockdown loosen we have to get back to work, but there is a massive possibility that infection can spread in our workplace as, When a person is infected he can be asymptomatic for up to 21 days and still be contagious, so the only way to contain the spread is by wearing a mask and maintaining hand hygiene. WHO and CDC report said that if everyone wears a mask and maintains hygiene then the number of cases can be reduced three folds. But HOW we will do that? , How can we make ever one habituated to the following safety precaution so the normalization can take place. So we have come up with a solution called C-CARE 1st ever preventive habit maker that will bring a positive change.
What our project does
Our app is 1st of its kind safety awareness system, which works on google geofencing API, in which it creates a geofence around the user home location and whenever the user leaves home, he will get a notification in the C-CARE app ( ' WEAR MASK ' ) and as the users return home he will get another notification ( ' WASH HANDS '), ensuring full safety of the user and their family. It is also loaded with additional features such as i.) HOTSPOT WARNING SYSTEM in which if the user enters into a COVID hotspot region he will be alerted to maintain 'SOCIAL DISTANCING' And it also has a statics board where the user can see how many times the user has visited each of these geofences. With repeated Notification, we will make people habituated of wear masks, washing hands, and social distancing which will make each and every one of us a COVID warrior, we are not only protecting ourselves but also protecting others, only with C-CARE.
Challenges we ran into
1,) we lack financial support as we have to make this app from scratch.
2.) the problem in collecting data regarding government-certified hotspot and also we have to do a lot of research regarding the spread pattern of COVID-19.
3.) Due to a lack of mentors, whenever the app stop working we had to figure out by ourself, how to correct the error.
4.) It took us too long to use it in real-time as during lockdown it was too hard to go outside in the quarantine but finally, after lockdown loosens a bit we tested it and it gave an excellent result.
5.) we didn't know much about geofencing before that so we have to learn it from scratch using youtube videos.
Accomplishments that we're proud of
WINNER at Global Hacks in the category of HEALTH AND MEDICINE.
WINNER at MacroHack As the best Android Application.
WINNER at MLH Hackcation in the category ( Our first Hackcation ).
TOP 5 in innovaTeen hacks.
TOP 10 in Restartindia.org and Hack the crisis Iceland.
What we learned
All team members of C-CARE were able to grow their area of competence by participating in the whole process of idea definition, market research, validation, prototyping, and presentation. Through different mentor sessions, we learned that problems could be approached by many means, but most importantly our mission should be clear.
What's next for C - CARE
COVID cases are increasing every day, and chances are low that we can create a vaccine immediately, apps like C-CARE will play a crucial role in lower the spread of infection till a proper vaccine is made.
Our app can also be used for seasonal diseases such as swine flu or bird flu or possible future pandemic such as Hantavirus, G4 Virus, bubonic flu, Monkeypox.
Built With
android-studio
geofence
google-maps
java
sqlite
Try it out
drive.google.com | C - CARE | C - CARE An app that makes every person a COVID warrior. | ['Anup Paikaray', 'Arnab Paikaray'] | ['Track Winner: Health and Medicine'] | ['android-studio', 'geofence', 'google-maps', 'java', 'sqlite'] | 44 |
10,277 | https://devpost.com/software/coronanalaysis | . | . | . | [] | [] | [] | 45 |
10,277 | https://devpost.com/software/laser-w6x8vz | Charging
2 charges
Join room at top
Inspiration
I was inspired by the hand game shotgun, and I wanted to make a similar, online game that was more fun and can be played with your friends even with lockdown.
What it does
There are 4 moves: charge, beam, forcefield, and atomic.
You start with 0 charges, and charge lets you gain a charge
Beam makes you lose a charge and lets you attack another user
Forcefield blocks against beam and costs 0 charges
Atomic costs 6 charges and defeats everybody
The game is turnbased, so you cannot see what the others do until everyone moves. Once everyone moves, there are animations that show what happened.
How I built it
I used AWS AppSync in conjunction with web sockets, DynamoDB, and GraphQL to allow users to see the actions and moves other users in the room took and I used antd for react animations on a canvas. The website scales because it can support any number of users in the same room. There would just be more users that appear around the circle. The bold user is you and the names of everyone are under their sprites.
Challenges I ran into
Making animations that correspond to where each user is was difficult. For example, if you shoot someone else the bullet has to be angles towards the other person and go towards them. I had to use a lot of math to calculate the paths.
Accomplishments that I'm proud of
This was a game that I wanted to create for a long time, so I feel very accomplished that I finally had the skills to do so and that it looks better than I thought it wood.
What I learned
I learned how to make cool react animations and how to make the paths to do so.
What's next for Laser
I will add an instructions page and perhaps more moves so that the users have more options to choose from when they move. I also want to get a different domain (like lasergun.io) so that its not hosted on my domain and more people would use it.
Built With
api-gateway
appsync
dynamodb
graphql
lambda
react
redux
route53
s3
serverless
websockets
Try it out
github.com
lasergun.rampotham.com | Laser | Laser is a fun, online multiplayer game that can be played with any number of people. Simply join the same room name to get started! | ['ram potham'] | [] | ['api-gateway', 'appsync', 'dynamodb', 'graphql', 'lambda', 'react', 'redux', 'route53', 's3', 'serverless', 'websockets'] | 46 |
10,277 | https://devpost.com/software/again-vui0w1 | Inspiration
Few days before the start of the quarantine in Morocco, we were walking down the street and we saw a homeless guy trying to find food. Going back home, we were wondering what can this guy do if the quarantine gets imposed on us, Moroccans. A few days later, that was exactly what happened: we were quarantined. Thinking about that guy we saw the other day, we started brainstorming solutions that we can build as computer science passionates to make him and many others in the same situation as he finds a shelter especially during this tough time when they can be easily infected by the virus, as likely as easily spreading it. After seeing Covidathon, we believed that this is our chance to make our solution reach more people and to take the first step in making an impact.
What it does
Again is a solution that aims at securing shelter for homeless people during the lockdown by matching associations and organizations that deal with homeless people and house donators.
The solution also creates jobs for people who have lost their jobs by being applications' reviewers (more details about this below).
To secure shelter for homeless people, the application allows users to create accounts as an association, a house owner, or an applications' reviewer. All of the different types of users enter useful information about themselves when registering (details about the registration information required from each type can be found on the demo site):
As a house owner: anyone who possesses a house or multiple houses can donate them via the application by filling a house donating application. The application asks for information about the house/s that the user would like to donate. This information includes the location of the house, the area, but most importantly a document proving that the user owns that house. The purpose of this proof is to reduce the wasted time after matching an association with a user that does not really possess the house. This proof document will be processed by an AI system that will either validate it or not. If the document is validated, it will be available to applications' reviewers to match it with an association. If not, the donor’s application will be withdrawn. After the donated houses have been matched with an association or more associations (if there are many houses that a lot of associations can use), the contact of the donor is given to the associations so that they coordinate to finalize the donation process.
As an association: after registering in the application, associations can submit applications asking for matching with a donor. An approximate number of homeless people who will benefit from the donation should be specified in the application. It is then the job of applications' reviewers to review the application and decide on a match with a donor.
As an application reviewer: applications’ reviewers are people recruited through the application in order to review the associations’ applications and match them to house/s donors. To be an applications' reviewer, one must apply to the job through the website (applications are available in case of need when the amount of applications is too much). Applicants must provide their personal information, but most importantly, proof of losing their job because of the pandemic. This proof can be of any kind: a screenshot of an email of firing (the email should be forwarded later to make sure it comes from a recruiter, a document..). This proof of losing a job, plus the first-come, first-served basis, and the description of the need in the application are the factors that the admins are going to rely on when assessing applications. Each applications' reviewer will get associations’ applications on a weekly basis. Their job is to assess the need for associations and match them with house donors in the same locations. They also have to distribute the houses in an optimal way taking the need and the impact into consideration. Applications reviewers get paid from donations to the web application. These donations have nothing to do with the house/s donations, they are monetary donations that can be done through the web application to a specific bank account for this purpose. Anyone can donate including people not registered under any type in the application. More on how application reviewers get paid in the section below.
Payment Policy
Applications reviewers will get paid from donations. Since donations are uncontrollable, our team came up with an adequate solution. Applications reviewers will get a token for each application reviewed and thus an association matched with a donor. The value of a token changes on a weekly basis depending on the donations received. Here is a hypothetical scenario: we have 3 applications' reviewers who have reviewed 10 applications each, this means that each applicant has earned 10 tokens, making 30 tokens in total. The amount of donations received in this week is 300 $, implying that a token is worth 10 $. In this case, each reviewer will receive 100$ for this week. However, this method is not good if the amount of donations for a certain week is very high, let’s suppose that in the same previous scenario, the amount of donations is 30000 $, then a token will be worth 1000$. This also means that an applicant will earn 10000 $ for a single week. This might be not fair for other applicants who will join in the coming weeks, and when the donations will be very much lower. To solve this problem, we decided on having a maximum amount that a token cannot exceed so that if the amount of donations is high, we save it for later weeks.
Going back to our scenario, if we set the maximum worth of a token to be 20$, and having 30 tokens to issue, we will spend 600 $ and save 29400$ for upcoming weeks.
Important notes:
Before associations submit their applications, they have to agree to some terms and conditions. An important condition is that the associations should engage the beneficiaries in society by making them help either by doing a job, volunteering or helping other homeless people. The goal of the application is not only to find shelter for these people but to try to engage them in society especially during these tough times when we all have to unite.
Link to the document about using AI in Again:
[
https://docs.google.com/document/d/1RNNpGf3MIhp-lksVtGzXkH7Tb91Ilw4gRw7AJmu27bA/edit?usp=sharing
]
How we built it
To build our web app again, we (team members) divided the work into three parts:
The front-end part (Mohamed Moumou): This part consisted of designing each web page in the web app. The story of AGAIN and all the scripts in the web app. Also, building the actual web app front end using the react framework.
The back-end part (Ouissal Moumou): This part consisted of designing the database and building the actual back-end of our web app using the express.js framework, MongoDB(for the database), and APIs.
Deployment (Ouissal Moumou & Mohamed Moumou): We used Heroku to deploy either the back-end and the front-end app.
Accomplishments that we're proud of
The team of Again is very proud that he is thinking about homeless people when everyone is thinking about the problems of the homeful ones. It does not mean that homeful people’s problems are not urgent, but it means that there is a huge part of society that struggled and now struggling more because of the COVID-19 outbreak that needs urgent help and re-integration. Another accomplishment we are proud of is that our idea is providing jobs for people losing their jobs.
What's next for Again
1- Implementing AI solutions in our App,
2- Adapting the services offered by the app to every country's laws,
3- Make our web app available in many languages (Arabic, French...).
Helpful hints about running the application in our demo site:
http://againproject.herokuapp.com/
If the page returns an error message from Heroku, just refresh the page and it will work.
Here are some login credentials for quick testing of the application:
For an association: **
email:
tasnimelfallah@gmail.com
password: Tasnim123
*
For a house/s donator: *
email:
mohamedjalil@gmail.com
password: yay yay
*
For an application reviewer: *
email:
badr@again.com
password: Badr123
**The information and metrics shown on our app are fictional.
Built With
heroku
javascript
mongodb
node.js
react
rest-apis
uikits
Try it out
againproject.herokuapp.com
againbackend.herokuapp.com
github.com
github.com
docs.google.com | Again | Again is a solution that aims at securing a shelter for homeless people during the lockdown by matching associations and organizations that deal with homeless people and house donators. | ['Mohamed MOUMOU', 'Ouissal Moumou'] | ['The Wolfram Award'] | ['heroku', 'javascript', 'mongodb', 'node.js', 'react', 'rest-apis', 'uikits'] | 47 |
10,277 | https://devpost.com/software/ez-eats | EZ eats app UI
EZ eats logo
EZ eats website
GitHub, Framer, and Presentation Link down below!!
Inspiration
We were inspired to create EZ eats after seeing and researching how much food is wasted in the world. Especially with our current situation, restaurants are wasting more and more unused food and losing money at the same time. This accounts for about ⅓ of the world’s food production which is wasted and goes to show how much can be done if we knew how to distribute it properly since it is still perfectly good food, it just hasn't been sold.
This not only contributes to growing food wastage numbers but also takes away from the economy which is already tremendously suffering. Restaurants are losing tremendous amounts of money as not as many customers are going to restaurants these days.
The major food wastage problem and the economy sailing into a colossal storm, due to the pandemic, inspired us to create EZ eats!
What it does
EZ eats connects users to restaurants in their area which have perfectly good unused food after hours that they would normally have to throw out. Users can order food from their favorite restaurants based on availability through our app and pick it up accordingly. The app will connect users with restaurants of their preferred cuisines and they can see which restaurants have leftover food daily, allowing them to purchase whatever they want while being at a cheaper price than the normal selling price. Since the food is being sold after hours, the price is reduced anywhere from 30-70 percent so the restaurants are still making money instead of losing it by throwing the food away, and users can buy good food at a cheaper price. This helps the problem of food waste and the economy at the same time.
How we built it
We made a website using HTML for EZ eats. We began by writing a simple code asking the user to input their contact information in order to receive updates about the steps that EZ eats will take moving forward. We also inserted logos and social media links where people can find out more about the app when it goes up and running. The website will update with new developments for EZ eats and will periodically send information to users who have signed up with their emails. In the future, this website will allow for more people to learn about EZ eats and its purpose; we are aiming to bring awareness to food wastage and how we can act upon it with the creation of this app.
We also created a functioning prototype on Framer which showcases the UI for the EZ eats app. We made all the screens for the app’s UI and then proceeded to link the buttons to their respective pages, allowing for a perfectly working prototype which can then be used as a model for the real app when created.
Challenges we ran into
Some challenges we ran into were agreeing on an idea as well as what we were going to do in order to execute it. We first started off by brainstorming ideas and then coming together in order to decide, which did take a considerable amount of back and forth. We then took some time to decide how we were going to turn the idea into a reality. These challenges overall helped us create a solid plan as to what we were going to do and how we were going to go about doing it, allowing for us to have a very smooth experience when actually working on a bulk of the project.
Other problems we faced were coding the website through HTML. We are both beginner level HTML coders, so a majority of our time was focussed on developing the website. We learned a lot along the process, ultimately, the long process was worth it.
Accomplishments that we're proud of
We are proud that we were able to create a website and a working prototype in the allotted time and that we were able to work together so seamlessly in order to create the best product we could. The website shows that the app is currently in progress and allows any interested people to sign up whenever they want to receive updates. This prototype allows us to see a true vision of what this app will be as well as its functionality.
What we learned
We learned how to make an idea into reality in a short amount of time by making a functioning prototype and website. We also learned the nuances of creating a website like the code and purchasing the domain so the idea could truly be ours. We also became more able to manage our time very efficiently and make an idea into reality. Let’s modernize our world and eat for less!
What's next for EZ eats
We hope that people truly see the vision of EZ eats and how it is aiming not only to help the environment but the economy as well. We plan to continue by doing some more in-depth market analysis and advertising it online and in-person in order to stir up interest. The more people who know about this problem and use this app to make a step forward, the more that we can curb the problem of food wastage and the effects this is taking on restaurants and the economy. This app is all about making a difference and this could be the first step to making it happen. Let’s modernize our world and eat for less!
Built With
framer
html
Try it out
github.com
framer.com
docs.google.com | EZ eats | Let's modernize our world and eat for less. | ['Mihika Bhatnagar', 'Annika Desai'] | [] | ['framer', 'html'] | 48 |
10,277 | https://devpost.com/software/real-time-emotion-recognition | Web Application
Desktop Application
Angry
Disgust
Fear
Happy
Neutral
Sad
Surprise
Inspiration
The identification system has undergone great development since its invention. Related techniques are widely utilized and have many applications, such as the robot obstacle avoidance, the robotic arm system learning from human demonstrations, the recognition of handwritten characters, the classification of cats and dogs, the classification of flowers, etc.
Emotion recognition plays a significant role in recognizing one’s effect and in turn, helps in building meaningful and responsive
Human-Computer Interface (HCI)
,
ATM Security
,
Lie Detection
,
Face Detection in Interviews
, etc.
What it does
This Project takes Real-Time images (i.e. from user web-camera) and predicts its emotion simultaneously. It gives seven basic emotion (Happy, Angry, Sad, Fear, Disgust, Surprise and Neutral).
How we built it
Built using the Python programming language.
Algorithm for the model is Convolutional Neural Networks (CNNs).
For Web Application: Flask is used and Desktop Application: PyQt5 is used, both are python based frameworks.
Challenges we ran into
The Challenge to build-up this project was to have better accuracy of the CNN model.
Accomplishments that we're proud of
Got Accuracy up to 91%. Accuracy is increased due to Google Colab Platform that provides inbuilt GPU and CUDA features.
What we learned
Convolutional Neural Networks (CNNs)
Flask
PyQt5.
What's next for Real-Time-Emotion-Recognition
The future scope of this project:
Can Predicts
Depression Level
using Emotion Recognition.
In the future, input for the model will be 3D format so, this project can be used for 3D input images.
Instructions
Already CNN model is trained. Just need to run Emotion_Recognition.py (Desktop Application) and app.py (Web Application).
Built With
convolutional-neural-network
css
flask
google-colab
html
jupyter-notebook
pyqt5
python
Try it out
github.com | Real-Time-Emotion-Recognition | A system that predicts or recognize seven basic human emotions (Happy, Angry, Sad, Fear, Disgust, Surprise and Neutral). For user convenience Web-App and Desktop-App is developed. | ['Vishal Parandwal', 'TAPAN MEHTA'] | [] | ['convolutional-neural-network', 'css', 'flask', 'google-colab', 'html', 'jupyter-notebook', 'pyqt5', 'python'] | 49 |
10,277 | https://devpost.com/software/covidaccountable | Inspiration
According to
Fortune
magazine, most Paycheck Protection Program loan recipients remain unnamed. As the global economy enters into a recession, we must restore democratic oversight over how this stimulus money is used. Thanks to the work at
Accountable.US
as they have pored over SEC filings to elucidate where American taxpayers' have gone, we have created a Chrome Extension that will help people around the world judge whether companies that received PPP bailouts really deserve their patronage.
What it does
CovidAccountable
looks through a webpage and searches for company names that match that received
PPP funding
. Company names that have a hit in this database get highlighted where the user can learn about how much the company has reaped from the PPP.
How we built it
COVIDAccountable runs on Google Chrome. We wrote a custom script that uses regex to read through a webpage DOM and identify the names of corporations that received COVID-19 funding. The tooltip that occurs over the word when generated uses the tipped tooltip library (
https://www.tippedjs.com
). Corporation data is sourced from Accountable.us data on Trump bailout (
https://www.trumpbailouts.org/small-businesses/?fbclid=IwAR3wjOLPg8FgoDRcoDY9sB5_S4l1RM-yb-WqoGWPnb-oZGf6JzAGszfQ744
)
Challenges we ran into
Finding PPP lender Information
We thank
Accountable.US
for their work in amassing this research together as without it, this project would not have been possible. However, even finding this information was difficult. As such, the importance of this project is of even more importance as we must hold our government accountable to ensuring fair access to PPP funds.
UI/UX Design
Computer Science curricula are much more focused on theory than on the latest of user interface. Consequently, it took quite some experimentation and research to get a good library working. Hans had prior experience with the
Tooltipster
library, but we eventually went for the
Tipped
library instead.
Accomplishments that we're proud of
As we approach an election year, it is extremely important that we understand how our government has managed the COVID-19 pandemic, both in epidemiological management and in economic support for the general population. As this government has obscured efforts to understand how PPP money has been used, we're proud of our steps to unveil this thus-opaque process.
What we learned
Chrome Extension development
UI with the Tipped library
What's next for CovidAccountable
We hope to train name-entity recognition models that will be able to distinguish company names from other names, e.g. suppose a company were called Ananas, we would want to pick up the company name Ananas, but not pineapples on Wikipedia.
Built With
chrome
javascript
jquery
tooltip
Try it out
github.com | CovidAccountable | Chrome extension that identifies businesses that benefited from the 2020 Paycheck Protection Program. COVID mitigation incompetency is no excuse for lack of economic accountability! | ['Allen Mao', 'Hans Gundlach'] | ['Overall Best'] | ['chrome', 'javascript', 'jquery', 'tooltip'] | 50 |
10,277 | https://devpost.com/software/covid19-kit | dashboard
please check video for the features of the app
booking an appointment with the proctor/ faculty
project and document submission
creating channels for online teaching and mentorship
please check the mentioned github repo for the App. This app is for caretakers of patients with serebral pasly and people on wheelchais.
body temperature, heart rate, alarm functionality with data stored in the cloud database.
dues and assignments
messaging services
online proctored tests
Inspiration
During online classes, many students verbally harass the teachers and students of the class. This spoils the whole environment of the class, So we decided to block these students using speech recognition technology.
Then we all must have seen that delivering the things without contact has become a major problem, therefore we designed a hand gesture moving messenger who deliver things to Covid19 infected people in care centers.
What it does
The first part is a
remote education
android app which resolves all the problems stated above. It contains all the features a student will want in his/her app. We tried to involve every activity that we use to do in offline college times in this App. It consists of
Video call functionality
with a special feature of blocking students who are speaking abusive or bad words during a live session. The student will be reported to the admin of the app and all the records of the blocked student will be sent to the admin app. Admin can unblock the student again. Then our app contains a
chat room
for each classroom a student is enrolled in, it will allow the students and teachers to communicate as they use to do in Offline College. Then comes the appointment feature. Before contacting any teacher we have to make an appointment with him/her to ask for their time. So our App includes this cool feature of
appointment
for the students. This reduces the chaos and brings the working thing so that follows proper protocol. Teachers wanted an invigilation system to invigilate students during the test. In our App, we provided this feature by
camera proctored examination
feature. Under this a teacher can proctor all students through their webcams while the students are giving tests, also the teacher can pass their voice in the whole class to
convey messages
during tests. Also, our app has a feature of
assignment submission
. The teachers can upload the assignment questions along with the due date and students on the other hand can upload the solutions of these tests on the app itself.
How I built it
We used the android studio to build a remote education app. For backend, we used firebase realtime database. For identification of abusive words we used IBM speech to text services to convert the speech of the students in text and then we used this text in the loop to find whether he is abusing or not. We took the dataset of abusive words from Kaggle and gitHub.
For our IoT bot, we used the hand gesture sensor and on the basis of the gesture, the robocare bot will move and deliver thing to patients. It can also be used as a wheelchair.
Challenges I ran into
We faced many challenges like detecting and blocking students who speak the abusive language during the live class. We wanted to make something that everyone can relate with offline college activities. Therefore, we need proper planning and structure. The assignment section needed a proper structure to be executed.
Teachers all over the globe wanted a platform for cheat-proof examination. Our challenge was to make a cam proctored examination with cheat-proof features like on leaving the test you can not re-enter it.
Accomplishments that I'm proud of
We are proud of our abusive language detector system which blocks users when they speak bad words. Also, the structure we made is highly related to offline day to day activities. Our cam proctored test system is awesome, and it restricts the user from cheating and helps the invigilator to invigilate during a test.
What I learned
We learned, how to work with the realtime database, how to use IBM's speech to text services to detect abusive words. In this pandemic situation, we learned the complete use of GitHub and how to collaborate our work with teammates. Also, we learned some new IoT features which helped us to make the robocare bot.
What's next for Covid19 Kit
For future aspects we are planning to make a complete, general messenger system for private and government offices which they can use to share files, letters, assigning task and doing all other stuffs which people do in offline office hours.
Built With
android-studio
arduino
e-learning
education.com
firebase
ibm-watson
iot
Try it out
github.com
drive.google.com
drive.google.com | Covid19 Kit | An android app, an IoT device, and a Covid19 tracker, a complete kit for students, doctors, patients, and common people. An IoT bot to follow social distancing practices. | ['Ayush Sharma', 'Elio Jordan Lopes', 'Shaolin Kataria', 'Ritik Gupta', 'DEVANSH MEHTA'] | ['The Wolfram Award'] | ['android-studio', 'arduino', 'e-learning', 'education.com', 'firebase', 'ibm-watson', 'iot'] | 51 |
10,277 | https://devpost.com/software/lockdown-covid19 | Inspiration
The pandemic indiced me to make a cool game during the lockdown
What it does
In this game based effect, you have to dodge all coronoviruses you encounter and may your own way out of the havoc caused by the pandemic. This effect is based on a face tracker where you have to tilt your head from side to side to control the movement of the bike. Also make sure you don't stay outside the road for 3 seconds or more. Everybody is bored during the lockdown. So this cool filter is one way you could engage in some fun avtivity adn battle the viruses. ENJOY!!!
How I built it
Gameplay Patch:
The gameplay patch is the main patch for simulating the gameplay. It contains the road animation, moving objects and character animation patches. The road animation is used to simulate a running vehicle on a road. It contains about 45 frames of road images which are extracted from a gif found online and are simulated using the Loop animation and transition patches connected to the current frame of the road. The start and end values run from 0-45.
The character animation patch is used to control the movements of the character as he moves his way on the road. Here I have used a face finder, face select, face tracker patches in my graph to capture the face of the user and control the character position as the user tilts his/her head side to side. Here I have used a -1 multiplier to turn the character laterally in the direction of the users head during the tilting action. The patches used here are the character position, 3D head (face mesh) rotation and character 3D rotation which are all synchronised with the face tracker.
The character animation also controls besides users movement, that the user shouldn’t cross the width of the road for more than three seconds, the violation of which kills the user by indicating game over.
The moving objects patch contols the On/Off, duration and reset parameters of various colliding objects in our interaction. Some of the interacting objects include coronaviruses, trees, street and the cityscape during the night. Some occur on the ground and some in the air.
Challenges I ran into
I had to overcome various challenges like placing and moving the charcter in the 3D space. simulating the road animations, increasing the speed of the gameplay, making the colliding objects appear at randoim intervals of time and of course making the animations and assets, reactive scripting and optimising the effect to be compatible with the instagram platform.
Accomplishments that I'm proud of
I am proud that I was able to set the right targets and achieve them. I got to the opportunity to learn to make amazing effects using sparkAR and understand how it can be used to promote a message and engage audiences. I improved my understanding of the 3D geometry and coordinate space.
What I learned
I learned various features and functionalities of SparkAR and its scripting using reactive programming and also 3D model creations using blender and animations with sparkAR.
What's next for Lockdown-Covid19
I would like to involve a blinking feature to enable the bike to jump over obstacles and also increase the frequency of the obstacles in the effect when the user opens his/her mouth indicating danger and add more music effects and better assets to improve the reach.
Built With
graph
javascript
patch
sparkar
Try it out
www.instagram.com
github.com | Spooky-Covid19 - An augmented reality based game effect | In this game based effect, you have to dodge all coronoviruses you encounter and help the masked user make his way out of the mess on his bike . This effect is controlled using the face tracker module | ['Elio Jordan Lopes'] | [] | ['graph', 'javascript', 'patch', 'sparkar'] | 52 |
10,277 | https://devpost.com/software/thinkpos | Home Page
View Quotes
Add a Quote
Inspiration
With all the negativity being spread around in the online world, we [3 rising seniors in high school] wanted to find a solution that changes this narrative.
So, we decided to create a platform where people can spread positivity by submitting personal quotes on different topics.
Whether it is an educational, comedic, or even a interesting quote, you never know who may benefit from reading these unique statements from people coming from all walks of life. We want to provide a safe space for people to share their opinions and ideas on certain subjects without being criticized for the belief that they have.
Our goal for this project is to create a website that will leave a lasting impact on society.
What it does
ThinkPos provides people with a platform to spread positivity through personal quotes
. We provide a user-friendly platform where unique individuals can share their beliefs, ideas, and opinions on all kinds of issues that are prevalent in our lives today.
How we built it
Using
MySQL
and
Node.js
, we created a backend that stores all the quotes being written by people, along with their name and where they're from. We also created a detailed and personal frontend using
Javascript, HTML5, CSS, and Bootstrap.
*
Overall, we spent 8 hours creating this project and deployed it using Heroku. *
Challenges we ran into
We struggled to properly format the quotes and dynamically add them to the website as they were being created by the user. Along with this, we struggled with storing and retrieving the quotes from the SQL database.
Accomplishments that we're proud of
We were able to create a simple and intuitive interface to allow the users to view and write quotes with ease. We also successfully integrated the database with the frontend quotes display.
What we learned
We learned how to collaborate as a team in order to develop both ends of the website smoothly.
What's next for ThinkPos
We plan on deploying and publishing ThinkPos in order to allow people from around the world to use this platform frequently.
Built With
bootstrap
css3
html5
javascript
node.js
sql
Try it out
www.thinkpos.us
github.com | ThinkPos | Creating a positive change in the world through the power of quotes. | ['Skyler Gao', 'Ashay Parikh', 'Abhi Nayak'] | [] | ['bootstrap', 'css3', 'html5', 'javascript', 'node.js', 'sql'] | 53 |
10,277 | https://devpost.com/software/remote-elderly-home-care-via-privacy-preserving-surveillance-6etr18 | Privacy preserving face detection at home
Plug and Play AI Device Discovery
Ambianic Home Page
Person Detection Indoors
Person Detection Outdoors
Inspiration
COVID19 isolated at home many of us, including our elderly parents and grandparents. Not being able to check on them regularly elevates the risks that they are exposed to such as falls, gas leaks, flooding, fire and others.
What it does
Ambianic.ai is an end-to-end Open Source Ambient Intelligence project that removes the stigma associated with surveillance systems by implementing privacy preserving algorithms in three critical layers:
Peer-to-Peer Remote access
Local device AI inference and training
Local data storage
Ambianic.ai observes a target environment and alerts users for events of interest. Data us only available to homeowners and their family. User data is never sent to any third party cloud servers.
Here is a blog post that goes into the reasons why we started this project:
https://blog.ambianic.ai/2020/02/05/pnp.html
And here is a technical deep dive article published in WebRTCHacks. It clarifies that it is absolutely possible to build a privacy preserving surveillance system, despite popular cloud vendors making us believe that all user data belongs safely on their cloud servers:
https://webrtchacks.com/private-home-surveillance-with-the-webrtc-datachannel/
How we built it
Ambianic.ai has 3 main components:
Ambianic.ai Edge: a Python application designed to run on an IoT Edge device such as a Raspberry Pi or a NUC. It attaches to video cameras and other sensors to gather input. It then runs inference pipelines using AI models that detect events of interest such as objects, people and other triggers.
Ambianic.ai UI: A Progressive Web App written in Javascript using Vue.js and other front end frameworks to deliver an intuitive timeline of events to the end user.
Ambianic.ai PnP: A plug-and-play framework that allows Ambianic UI and Ambianic Edge to discover each other seamlessly and communicate over secure peer-to-peer protocol using WebRTC APIs.
Challenges we ran into
Challenges include selecting high performance, high accuracy and low latency AI models to detect events of interest on resource constraint edge devices.
Another challenge is taking into account user local data to fine tune AI models. Pre-trained models can perform reasonably well, but they can be improved with privacy preserving federated learning on unique new local data.
Accomplishments that we're proud of
Ambianic.ai has been in public Beta for several weeks helping a number of users in their daily lives. Some users report success in keeping an eye on their elderly family members:
https://twitter.com/mchapman671/status/1230931722650423299
What we learned
Although the project sets ambitious goals, there seem to be sufficient enabling Open Source frameworks and community momentum to drive the ongoing success.
What's next for Remote Elderly Home Care via Privacy Preserving Surveillance
We need to work on these major areas:
Recruit volunteers in the home care community to test the system and provide feedback
Select more models to address open use cases such as fall detection, gas leaks and others
Work on implementing Federated Learning infrastructure to fine tune initial pre-trained models.
Built With
javascript
pwa
python
raspberry-pi
tensorflow
webrtc
Try it out
docs.ambianic.ai | Remote Elderly Home Care via Privacy Preserving Surveillance | COVID19 isolated at home many of us, including our elderly family members. Left unattended they are prone to risks such as falls, gas leaks, flooding, fire and others. | ['Yana Vasileva', 'Björn Kristensson Alfsson', 'Ivelin Ivanov'] | [] | ['javascript', 'pwa', 'python', 'raspberry-pi', 'tensorflow', 'webrtc'] | 54 |
10,277 | https://devpost.com/software/ai-voice-assistant | Inspiration
The inspiration was always to learn new technology.
What it does
It is a voice assistant powered by wit.ai. The users can use a voice interface to ask the assistant very basic things like time and date to information about anything, play songs, personalized jokes, browser automation, COVID related data etc
How I built it
The main languages I used was javaScript and python. The UI was done in electron js and the backend with wit.ai integration was done with python3. I used a library called Eel to connect my python code to js .
Challenges I ran into
The challenges I ran into was lack of time, so I could not add all the features that Il wished to include.
Accomplishments that I'm proud of
In spite of the lack of time and resources, I managed to complete the project
What I learned
I got to learn wit.ai a very powerful tool for NLP related projects.
What's next for AI-Voice assistant
The next features that I like to include are complete home automation using my assistant
Built With
eel
electron
javascript
python
wit.ai
Try it out
github.com | AI-Voice assistant | This is a personal voice assistant built with Wit.ai platform with a voice interface. The users can ask, information about anything, to play songs, to send an email, computer hardware status etc. | ['Abhinav Tharamel Baiju'] | [] | ['eel', 'electron', 'javascript', 'python', 'wit.ai'] | 55 |
10,277 | https://devpost.com/software/virtuquiz | Thousands of videos, understand your lessons clearly.
Inspiration
There are so many students around the world who are weak at studies. Many children don't like the traditional learning or the e-learning method.
Although there are many learning apps, there are some features that I thought of that no other app has. Including all these features I wanted to create a learning app, and thus Virtuquiz, which is not limited to quizzes, was born....
What it does
Virtuquiz is a learning app which anyone can download on their mobile phone and start to learn. This app is recommended to students of grades 6-12, but other grades will be added sooner.
Virtuquiz has 2 main sections, one is learning and the other is quizzes.
Leaning Section
The learning section features 3 sub-categories which include videos, a homework checker and an extra knowledge bot.
Videos
There are thousands of videos under different topics which you can refer to. The video section consists videos from an online school 'Khan Academy.' Watching videos here is simple. Scroll down on the topic list, select the topic, then select a video and watch it. All videos are in English.
Homework Checker
This is a feature where anyone can submit there homework for a re-check before submitting it to a teacher. You can either send a picture or document. Then we will re-check it with automated systems as well as manual systems and send whether the work is correct or point out the mistakes and analyze them. We have clearly said that no one can use this feature for cheating.
Extra Knowledge Bot
This bot which is called as the Virtubot can be used for learning good qualities and learning about the society. This is also an essential part which education systems have missed out today. The Virtubut is still under development, it only has 3 questions yet. Using it is simple, the bot asks questions; for example how will you handle a situation where your friend is scolding you for what you didn't do.
There will be some options of what you can do. You will have to chose the wisest solution. You will be judged and given feedback (You are rude, or , very good you are generous).
Quizzes
After you have learned using the video feature you can check your knowledge using the quizzes. There are 20 quizzes with 10 questions each at the moment, more will be added too. Quizzes are under 5 main topics. (Science, History, Technology etc.)
Answering questions in quizzes is simple, all the questions are multiple choice questions, you just how to select the answer and press next. Finally after finishing all the 10 questions you will get a report on your performance. The pass mark for all quizzes is 70%.
How I built it
The Virtuquiz app was built using different app building platforms, the questions were built created by me with the help of online articles. The video feature was added in collaboration with Khan Academy Videos. The Virtubot was built using the virtual bot creator. The app was finally compiled using Android-Studio.
Challenges I ran into
There were many challenges.
The first was finding videos, I couldn't do all the videos myself. But finally I found a Khan academy feature which allows you to add the videos which belongs to them.
Another challenge was creating quizzes, I had to make 200 questions and add different answers. This was all done within 12 hours..
Also the Virtubot was difficult to create. I failed in creating the bot and integrating it successfully at the beginning, but later I was successful.
Accomplishments that I'm proud of
I am proud of adding a bot which is a unique feature and also a feature that plays a role in social-good.
Also I am proud of successfully creating this app.
What I learned
While building my app, I had to read many educational articles, I gained a lot of education through this. Also this was one of the most difficult apps I built, it really taught me a lot about programming etc.
What's next for Virtuquiz
I have to let people know about my app, although it's good and working many doesn't know that something like this exists. So, I need to promote.
Also I will have to develop this app more in the future.
Built With
android-studio
appsgeyser
appy-pie
gimp
Try it out
github.com
play.google.com | Virtuquiz | The Ultimate Learning App, quizzes, video lessons and even problem solving bots included... | ['Senuka Rathnayake'] | [] | ['android-studio', 'appsgeyser', 'appy-pie', 'gimp'] | 56 |
10,277 | https://devpost.com/software/head-voice-simulator | Inspiration
I was inspired by a youtube comment that suggested the idea.
What it does
It simulates how your voice sounds like.
How I built it
I researched how to record audio and play it back.
Challenges I ran into
I needed to figure out how to
Accomplishments that I'm proud of
It works somewhat well, but it can definitely be improved
What I learned
I learned how to record audio, and also playing it back. Additionally i learned how sound propagates through bones
differently than through the air.
What's next for Head Voice Simulator
Making it more accurate, and perhaps a better ui. Could also become a ios app or web app additioanlly.
Built With
android
android-studio
media-player
Try it out
github.com | AtlasHacks Project | AtlasHacks Project | ['Manu b'] | [] | ['android', 'android-studio', 'media-player'] | 57 |
10,277 | https://devpost.com/software/build-an-blockchain-app | Problems It Resolves
Inspiration
I.Fear of Missing Out’ Blockchain Solutions
2.Opportunistic Solutions
3.3. Trojan Horse Projects
Evolutionary Blockchain Projects
Blockchain-Native Solutions
I built it Using Blockchain to build a blockchain app using Etherium smart contracts . I will learn how to create a todo app with Etherium smart contracts using the Solidity programming language. I will also learn to write tests, deploy to the blockchain, and create a client-side application.
I will learn how to create a todo app with Etherium smart contracts using the Solidity programming language. I will also learn to write tests, deploy to the blockchain, and create a client-side application.
Accomplishments that I will learn how to create a todo app with Etherium smart contracts using the Solidity programming language. I will also learn to write tests, deploy to the blockchain, and create a client-side application.
I learned I will learn how to create a todo app with Etherium smart contracts using the Solidity programming language.
Cryptocurrency Converter In JavaScript .This is my Next Goal Which I am Currently Working On,
Built With
blockchain
django
iot
Try it out
github.com | Build an Blockchain app | A Guide to the Types of Blockchain Projects Ruling the Decentralized Economy By Sudeep Srivastav | ['Situ Dash'] | [] | ['blockchain', 'django', 'iot'] | 58 |
10,280 | https://devpost.com/software/levels-advanced-water-tracking-system | The project in action!
The data gathered on the back end
Inspiration
We wanted to come up with a cheap way to solve floods, droughts, and water quality problems in the most inexpensive yet effective way possible
What it does
Our system logs, records, uploads, and analyzes water data that it gets from its sensors, maps out flood warnings, and makes future predictions about droughts and floods
How I built it
I use Arduino and C# for the physical water checker, and HTML for the website.
Challenges I ran into
Linking the sensors was extremely difficult, and filming some of the shots as well.
Accomplishments that I'm proud of
The cinematics are pretty high quality and the project has a great purpose!
What I learned
We learned how to connect multi-scale sensors in Arduino.
What's next for Levels - Advanced Water Tracking System
We hope to cut down costs and make it as cheap as possible!
Built With
arduino
csharp
html5
Try it out
github.com | Levels - Advanced Water Tracking System | Tracking water levels, purity, and quality in the most inexpensive way possible | ['Timotheus Weigand', 'Bill Bai'] | ['Best Environmental Hack'] | ['arduino', 'csharp', 'html5'] | 0 |
10,280 | https://devpost.com/software/effortless-health-records | The home page
The login page
The patient information input page
Inspiration
Felix and Kirsten both worked at coop placements in the health industry. While working in very different settings, they both experienced one common issue: recording and transferring patient information and health records. While health records and electronic health records have become commonplace in many clinics, physicians seem less-than-inclined to use them due to the copious amount of writing or typing required. This makes sense, as a physician's expertise lies in diagnosing ailments, treating them, and working with patients, and not inputting values into tables or signing paperwork. This doesn't seem like a very large problem until one factors in the consequences of a physician rushing through this information-gathering process to focus on patients. 50 out of 175 million patient accidents were caused by typing errors on medical forms. This is outrageous and is only exacerbated by something like a global pandemic increasing the traffic in hospitals and, consequently, the number of forms physicians must fill out. To fix this major issue, our team decided to create a website that automates the EHR recording process. Drawing from our own experiences, we realized that physicians spend most of their time during check-ups talking to the patient. Instead of talking to the patient and looking down at a tablet to type information, why not just use the information rushing out of their own mouths? Hence, our solution is to use voice-to-speech and an efficient information processing algorithm to store patient information without the need to type a single word!
What it does
Our website has several features. Firstly, users sign in with a username, password, and occupation. Once signed in, users will enter the main page, where they will be directed to 3 links: the patient information form, the prescription form, and a link for contacting us in case they need help using our site.
The patient information form is the main feature of this website, as this is what automates filling out EHRs by hand or by typing information manually. The physician simply has to click "Start Recognition" and allow the site to access their microphone. Then, anything they say will be converted to text by the Web Speech API in our project. Once the physician stops speaking for over 15 seconds or the physician clicks "Pause Recognition," the voice-to-text API will stop receiving input. During pauses of speech, transcripts will appear inside of the main text box. Physicians can correct any mistakes made by the voice-to-text API inside this text box. Once the information is confirmed to be accurate, the physician simply needs to click "Save Information." Our website instantly cuts away the unnecessary words, leaving behind all the important details from the transcript pertaining to the patient by identifying keywords and only saving parts of the transcript surrounding these keywords. This is stored on the webpage with a date and time stamp of when information was saved. Physicians can delete this with a simple button click as well. This process streamlines EHRs tremendously, since physicians can speak with a patient and fill out the patient's EHR at the same time without looking at a screen or typing. Physicians can have all their patient's crucial information saved in as few as 3 button presses.
How we built it
We built this website using HTML, CSS, Javascript, and Web Speech API. The Web Speech API received microphone input and provided us with easy-to-use methods for transcribing vocal input to text. HTML was used for the skeleton of each webpage, CSS was used to style the webpages, and Javascript was used to allow button clicks to trigger actions, to receive vocal input, and to output relevant patient information.
Challenges we ran into
Some challenges we ran into were properly receiving the voice input. We had to read documentation on Web Speech API and access tutorials on the internet about integrating the API into Javascript code. We also ran into issues with styling the website and storing the voice input properly. However, we were able to solve all our problems by researching and finding alternative methods to achieve a similar end result.
Accomplishments that we're proud of
We're quite proud of making an aesthetic website in under 24 hours. We are even prouder of getting the Web Speech API to properly receive vocal input and enter it into the text box. Lavan was quite jovial when he managed to properly filter vocal input into a concise format when saving patient information and stamp it with the date and time. Overall, we are proud of the amount that we were able to achieve considering that most of our group had never worked with web development tools prior to this hackathon. In fact, most of our team had never attended a hackathon prior to this one, so this has been a wonderful experience and a great learning opportunity!
What we learned
We learned how to create a webpage using HTML, how to style elements using CSS, how to create functions triggered by button clicks in Javascript, and how to use an API to convert vocal input into text. Finally, we were able to turn our project into a live demo site using Github Pages! (UPDATE: no longer online)
What's next for Effortless Health Records
With more time, our group plans to complete the prescription form and improve on the storage of patient information using databases, so that patient records can be amended after an initial recording has been saved. We also want to work on security, ensuring that login information is stored safely and not displayed in the web browser link.
Built With
css
html
javascript
webspeechapi
Try it out
github.com | Effortless Health Records | A web app that optimizes recording patient health information | ['Kirsten Lo', 'Alexander Chow', 'Felix Du', 'Lavan Sumanan'] | ['Best Health Hack'] | ['css', 'html', 'javascript', 'webspeechapi'] | 1 |
10,280 | https://devpost.com/software/hack-it-better | Inspiration
We were inspired to create Viral Learning from our experiences with the secondary school hybrid learning model - two subjects, 4 quadmesters, half of the week online learning and the other half in school, each class separated into two cohorts with opposite schedules. We noticed a number of problems from both the teacher and student perspectives that made this learning model particularly difficult:
a)
Teachers are not well equipped with handling online learning due to their lack of familiarity with technology. Students spend too much time studying and can lose track of some important things.
→ Teachers generally aren’t good with technology, which when adding many different new platforms to learn, it is counter productive
→ Increase in summative assignments makes me lose track of where I should be with other courses as I have to spend a lot of time studying
→ Lack of knowledge to be able to create lessons online (video recording, uploading)
→ Lack of community aspect, people will generally stick to the friend groups they have formed already and don’t get chances to socialize with others, many friend groups have been split up because of the 15 person limit
b)
There is a large gap between in-person normal learning and online learning
→ Delay in communication between students and teachers (teachers can be spam emailed)
→ Student to student collaboration is hindered because of social distancing rules and there is no alternate platform that is intuitive for online student to student collaboration
→ Teachers have difficulty planning for two cohorts to be learning at the same pace
→ Classes are much less stimulating online
→ Lack of “class” participation (e.g. just teacher talking or one person responding)
→ No environment to connect with new friends
When we thought about what we could do to solve these problems we were having, we came up with the idea of creating a third party distance learning communication platform - compatible with Google Classroom and Brightspace- for teachers and students. We wanted to make sure to solve the main problems of a)long delays in communication with teachers online and b) enable students to form study groups on a dedicated education communication platform to improve collaboration and productivity.
What it does
Viral Learning is an web-based ticket-response and instant messaging service built with Node.js that allows students to create topic-specific “tickets” to ask questions to their teachers. Students will see all of their classes on the side and clicking on each class shows them their active “tickets” and group chats for that class.
Ticket Creation and Response
Instead of unfocused e-mails, students can now send tickets asking about specific material to teachers. Students can easily keep track of which questions they’ve asked about on their ticket dashboard to prevent duplicate questions. To prevent teachers losing questions due to clutter, each ticket they receive is sorted by class, subject and material. Teachers simply need to open up a class to see, at a glance, every question that’s been asked in that class and even the material that the question refers to, all in one place. This is made possible by sorting each ticket object into various nested keys in the backend (show example). This streamlines the answering process by filtering the messages based on content, preventing teachers from having to continually refer back and forth between different materials for each question. The teacher can also choose to respond to all tickets of one type with one response if he/she feels that their response fits all of the questions. To ensure that tickets are always resolved quickly and not forgotten about, a notification will be sent to the teacher outlining all unanswered tickets that are more than two days old.
Group Chat Creation and Management
Students will also be able to create group chats with their peers to collaborate on projects or ask for help with the help of socket.io. From comparing notes to working on group assignments, these chatrooms not only allow students to get in touch with classmates who they otherwise cannot contact, it also keeps conversations only relevant to them separate from the rest of the chat, both for the comfort of the students in the chat and in order to not disturb the other students in the rest of the class.
How we built it
We first built out a ticketing system with tags for assignment specific questions to teachers. These tickets, as well as their current group chats are displayed on their dashboard. These tickets are organized for the teacher to reply easily by sorting each ticket based on the tags that the student places on the question. This streamlines the answering process by filtering the messages based on content, preventing teachers from having to continually answer the same questions and refer back and forth between different materials for each question. Students can also create study groups with classmates to collaborate, and discuss solutions - this was created using socket.io. The entire platform was built using HTML, CSS, and node.js.
Challenges we ran into
We had a lot of features that we would've wanted to implement but because of the time limit of the hackathon we weren't able to. These features included:
Creating a video lesson tutorial for new users with templates to create video lessons
A productivity dashboard for students - classes, lesson times, work, etc...
A teacher planning dashboard - content, classes, lesson times...
Better visualization for scheduling lessons to keep cohorts in line
Push notifications for teachers (teachers get notified of student q’s and reminded to answer them after a given time frame)
Learning new languages was another challenge that we all worked through and helped each other with. Previously Ben had never coded a website in HTML and CSS before and this was his first project and hackathon, Johnny was unfamiliar with syntax for node.js and using git. Matt also was unfamiliar with syntax for node.js and using git. We had difficulty in coming up with a design for the website since this was a learning process for everyone, there wasn't a lot focus that was able to be dedicated for the UI/UX.
Accomplishments that we're proud of
Being able to push out our MVP and completing our first hackathon! Also proud of ourselves for not relying on any crutches -- everything was coded by us :)
What we learned
We were all able to learn a new language and figure out how to work together well :D
What's next for Viral Learning
We plan on revamping the dashboard for students so that they can plan and see deadlines on a calendar. We also plan on introducing a similar feature to teachers so they can plan for their different classes to progress at the same pace. Furthermore, the filtering system for student questions could be improved by using NLP to assist in grouping questions. Finally we plan on making the software with already existing platforms (Google Classroom, Brightspace) and prettying up the UI/UX.
Built With
html
javascript
scss
Try it out
github.com | Viral Learning | Viral Learning is a distance learning communication platform bridging the student-teacher communication gap using a filtered ticket system and enabling study groups for student-student collaboration. | ['Ben Xu', 'Matt Huang', 'Johnny Qu'] | ['Best Community Hack'] | ['html', 'javascript', 'scss'] | 2 |
10,280 | https://devpost.com/software/dulcis-4kofpn | Dulcis
A revolutionary management app for diabetics
Inspiration
Directly involving people most affected by a problem is often the solution to many issues. With a rapidly rising number of over 3 million Canadians with Diabetes, we decided to create a simple, but revolutionary application for diabetics to stay in control of their condition. Combining the idea of gamification and a virtual assistant is how Dulcis was created.
What it does
Dulcis revolutionizes the way diabetics can keep track of their blood sugar levels through its 3 main features:
Food AI
Using Dulcis you can take a picture of a meal, and upon analyzing the image for food and ingredients, it will return the average glycemic index (essentially sugar content) of the meal, and provide a recommendation of whether or not to eat it.
Drake the Chatbot
Ask Drake any questions you have about diabetes such as:
What is insulin?
Is my blood sugar healthy?
What does type 2 diabetes mean?
Or you can also tell Drake your symptoms such as:
Im feeling faint
My vision is blurry
I’m very thirsty
After some follow up questions, Drake will make a recommendation based on your symptoms to visit a doctor, monitor your symptoms, or if you are good to go.
Try out a demo of Drake the Chatbot here:
https://bot.dialogflow.com/47e40892-d48a-4373-a227-9e9ff2cb77df
.
Blood Sugar Logs
By simply clicking ‘new log’, you can add a new blood sugar log at a certain time in the day by entering your blood sugar level after getting a reading from your device. Dulcis will automatically do some analysis and calculations to provide you with a graph, and average stats.
How we built it
The application was developed using a react native, a universally used JS framework for building cross platform applications for android and ios. We used react native in a combination with Typescript, an open source language which adds strong typing to vanilla JS, and expo, an open source platform for building react native applications. Services such as Firebase (auth and database), Clarifai (ML image classification model), and DialogFlow (chatbot) were also used to create the application.
Next Steps
Dulcis has a lot of potential and room for both improvement and adjustments. The first improvement would be to expand the database of Glycemic Indices through possibly web scrapers to provide the most accurate information. By that same token, the second step would be to incorporate recommendations for healthcare locations near the user when Drake the chatbot detects concerning symptoms from the user. Finally, the most important expansion to the application would be incorporating telemedicine. Especially with Covid-19 restrictions, having doctors on the application itself, having video calls to provide prescriptions for the user based on their data in the application, or chatting with users who feel certain symptoms. Connecting doctors with patients on the application would be a game changing update for Dulcis.
Download Dulcis (android)
Click the link below to download Dulcis on your android device
https://expo.io/artifacts/77a120d3-a633-4eea-bbd5-f965b8cccd59
Services and Dependancies
Services
Firebase
Clarifai
DialogFlow
Packages
react-navigation
react-navigation-tabs
firebase
clarifai
react-navigation-stack
react-native-indicators
react-native-chart-kit
expo-image-picker
expo-camera
react-native-raw-bottom-sheet
react-native-dialogflow
react-native-gifted-chat
react-native-material-menu
Built With
javascript
typescript
Try it out
github.com
expo.io | Dulcis | A revolutionary management app for diabetics | ['eshchock1@gmail.com', 'Eshwara Chock'] | ['Best Video Presentation'] | ['javascript', 'typescript'] | 3 |
10,280 | https://devpost.com/software/urban-apples | The home page for our site
Inspiration
We were inspired to make this site after we noticed so many apple trees that weren't being picked around our neighborhood despite child hunger being an issue. So we decided to do something about it.
What it does
This site lets people post trees that have apples or other fruit on them to let people know that they can be picked from.
How I built it
We built this site using flask and python and it is hosted on pythonanywhere
Built With
flask
html5
python
Try it out
bloxman797.pythonanywhere.com | Urban Apples | A website to find fruit trees in your neighborhood | ['John Chudobiak', 'Raymond Dai'] | ['Most Creative Hack'] | ['flask', 'html5', 'python'] | 4 |
10,280 | https://devpost.com/software/fire-watch-wk6ufv | Inspiration
Currently, wildfires are a growing problem in the United States, and it's even worse around the world. Almost every week we hear about these wildfires getting out of control, and not only does it force people to leave their homes, but it also contributes to 20 percent of greenhouse gas emissions.
What it does
Fire Watch allows users to determine their location's wildfire threat and air quality by entering their locations zip/postal code.
How we built it
The website is composed of three pages, one of which is running javascript. The script allows us to convert the user’s postal code or zip code, to longitude and latitude, and then compute wildfire information based on their location.
Challenges I ran into
Besides the short time frame, we ran into slight issues with implementing API integration, but after a few hours of trial and error, we managed to isolate the point of failure.
Accomplishments that I'm proud of
We really like how the visual aspect of the website turned out.
What I learned
This was the first hackathon for all of us, so it taught us how to effectively work as a team in a time constricted environment.
What's next for Fire Watch
In the future, Firewatch will be able to alarm users through their phones with live updates in case of unexpected emergencies.
Built With
breezometer
css
google-geocoding
html5
javascript
Try it out
18.224.16.60 | Fire Watch | Fire Watch is a website that is capable of detecting wild-fire and air quality threats within a 30 km radius around your location. It updates live to ensure you're safe before it's too late. | ['Himanshu Singh', 'Alexander Tsarapkine', 'LUKA GRAHEK', 'MICHEL BEHNIA'] | ['Most Popular Hack'] | ['breezometer', 'css', 'google-geocoding', 'html5', 'javascript'] | 5 |
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