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 |
|---|---|---|---|---|---|---|---|---|
10,337 | https://devpost.com/software/cognitive-tutor-f2pmgq | A standalone application for students to learn innovatively based on their respective classes and they can test knowledge using take test option in the application that is based on the content they learnt.
Features:
1.Teachers can add content for students to learn and question pattern to take test.
2.Students can go the material which is uploaded by teacher and take test based on the answers badges will be given.
3.Teachers only can add contents where students can read it.
4.Notifications will be sent to teacher if any student is added to their class
5.Students can only see the groups where there are added.
Built With
pega
Try it out
github.com | Cognitive Tutor | A standalone application for students to learn innovatively | ['Durga Ravi', 'Sowmiya Kannappan', 'selva marishwaran'] | [] | ['pega'] | 14 |
10,337 | https://devpost.com/software/educare-a73rxy | We are working on to develop a platform where a candidate will be taking personalized video courses according to their specifics.
Step 1: Onboarding While onboarding the candidate after knowing what course they're interested in, we'll evaluate them based on their current knowledge in that particular domain using an adaptive test (with dynamic difficulty) and will score them on different topics of the course. These scores will help us generate the course content dynamically focusing more on the parts where the candidate is lacking.
Step 2: Personalized course Our engine will generate a personalized video course with dynamic content for the candidate according to their abilities and learning capacity. Also, along with that, we'll be giving links to highly cited articles and official docs for the related topics.
Step 3: Consistent Monitoring and Improvising Course We'll take frequent tests after every bunch of topics and evaluate the candidate's progress and modify the course content on their learnings.
We'll have multiple courses from various teachers as we firmly believe "One teacher doesn't fit for all"
Step 4: Helping through hard times Next, we will be constantly monitoring the user's behavior while they are taking the video course. We will detect if the user is yawning or is away from the screen (i.e indulged in other activities), switching tabs, detecting surrounding noise, etc. to know the user's interest towards a particular material he is studying. If the interest level is down then we will notify him through a notification to skip this part and move to the next topic or continue tomorrow. This will help us to keep user in our platform and study more.
Built With
ar
heroku
javascript
machine-learning
python
react
unity
Try it out
earthhacks-smart-edu.herokuapp.com | EDUCARE | Personalized courses as per student's current knowledge level and learning capacity , Provide support for low bandwidth transmission ! we also have some AR | ['Pulkit Midha', 'rahul garg'] | [] | ['ar', 'heroku', 'javascript', 'machine-learning', 'python', 'react', 'unity'] | 15 |
10,337 | https://devpost.com/software/quizmeet-a-better-online-learning-experience | QuizMeet: A Better Online Learning Experience
A fun new way to learn online
A great tool for teachers
A blast for students
Transform your online classroom today!
Inspiration
I have been a middle school science teacher for 8 years. The pandemic has created challenges for educators and students that we've never experienced before. From an educator's standpoint, we lose the personal and relationship-building aspect of our job that is essential for serving our youth. As a student, it's difficult to engage and interact with your teachers and peers. School is a place for our students to socialize, connect, and grow together. We want our project to streamline the online learning process and improve the virtual classroom experience for both teachers and students.
What it does
QuizMeet is a Chrome Extension that will enhance the virtual classroom experience on Google Meet. The extension allows teachers to create and post multiple-choice questions to all participants within the video meeting. Participants are able to interact directly within Google Meet's interface in real time to answer those questions. This extension will eliminate the need to share screens, open additional tabs, enter class codes, or use additional devices. As a teacher, you will still be able to see your students' video in Sidebar Layout view while seeing your students' responses immediately after each question. For students, this offers an engaging and interactive atmosphere that is often missing in an online setting. They can earn points based on accuracy and speed to climb up the leader board, which is updated after the answer is revealed. This form of competitive educational gaming is extremely popular in the classroom and QuizMeet makes it accessible even during distance learning. This gives them the opportunity for normalcy and social interactions under these extreme circumstances.
How I built it
The concept and design of the project is based on the popular education website Kahoot! The front end portion of QuizMeet is a Chrome extension built with VueJS. The backend is a python flask server behind an nginx reverse proxy, deployed on a GCP virtual machine. Quiz participants are linked together on a cross-origin websocket connection. Quiz questions are currently hard-coded in the backend. We took some ideas from the open source Chrome extension Nod to help scrape user data from Google Meet.
Challenges I ran into
We originally wanted to integrate with the online quiz platform Kahoot!, but Kahoot! doesn’t provide a public API.
Accomplishments that I'm proud of
Smoothly integrating with the Google Meet UI.
Setting up a cross-origin, secure websocket backend.
Asymmetric initialization for teachers and students.
What I learned
The websocket protocol
nginx configuration for SSL and websockets
Using VueJS as a chrome extension
What's next for QuizMeet: A Better Online Learning Experience
The extension is based on the extremely popular education website Kahoot!. Unfortunately their API is not available at this time. If Kahoot! makes their API available, then we can directly integrate it with QuizMeet.
Developing an interface for teachers to create the questions.
Supporting other browsers besides Chrome.
Making QuizMeet compatible with other video conferencing tools like Zoom.
Exploring potential for mobile devices.
Built With
figma
flask
javascript
python
sublime-text
vue.js
Try it out
srblum.github.io | QuizMeet: A Better Online Learning Experience | We allow teachers and students to directly interact within Google Meet’s interface to create a dynamic learning environment. | ['Mo Chen', 'Sean Blum', 'Lei Fu'] | [] | ['figma', 'flask', 'javascript', 'python', 'sublime-text', 'vue.js'] | 16 |
10,337 | https://devpost.com/software/bella-stayhome | Stay Home powered by BEK Service GmbH
Due to the current COVID-19 situation, we stay at home. Use Stay Home especially now to connect yourself with your neighbours, to stay in touch with your social network and get through quarantine healthier. We have decided to provide “Stay Home” free of charge until further notice! Sharing is caring <3
Stay Home is a Real Social Network, in which you can meet and support your neighbourhood and the surrounding areas. Stay Home enables you to bring the advantages of the digital world into the analogue world.
Just imagine: Your neighbour goes shopping and can bring you something. You urgently need flour, because you are going to bake a cake? Or, you need a screwdriver but don't have one by yourself? No problem! With Stay Home, your neighbour is just a click away.
Searching-Radius: Meet people in your surrounding areas has never been closer.
Post your contribution: Need something? Great! Just post it and tell it to your neighbours. You can help? Awesome! Post your contribution and tell the granny in your surrounding areas that you plan to go shopping. You would deserve grandma's kiss!
News: You have an individual concern? Just ask your neighbours.
Easy Login: Use your Facebook- or Xing- Account to get ready within a few seconds.
I'm proud of 200k Users in 1 Week
Built With
android
google-geocoding
google-places
ios
node.js
react
Try it out
stayhome.app.link
bekservice.de | Bella #Stayhome | Stay Home: Neighbourhood hub / Connect with people around you | ['BEK Service GmbH'] | ['The Wolfram Award'] | ['android', 'google-geocoding', 'google-places', 'ios', 'node.js', 'react'] | 17 |
10,337 | https://devpost.com/software/corona-protective-smart-hat | CORONA PROTECTIVE SMART HAT
ART WORK DIAGRAM
We all know that corona virus is a very dangerous virus and we all are worried about it. Corona virus enter human body through eyes nose and moth by our contaminated hand. When we go outside from our home unconsciously we touch our eyes, nose and mouth by our contaminated hand.
The effective module introduced with personal protective intelligent hat. The hat integrated with a small circuit made by hall sensor, resistor, diode, transistor, buzzer, battery and switch. The manual switch is incorporated as per the requirement of on/off of this module. The novel corona virus has capability to enter our body by touching eyes, nose and mouth. This special type of smart hat is based on the working principle of hall sensor and neodymium disc magnet set ring. The hall sensor has ability to detect the magnet within the distance of 3-3.5 cm. The range of this distance will also able to change according to requirement.
When the neodymium set ring get come close to the hall sensor, due to magnetic field a voltage difference create in the hall sensor this voltage difference is also known as hall voltage. From this hall voltage an output current generate in the hall sensor. This output current goes through the resistor, diode and transistor. After activate the base part of the transistor the current flow to the buzzer and make the buzzer active. Sound of the buzzer alert the person from unconsciously touches of eyes, nose and mouth.
This invention claims its importance on the basis of present scenario of world and it is obvious to introduce in new industry sector.
Built With
battery
buzzer
diode
hall
magnet
resistor
sensor
wire | CORONA PROTECTIVE SMART HAT | Reduce the chances of unconsciously touches of eyes, nose and mouth by contaminated hand. | ['Sarthak Chatterjee'] | [] | ['battery', 'buzzer', 'diode', 'hall', 'magnet', 'resistor', 'sensor', 'wire'] | 18 |
10,337 | 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'] | 19 |
10,337 | https://devpost.com/software/my-covidential-diary | Case life cycle
First submission page
Example of the multiple choice questions
Submission for multiple choice questions
End stage
Personalised email sent
Personalised diary entry received by user via their email
My Inspiration
Hello, my name is Jessica Levett.
I have created an application called My Covidential Diary using the PEGA Platform V 8.4.
It's inspired by a woman I have studied and read about for much of my life,
Anne Frank
.
She lived through one of the worlds most traumatic experiences and still wrote and documented her diary.
I wanted to make writing a diary as simple as clicking a button.
So that anyone can document their current experiences.
All entry's are sent personalised to your email and are customised by your answers.
I hope people can find comfort in creating their diary just as others have done before :)
I have entered my application into this
Amazing Hackathon
, in the hope that I can help spread awareness of positive change and using the resources around me avaliable to do so. And to show what girls can do 💪
I wish everyone in the world the best and have a great day!
What it does
It generates a personalised diary entry based on your multiple choice answers to help document your day.
It includes questions inspired by Anne Frank's diary and the types of things she wrote about.
I have also used questions given to me from a few years ago from my councillor which helped me come to terms with how I was feeling at the time.
The language is also not too complicated and provides straight forward answers for those with additional needs.
My younger brother who has severe learning disabilities has trialled the application and submitted his diary entry.
I really tried to make my application suitable and helpful to as many people as possible because writing is an amazing vice for those going through tough times.
How I built it
I built it using PEGA 8.4 in the App and Dev studio.
Challenges I ran into
I wanted to create this application as best as possible in the time frame to ensure functionality.
I'm all about perseverance, pushing through obstacles and finding solutions.
So I'm really happy that I was able to achieve my submitted product.
Accomplishments that I'm proud of
I am proud that it works and that it has already helped some people who have tested it out.
For example I have a teenage sister and offered her to test my app after a stressful day of online exams.
She told me how relieved she felt opening up to herself with the questions and now she has something to show herself in the future about how she has dealt with the current situation.
That really made my day because that was the goal for this application.
What I learned
That I can help people by using my skills with the PEGA system.
What's next for My Covidential Diary
I'm sure once people have grasped the concept they will want to try it, so to make it deployable would be a dream come true. The goal is to help people using PEGA resources and I really do feel that my application does that.
Built With
pega | My Covidential Diary | Document your Covidential Diary with just the click of a button. | ['Jessica Levett'] | [] | ['pega'] | 20 |
10,337 | 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'] | 21 |
10,337 | 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'] | 22 |
10,337 | https://devpost.com/software/neuroscribe | NeuroScribe
Striving for educational equity, one word at a time.
NeuroScribe's Impact
Despite the advancements made, education in the United States and around the world still faces an inequality in the amount of opportunities provided to students. Financial status is still one of the most important factors in the quality of education. Far too many students lack access to a great education.
We have personally experienced this as first and second-generation immigrants whose parents struggled with learning English. With the ongoing COVID-19 pandemic and transition by many schools to distance learning, the inequality will only widen as students get less opportunities to talk to teachers in person. Receiving meaningful direct feedback on writing that’s more than simply spelling is critical to a better understanding of the language and overall success.
Thus, we decided to create NeuroScribe, a free tool that will help address this inequality and help anyone improve their English! Even for those seasoned in the ways of writing, this tool can be used to find that perfect word that was at the tip of your tongue.
AI Integration, How We Built It
NeuroScribe uses a machine learning model to analyze the inputted text, checking whether each word makes sense within the context of the sentence.
More specifically, Neuroscribe uses Natural Language Processing (NLP) with TensorFlow in Python to analyze the text. A bidirectional LSTM (Long Short Term Memory) model then sifts through the input and looks for unreasonable words within the text, as well as suggested corrections.
Next Steps
As next steps, we would like to train the model on a larger or more specific dataset such as business emails to provide more tailored suggestions. We would also like to make the model give more detailed feedback, making it more helpful and furthering our goal of educational equity.
Built With
css
dockerfile
html
javascript
jupyter-notebook
python
Try it out
neuroscribe.cloud
github.com | NeuroScribe | A web app that analyzes your writing using NLP and gives context-aware suggestions. Striving for educational equity, one word at a time. | ['Rohan Bansal', 'Yixuan Qiao', 'Andy Li'] | [] | ['css', 'dockerfile', 'html', 'javascript', 'jupyter-notebook', 'python'] | 23 |
10,337 | 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'] | 24 |
10,337 | 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'] | 25 |
10,337 | https://devpost.com/software/covid-19-ultimate-tracker | s | i | s | [] | [] | [] | 26 |
10,337 | https://devpost.com/software/sistema-de-historico-de-pacientes-publicacao | mapa de telas
Desenvolvemos um projeto para área de saúde pública que visa atender a população mais carente. O projeto trata da gerência dos dados históricos de pacientes. A ideia é desenvolver um Data Lake (um repositório de dados estruturados, semi-estruturados e não-estruturados) que armazene os dados dos pacientes. A vantagem do Data Lake é que é possível associar a dados estruturados (um banco de dados existente), dados não estruturados como imagens de um exame, etc. Além de ser possível aplicar técnicas de aprendizado de máquina sobre esses dados. É um ambiente de integração de dados sem todo o custo de bancos de dados multidimensionais como Data Warehouses e Data Marts. A partir desse Data Lake, o plano é desenvolver um sistema que seja capaz de gerenciar/consultar os dados. Resumidamente um banco de dados atualizado, confiável, seguro e gerenciado com dados e informações pelos pacientes e seus médicos. O fato de usar a tecnologia de Data Lake faz com que esse projeto possa ser utilizado em qualquer lugar do mundo da mesma forma. Finalizando podemos usar a saúde pública nos controles de doenças de forma coordenada mundialmente e ajudar diretamente quem mais precisa nos momentos de pandemia além de poder projetar futuros surtos de doenças através de inteligência artificial e modelos de projeção matemáticos.
Built With
data
flutter
Try it out
xd.adobe.com | Sistema de Historico de Pacientes | Leve sua vida consigo onde for! | ['Jose Alexandro Acha Gomes'] | [] | ['data', 'flutter'] | 27 |
10,337 | https://devpost.com/software/faco-fight-against-corona-jfcza9 | GIF
Confusion matrix for our final model
INSPIRATION
A diagnosis of respiratory disease is one of the most common outcomes of visiting a doctor. Respiratory diseases can be caused by inflammation, bacterial infection or viral infection of the respiratory tract. Diseases caused by inflammation include chronic conditions such as asthma, cystic fibrosis, COVID-19, and chronic obstructive pulmonary disease (COPD). Acute conditions, caused by either bacterial or viral infection, can affect either the upper or lower respiratory tract. Upper respiratory tract infections include common colds while lower respiratory tract infections include diseases such as pneumonia. Other infections include influenza, acute bronchitis, and bronchiolitis. Typically, doctors use stethoscopes to listen to the lungs as the first indication of a respiratory problem. The information available from these sounds is compromised as the sound has to first pass through the chest musculature which muffles high-pitched components of respiratory sounds. In contrast, the lungs are directly connected to the atmosphere during respiratory events such as coughs, heart rate.
PROBLEM STATEMENT
In this difficult time, a lot of people panic if they have signs of any of the symptoms, and they want to visit the doctor.
It isn’t necessary for the patients to always visit the doctor, as they might have a normal fever, cold or other condition that does not require immediate medical care.
The patient who might not have COVID-19 might contract the disease during his visit to the Corona testing booth, or expose others if they are infected.
Most of the diseases related to the respiratory systems can be assessed by the use of a stethoscope, which requires the patient to be physically present with the doctor.
Healthcare access is limited—doctors can only see so many people, and people living in rural areas may have to travel to seek care, potentially exposing others and themselves.
SOLUTION
We provide a point of care diagnostic solutions for tele-health that are easily integrated into existing platforms. We are working on an app to provide instant clinical quality diagnostic tests and management tools directly to consumers and healthcare providers. Our app is based on the premise that cough and breathing sounds carry vital information on the state of the respiratory tract. It is created to diagnose and measure the severity of a wide range of chronic and acute diseases such as corona, pneumonia, asthma, bronchiolitis and chronic obstructive pulmonary disease (COPD) using this insight. These audible sounds, used by our app, contain significantly more information than the sounds picked up by a stethoscope. app approach is automated and removes the need for human interpretation of respiratory sounds, plus user disease can also be detected by measuring heart beat from camera of smartphone.
The application works in the following manner:
User downloads the application from the app store and registers himself/herself.
After creating his/her account, they have to go through a questionnaire describing their symptoms like headache, fever, cough, cold etc.
After the questionnaire, the app records the users’ coughing, speaking, breathing and heart rate in form of video from smartphone.
After recording, the integrated AI system will analyze the sound recording, heart rate comparing it with a large database of respiratory sounds. If it detects any specific pattern inherent to a particular disease in the recording, it will enable the patient to contact a nearby specialist doctor.
The doctor then receives a notification on a counterpart of this app, for doctors. The doctor can view the form, watch the audio recording, and also read the report given by the AI of the application.
The doctor, depending upon the report of the AI, will develop a diagnosis, suggest medicines, or recommend a hospital visit if the person shows symptoms of corona or other serious condition.
In cases where the AI detects a very seriously ill patient, it will also enable the physician to call an ambulance to the users’ location and continuously track the user.
HOW WE ARE GOING TO BUILD IT
We will take a machine learning approach to develop highly-accurate algorithms that diagnose disease from cough and respiratory sounds. Machine learning is an artificial intelligence technique that constructs algorithms with the ability to learn from data. In our approach, signatures that characterize the respiratory tract are extracted from cough and breathing sounds. We start by matching signatures in a large database of sound recordings with known clinical diagnoses. Our machine learning tools then find the optimum combination of these signatures to create an accurate diagnostic test or severity measure (this is called classification). Importantly, we believe these signatures are consistent across the population and not specific to an individual so there is no need for a personalized database Following are the steps the app will take:
Receive an audio signal from the user's phone microphone
Filter the signal so as to improve its quality and remove background noise
Run the signal through an artificial neural network which will decide whether it is an usable breathing or cough signal
Convert the signal into a frequency-based representation (spectrogram)
Run the signal through a conveniently trained artificial neural network that would predict the user's condition and possible illness
Store features of the audio signal when the classification indicates a symptom
IMPACT
FACO will help patients get themselves tested at home, supporting in areas where tests and access to tests are limited. This will help democratize care in hard-to-reach or resource-strapped areas, and provide peace of mind so that patients will not overwhelm already stressed healthcare systems. Doctors will be able to prioritize patients with an urgent need related to their speciality, providing care from the palm of their hand, limiting their exposure and travel time.
CHALLENGES WE RAN INTO
No financial support
Working under quarantine measures
Working in different time-zones
Scarcity of high-quality data sets to train our models with
One Feature Related Problem- Legal shortcomings we might face when adding the tracking patient feature
ACCOMPLISHMENTS
We went from initial concept to a full working prototype. We got a jumpstart on organizational strategy, revenue and business plans—laying the groundwork for building partnerships with healthcare providers and pharmacies. On the creative side, we built our foundational brand and design system, and created over 40 screens to develop a fully working prototype of our digital experience. Our prototype models nearly the entire app experience—from recording respiratory sounds to reporting to managing contact, care, and prescriptions with physicians. Technologically, we successfully developed an algorithm for disease and have begun the application development process—well on our way to making this a fully functional product within the next 20 days.
You can explore the
full prototype here
or
watch the demo
(and
check out our promo gif
)!
WHAT WE'VE DONE SO FAR
We wanted to show that the project is feasible. Scientific literature has shown that audio data can help diagnose respiratory diseases. We provide some references below. However, it is unclear how reliable such a model would be in real situations.
For that reason, we used a publicly available annotated
dataset
of cough samples:
It is a collection of audio files in wav format classified into four different categories.
We wrote code in Python that converts those samples into MEL spectrograms. For the time being we are not using the MEL scale, just the spectrograms. We did several kinds of pre-processing of the signals, including data augmentation, then convert all pre-processed signals, along with their categories into a
databunch
object that can be used for training artificial neural networks created in the fastai library. The signals within the databunch were divided into training and validation sets.
Because the dataset size was reduced, we used
transfer learning
. That is, we used previously trained networks as a starting point, rather than training from scratch. We treated the spectrograms as if it were images and used powerful models pre-trained to classify images from large datasets. In particular, we tried both two variants of
resnet
and two variants of
VGG
differing on their depth (number of hidden layers). This approach implied turning the sprectograms into image-like representations and normalizing them according to the statistics of the original dataset our models were trained on (imagenet). We first changed the head of the networks to one that would classify according to our categories and trained only that part of the net,
freezing
the rest. Later on we
unfroze
the rest of the net and further trained it. We finally compared the different models by the confusion matrices that we obtained from the validation test. We finally settled on a model based on
VGG19
. We exported the model for later use in classifying audio samples through the pre-existing interface of our mobile app.
The results are promising, especially considering the small amount of data that we have available at this moment. We have included an image of the final confusion matrix that shows how our current network can correctly classify all four categories of signal about 50% of the time, far better than the random level of 25%. We conclude that wav files obtained trough a phone mic provide information that can be useful for diagnosing respiratory condition. We are confident that we can vastly improve both the sensitivity and the specificity of our model if we can gain access to larger, more representative datasets.
We provide an image of the final confusion matrix for our model in the gallery.
This is a
repository
that contains the most important pieces of our work, including some code, the confusion matrix image and the exported final model.
SUMMARY
We are developing digital healthcare solutions to assist doctors and empower patients to diagnose and manage diseases. We are creating easy to use, affordable, clinically validated and regulatory cleared diagnostic tools that only require a smartphone. Our solutions are designed to be easily integrated into existing tele-health solutions and we are also working on apps to provide respiratory disease diagnosis and management directly to consumers and healthcare providers.
Feel free to click on our
website
for more information. We developed this website using Javascript, HTML, CSS, Figma, and integrated it with Firebase to manage hosting and our database. Thank you for reading, and don't hesitate to reach out if you have any questions!
REFERENCES
Porter P, Claxton S, Wood J, Peltonen V, Brisbane J, Purdie F, Smith C, Bear N, Abeyratne U,
Diagnosis of Chronic Obstructive Pulmonary Disease (COPD) Exacerbations Using a Smartphone-Based, Cough Centred Algorithm, ERS 2019, October 1, 2019.
Porter P, Abeyratne U, Swarnkar V, Tan J, Ng T, Brisbane JM, Speldewinde D, Choveaux J, Sharan R, Kosasih K and Della, P,
A prospective multicentre study testing the diagnostic accuracy of an automated cough sound centered analytic system for the identification of common respiratory disorders in children,
Respiratory Research 20(81), 2019
Moschovis PP, Sampayo EM, Porter P, Abeyratne U, Doros G, Swarnkar V, Sharan R, Carl JC,
A Cough Analysis Smartphone Application for Diagnosis of Acute Respiratory Illnesses in Children, ATS 2019, May 19, 2019.
Sharan RV, Abeyratne UR, Swarnkar VR, Porter P,
Automatic croup diagnosis using cough sound recognition, IEEE Transactions on Biomedical Engineering 66(2), 2019.
Kosasih K, Abeyratne UR,
Exhaustive mathematical analysis of simple clinical measurements for childhood pneumonia diagnosis, World Journal of Pediatrics 13(5), 2017.
Kosasih K, Abeyratne UR, Swarnkar V, Triasih R,
Wavelet augmented cough analysis for rapid childhood pneumonia diagnosis, IEEE Transactions on Biomedical Engineering 62(4), 2015.
Amrulloh YA, Abeyratne UR, Swarnkar V, Triasih R, Setyati A,
Automatic cough segmentation from non-contact sound recordings in pediatric wards, Biomedical Signal Processing and Control 21, 2015.
Swarnkar V, Abeyratne UR, Chang AB, Amrulloh YA, Setyati A, Triasih R,
Automatic identification of wet and dry cough in pediatric patients with respiratory diseases, Annals Biomedical Engineering 41(5), 2013.
Abeyratne UR, Swarnkar V, Setyati A, Triasih R,
Cough sound analysis can rapidly diagnose childhood pneumonia, Annals Biomedical Engineering 41(11), 2013.
FACO APP VIDEO DEMO
LINK
FACO PRESENTATION
LINK
FACO 1st Pilot Web App
LINK
Built With
android-studio
doubango
fastai
firebase
google-cloud
google-maps
java
machine-learning
mysql
numpy
pandas
python
pytorch
sklearn
sound-monitoring-and-matching-api
spyder
webrtc
Try it out
github.com | FACO: Fight Against Corona | A contactless digital healthcare solution to assist doctors and empower patients to diagnose and manage diseases | ['Archit Suryawanshi', 'Oghenetejiri Agbodoroba', 'Ntongha Ibiang', 'Sahil Singhavi', 'Ruthy Levi', 'Navneet Gupta', 'Mohamed Hany', 'Prachi Sonje', 'GAVAKSHIT VERMA', 'Shraddha Nemane', 'snikita312', 'Gauri Thukral', 'udit agarwal', 'Francisco Tornay', 'Rubén Aguilera García'] | ['1st place', 'The Best Women-Led Team'] | ['android-studio', 'doubango', 'fastai', 'firebase', 'google-cloud', 'google-maps', 'java', 'machine-learning', 'mysql', 'numpy', 'pandas', 'python', 'pytorch', 'sklearn', 'sound-monitoring-and-matching-api', 'spyder', 'webrtc'] | 28 |
10,338 | https://devpost.com/software/zero-contact-uav-bot | Ardu Pilot Software
AA Interactive Form to collect Input
UAV Weather Forecast For Pre-Flight Checks
Mission Planner
UAV / Drone Taking off
Access Database for Logging
Sky Vector for logging Aeronautical chart
Code snippet in step level (MainTask)
Code snippet (Sub Task Module) for Input
Inspiration
The Novel Corona-virus has affected humanity in various ways, be it our economy, our freedom of movement, and the loss of loved ones. Something that struck me was elderly people having to wait in a queue for medicines at an outlet. Even though there are home delivery services, the risk of infection is extremely high as this job requires you to move around places at a higher rate and I recollected news of people infected by pizza delivery agents / Swiggy agents throughout India on multiple occasions. The Lockdown definitely has slowed down the infection rates but we are forgetting that all essential services are not contactless. That's when I decided to create a solution to this by using a Drone / UAV to Deliver essentials and medicines primarily for the vulnerable among us so that we ensure they are safe, Drones are usually manually remote-controlled by a pilot. Me myself being an aerospace engineer with focus on Avionics and with Automation Anywhere. I decided to use an AutoPilot Mission Planner to write coded commands to the Flight controller in order to make the Flight Autonomous and deliver the essential package and return home.
From the News
Bengaluru on superspreader alert after delivery boy tests positive
-
Click here to read
83-year-old man collapses while waiting in New World queue in New Lynn
-
Click here to read
Features in a nutshell
Interactive User input
Database Logging
Autonomous UAV Flight
Automated Pre Flight Checks
Address to Geo Coordinates conversion
Distance, Payload release altitude Calculation
AutoPilot Command creation (Flight Plan)
Payload Delivery (Essential package Delivery)
Scalability
What it does
The Bot collects the delivery address and input data using Interactive forms and converts the address string into location coordinates using Geocoding API and uses Python Script to calculate the Flight Distance using Haversine Formula based on the range of the UAV and Performs Pre-Flight Checks such as Wind speed, Temperature, Precipitation Probability, Cloud Cover, Visibility and more. It also checks for any nearby airport and logs the Aeronautical charts for the way-points using Sky Vector web service. It then Sends Flight information to the DGCA for Flying permission via API. It then calculates the payload release altitude based on logic using the Indian regulatory guidelines for construction. Finally, the bot compiles this information to create a flight plan command and uses the Mission Planner which is Ground Control Software to write the code into the Flight controller AutoPilot using a wireless transmitter and launches the UAV on its mission. While doing this each flight is tracked by a unique flight control number and logged to a database for future audit and compliance purposes and folder is created with Logs, charts, and autopilot code. Hence this Bot enables users to completely automate the Pre-Flight processes and automate the creation of code for Autonomous UAV Flight which will Deliver the payload (Essential Package) at the desired location and return back home and complete the mission. This makes the complete process contactless and safe. Hence serving the essential needs of the most vulnerable and reducing the infection rate.
How I built it
This RPA Solution is Built on Automation Anywhere A2019 and integrates with various technology as mentioned below, which is the real beauty of RPA.
Microsoft Bing Geocoding API
Python 3.8.3
Ardu Pilot Mission Planner ( with wireless transmitter )
Interactive Forms
UAV Forecast Service
Sky Vector Chart Service
DGCA API
Microsoft Access Database
UAV / Drone & Payload release mechanism
Challenges I ran into
One of the challenges was to use complex mathematical formulae using Python to derive certain parameters. However, the Python Package on A2019 made it really easy to call Python functions inside and code and get the output. Also creating a waypoint plan for the Autopilot was initially a challenge however using the product documentation I was able to create the flight plans using Log to file package making all the values dynamic.
Accomplishments that I'm proud of
I am happy that I was able to use my academic knowledge in Aerospace, my work expertise in Robotic Process Automation, and my curiosity to explore new possibilities in creating this solution which can help the world in this traumatic situation. I am also happy that I was able to bring out the true sense of Anywhere in the name "Automation Anywhere".
What I learned
It was indeed a great experience to develop this bot with a lot of research, trial & error and new learnings. I was able to start off with Python and I'm looking forward to trying out further possibilities.
What's next for Zero Contact UAV Bot
The RPA solution can be scaled up for usage with Queue (WLM) and to further improvise and add on more features. To make the solution more independent we can have a "Raspberry Pi" attached to the drone and connected to the Flight controller and the Internet. We can install AA Bot agent on the Raspberry Pi running windows and we can remotely deploy the automation considering the Drone as a bot runner with wings ;). This drone will be a fully automated solution for an Autonomous Flight using Robotic Process Automation as the base Technolgy.
Other areas of usage
Delivery Services
Search and Rescue Facilities
Climbers and Firefighters
Mine and Oil Industry
Military and Gaurd Services
Disaster Relief Services
Built With
api
ardupilot
automationanywhere
autonomousuav
flightcontroller
geocodingapi
missionplanner
payloadreleasemechanism
python
skyvector
uavforcast
Try it out
github.com | Zero Contact - Essentials Delivery UAV Bot | The Bot creates and executes an Autonomous Flight Plan for a UAV / Drone based on Guidelines for Contact less Delivery of Essential commodities during the pandemic. | ['Manuel Varghese Philip'] | ['The Wolfram Award', 'First prize', 'Gold'] | ['api', 'ardupilot', 'automationanywhere', 'autonomousuav', 'flightcontroller', 'geocodingapi', 'missionplanner', 'payloadreleasemechanism', 'python', 'skyvector', 'uavforcast'] | 0 |
10,338 | https://devpost.com/software/robgrade | Inspiration
Everybody hates manual, repetitive work and there are a few of us that really find joy in doing it. So I want to bring awareness inside my organization that we can indeed save time, money and make our employees happier if we get rid of some of this manual and repetitive work without losing the quality of this work.
What it does
It does not do anything right now, since it is not implemented yet. But the idea is to use a RPA robot to upgrade different applications/platforms that we are using in our manufacturing service inside my organization. We have a lot of applications and platforms which purpose is to help simple people, operators to produce different products from our portofolio. Upgrades can take months to be completed, validated and tested since one employee cannot work on multiple upgrades at once.
How I built it
It can be built using any RPA company available on the market, but I would chose Blue Prism for this project since it is one of my company's vendors
Challenges I ran into
The challanges I run into really often when trying to back-up a project like this is the people mentality. A lot of people, even really big managers with a lot of experience on board, are sometimes not so happy to change the systems or the things we are doing. A lot of people also think that a robot can replace them and even thought this can be true, it does not mean we are going to fire people, we are just going to free their time and they can focus on some other work which can be more fun to do. That's actually the purpose of the RPA robots.
Accomplishments that I'm proud of
I think I am proud that I keep on finding new posibilities and opportunities in my day to day job. Even thought as I mentioned above, it is really challenging to work with people and try to change their mentality, but that is the really fun part. At the end of the day, I am the proudest person in the room if I could convince one more person to adopt my new perspective (generally) and try to implement it in their work space
What I learned
I learned that even thought we pretty much know the opportunities that are out there, we often find ourselves in the position in which we do not take actions because we are used to the process and this keeps us from evolving.
What's next for Robgrade
The next steps is to propose the idea to my managers and START DOING IT!
Technical documentation and next steps can be FOUND HERE:
https://drive.google.com/file/d/1hgEA7oVBIrDDuoxP0K_lllaXVmoJA2eE/view?usp=drivesdk
Built With
rpa | Robgrade | Do you want to save 8 months of an employee work and at the same time be 8 months faster in the work this employee was supposed to deliver? Then let's develop an RPA robot to do the job! | ['Gabriela Tudor'] | ['Silver'] | ['rpa'] | 1 |
10,338 | https://devpost.com/software/sneakerassistant | Inspiration
I got inspired by one of my friends. Among the teenagers there's this trend: collecting sneakers. My friend told me that he forgot how many pairs he bought and he almost payed more than he should.
What it does
Let's say you want to search for a sneaker. The program can access 3 of the most successful shoe websites. After you select your sneaker, you will have to rate it yourself from 1 to 10 keeping in mind the price of it, the appearance and whatever little things you like/dislike. Then the whole process repeats, until you find all the shoes you wanted, and after that all the shoes and ratings and sites are stored in an Excel file so you will not forget anything.
How I built it
Using RPA basics i learned on the internet and UiPath tutorials.
Challenges I ran into
I think the biggest challenge is that i always want to do more about the program and constantly upgrading it but i don't have the resources or knowledge to do things like these and you have to accept that this is all you can do
Accomplishments that I'm proud of
I'm proud of myself that even if i had no lessons of RPA, I managed to do an entire automation with YouTube tutorials and UiPath Forums in a month.
What I learned
I gained a lot of RPA knowledge and I found out that I like doing this.
What's next for SneakerAssistant
As i said earlier, I don't have the knowledge to upgrade the program anymore, for now. This is all I could do before the deadline, but in the future I will learn way more about RPA, I will add popular sneaker websites, and more features to make your life easier.
Built With
rpa
uipath | SneakerAssistant | RPA program that helps you to organize your list of favorite shoes | ['David Tudorie'] | ['Bronze'] | ['rpa', 'uipath'] | 2 |
10,338 | https://devpost.com/software/wavy-assistant-fnphsd | Inspiration
Cardiovascular disease (CVD) affects millions of lives worldwide and is the number one cause of death worldwide. People suffering from CVD are mostly elderly, especially in the high risk categories for cardiac arrest and strokes. These elderly often live on their own. They are afraid something bad might happen and no one will be able to help them. Among elderly, heart attacks and strokes are a big factor in getting admitted into hospital care. It also takes a lot of time, effort and specialist devices to monitor the progression of CVD symptoms. Isn't there anything that can be done using recent technological advances, like 5G and wearables?
What it does
Wavy is the smart partner for your heart, by connecting wearable devices and smart home speakers, powered by the speed and reliability of 5G. Wavy learns to understand your heart and even gives customized alerts by analyzing and predicting your behavior. Through Wavy's connected 5G integration, every person with CVD is looked after. It also included music-based relaxation exercises, to lower stress-related CVD symptoms.
How we built it
A CVD patient wears a 5G enabled smart wearable device. Using 5G and API connections we stream that data to the cloud in real-time. The data is stored in a scalable big data environment and also put through our AI neural network detecting and monitoring the patient's heart data for any deviations. That data is made available to 5G enabled smart home speakers in real time, so in case worrying events happen, the smart home speaker can take action. It can for example unlock 5G IoT door locks in an emergency.
Challenges we ran into
The biggest challenge was retrieving and cleaning the data so it can be processed by a predictive algorithm. Another one was getting access to the APIs of smart wearables.
Accomplishments that we're proud of
We found an effective way to apply our technical skillset to create a high-impact solution to a huge social problem.
What we learned
With 5G we are able to tackle use cases that we otherwise could not. It's eye-opening to see the possibilities and opening up of completely new use cases, thanks to the unparalleled speed of 5G connections.
What's next for Wavy 5G
We are scheduled to test our prototype with a group of 30 female heart patients at a leading Dutch university hospital (Radboudumc Nijmegen). We are also in talks with health insurance companies, so we can ask to have it covered after proving its effectiveness.
Built With
5g
ai
big-data
dialogflow
iot
python
pytorch
react-native
rpa
smart-home-speakers
wearables
Try it out
docs.google.com | Wavy 5G | Wavy monitors heart patients using 5G wearables and alerts in real time if anything goes wrong. | ['Daryl Autar', 'Akash Kanhai'] | ['Bronze'] | ['5g', 'ai', 'big-data', 'dialogflow', 'iot', 'python', 'pytorch', 'react-native', 'rpa', 'smart-home-speakers', 'wearables'] | 3 |
10,338 | https://devpost.com/software/5g-rpa-communication-technology |
window.fbAsyncInit = function() {
FB.init({
appId : 115745995110194,
xfbml : true,
version : 'v3.3'
});
// Get Embedded Video Player API Instance
FB.Event.subscribe('xfbml.ready', function(msg) {
if (msg.type === 'video') {
// force a resize of the carousel
setTimeout(
function() {
$('[data-slick]').slick("setPosition")
}, 2500
)
}
});
};
(function (d, s, id) {
var js, fjs = d.getElementsByTagName(s)[0];
if (d.getElementById(id)) return;
js = d.createElement(s);
js.id = id;
js.src = "https://connect.facebook.net/en_US/sdk.js";
fjs.parentNode.insertBefore(js, fjs);
}(document, 'script', 'facebook-jssdk'));
Anglikan
Inspiration, It inspires you to learn about Communication technology
What it does,Stay connected with people easily
How I built it, I built this to help more fast Communication technology which can enables the community stay connected all day,so it is very good and soft .
Challenges I ran into, it not much like that,all I do is to keep on working on it every day by day in other to achieve it.
Accomplishments that I'm proud of
What I learned
What's next for 5G+RPA Communication technology,
Built With
across-communications
artoolkit
biogrid
general-land-office-records
telegram
Try it out
devpost.com | 5G+RPA Communication technology, | It enables You to learn fast and easy | ['Anglikan Chinonso'] | [] | ['across-communications', 'artoolkit', 'biogrid', 'general-land-office-records', 'telegram'] | 4 |
10,338 | https://devpost.com/software/timmy | Inspiration
Coronavirus pandemic has massively decreased the economy in our country. One of the many industries affected by this phenomena is
Romania's tourism
, which has decreased between 60% and 90% since the beginning of the pandemic.
These being said, we were eager to find a solution so we can attract tourists to places all around our beautiful country. To make that happen, we knew we needed something friendly, easy to use, helpful and effective to make tourists enjoy their free time as much as possible.
And this is how our idea started to develop!
Our first thought was building all the necesarry information and data about destinations and touristic places in just one application, but also to make easier booking a room or some seats when travelling or to find informations about a place at any time. This is how our project about the traveling app was born. After, many more ideas started to pop-up in our minds, so we took a notebook and wrote down every single idea. Every one of us participated at these brainstormming sessions where imagination has been the key element so far.
We also needed a name about our application. For us, the perfect name was unique, meaningful, but related to the beauty of traveling and technology too. Most of the names we first thought of were already taken, so we tried to make an acronym out of a sentence/quote we found most appropiate to what our application does. This is how we chose TIMMY, which stands for "Travel Intelligent. Make Memories for Yourself."
What it does
The TIMMY application has been designed to be a virtual assistant in your trips to Romania. Whether it's a wild beach or the busiest center in the country, we have recommendations for you as well as real-time informations about those places with the help of
AI and 5G technology
. When you travel you can add to your favourites the places you visited. Now is when the Artificial Intelligence is doing its best to save your preferences and recommend you new places like the ones you liked before. Also, the AI will know when some places are more busy and when they are free, according to the day of the week or the hour. All of these and many others will be sent to you with the speed of the 5G internet technology. You can also arrange a visit to the museum or book seats at a restaurant in less than 30 seconds. With the help of
RPA technology
, the application will send to the location a text format with all the details, like date and hour, number of persons, your name and phone number. Then, shortly after you will be contacted (by phone) for confirmation. This way, you don't have to do anything else than answering 2 questions and pressing 2 buttons. Without any worries and inconveniences, your vacation will be much easier to plan and more enjoyable with TIMMY!
How I built it
During the process of our app's development, design was most required. After we chose a logo, a name and a motto for our project, we took some notes of every idea we came up with and we tried to do some drafts/sketches of the interface. After these things were done, we started designing using Canva. We shared between us our process on this platform, we improved every design of the interface, we made suggestions to each other until we got the best out of all we had. We tried to think of every detail: main menu, map, directions using Waze or Google Maps, variety of places (from restaurants and hotels to beauty centers), informations, pictures and places to visit in every destination, suggestions suitable to every user's prefferences, creating an account and adding reviews. Even though we had to add a lot of features, we always focused on keeping everything as simple and friendly as possible. After the design of the app was done, we had to put everything in order, so we could realise a good presentation for our project. For the presentation we used PowerPoint. To upload our presentation we needed a recording program to make a video out of our PowerPoint. We chose Bandicam for completing this job. The video was edited in Wondershare Filmora 9.
Tasks were divided between our four members and every one of us did his best to reach the team's goal!
Challenges I ran into
The competitive market into this field was a challenge since there are many websites or apps that are offering alike information. Keeping this into account, we found an opportunity to develop the application by offering something more – an intelligent assistant who is up to date to all the cool places and to acces them in a friendly-user, interactive way.
Also, we saw a challenge for the future of travelling, the worldwide tourism industry has been devastated by the global pandemic of Covid-19. Many of the city's attractions are eerily empty and in the post-pandemic period we have to adapt and reinvent this domain.
We asked ourselves the question - How can the tourism industry recover? And we found the answer through this app.
Accomplishments that I'm proud of
COVID-19 reality gave us the opportunity to innovate this area and defy the competitors. In addition, we took this chance to save tourism from collapse or, at least, to fight for it. Our main mission is to help and also have to attract as many people as possible, to provide services, to show all possibilities and conditions they could benefit from owners, to promote Romania's beautiful places, landscapes and people, but also to increase the Romania’s economy.
What I learned
By developing our project, we discovered that it doesn't matter how different you are, where you are from, you could achieve everything. You need to be ambitious to get over obstacles. We discovered more about our beautiful country, learned how tourism could revive again. Pushing our limits into hours of brainstorming and coming up with ideas were nice moments for all of us. We have also learnt a lot from each other’s experiences. We discovered many issues in Romanian tourism which made us work harder and harder and be more creative and, finally, completing the task with a sustainable solution. Also, we found that the
teamwork makes the dream work!
What's next for TIMMY
In the future, we are going to target other countries too, especially Eastern Europe, encouraging tourism here. Nevertheless, we will update periodically the app with maps and new features to improve the quality of our services. We will contact companies for partnerships and advertising, such as Booking and Airbnb.
Furthermore, there are many underrated remote zones in Romania, with a beautiful landscape and amazing sights. We are planning to bring the attention on them back and help villiages, hotels, restaurants and terraces to present their offerts easier for clients. In advance, reviews and suggestions for tourists will increase the interest of people, also photos and specific features are integrated for a better experience.
Artificial Intelligence and RPA are very useful and important too in the procces of making reservations at restaurants or booking rooms at hotels, a struggle many people face and want to solve before leaving home and often takes a lot of time. Our App, TIMMY, will be your assistant during your trips and a wise advicer in taking all your further decisions. No more hurry during travelling! Now you can enjoy you trip and enjoy our suggestions regarding to restaurants, in order to have the perfect meal and atmosphere.
Development: 6-12 months.
Implementing: security, programming, web design development, graphic design development, AI tool, actualised world-wide maps based on GPS, RPA Tehnology.
Built With
brainstorming
canva
filmora
graphicdesign
java
node.js
photoshop
powerpoint
programming
react | TIMMY | The TIMMY application has been designed to be a virtual assistant in your trips to Romania. Your vacation will be much easier to plan and more enjoyable with TIMMY! | ['Barbu Bianca', 'Angela Dumitrescu', 'Alexandru Sichin', 'Andrei Turcea'] | [] | ['brainstorming', 'canva', 'filmora', 'graphicdesign', 'java', 'node.js', 'photoshop', 'powerpoint', 'programming', 'react'] | 5 |
10,338 | https://devpost.com/software/5g-antenna-tracker | Inspiration
I wanted to make it easy for everyone to know the source of the best current internet technology, so they can use it.
What it does
It pinpoints the exact location of 5G antennas in your hometown.
Built With
c++ | 5G Antenna Tracker | This projects encompasses the idea of pinpointing the exact locations of 5G antennas located throughout your city. | ['Denis-Mihai Vlasceanu'] | [] | ['c++'] | 6 |
10,338 | https://devpost.com/software/hj-efb1hd | Inspiration
I believe that technology is changing how we live and it improves our lives little by little. I wanted to come with an idea for a project that brings safety to humans, and RPA can certainly help us. Safety is a priority, and without it, we can’t evolve properly. Even though traffic rules and punishments exist, pedestrian accidents happen. I believe that a car that detects crosswalks and pedestrians can help people see the incident beforehand.
What it does
My car uses different technologies in order to identify crosswalks, because many accidents happen since drivers don't observe them in time. It is also the case when people run on the crosswalk or cross the street illegally, so then I thought that my car should detect pedestrians, too. My car is able to do this by automatization and robotization of the car's board, in order to surpass the human limit, using, of course, RPA.
How I built it
I built the site by selecting a theme that correlates with my idea and that was a good starting point. Then, I started to design the site by setting backgrounds, using strips and boxes for design and by using animations to captivate the visitor. I chose photos that had a connection with the car and its' technologies. I used videos at the beginning of two pages in order to present the car and give people an idea on how the car looks. By using Microsoft Video Editor I was able to create a video presentation of SMV. I selected different non-copyright videos from Pexels site, organised and edited them to create the YouTube video. Then, I wanted to find a music that brought my creation to life, so I used the music "Vibe" by Ash O'Connor that matched with the video. I edited the music a little bit using an online editor.
Challenges I ran into
Because I was working solo, I ran into different kinds of challenges that I needed to face. I was struggling in finding an idea at first, and I didn't know what a hackathon is, but now I experienced new things and I exited my comfort zone. I also didn't know what 5G and RPA technologies work and this hackathon expanded my vision of this world. Another challenge I faced was the finding and the implementation of an idea into a project, but eventually I knew how to do it. Creating a site was hard at first because the platform I used was unknown to me but, step by step, I overcame it. The hardest thing was organisation, because without it, you drift around without knowing what to do next, so I noted my ideas on a notebook in order to structure my thoughts properly.
Accomplishments that I'm proud of
I am proud of the fact that I learned how make a site and that I learned how to post a video on Youtube, which the latter was easier than I thought. I am proud that I am participating and working solo at my first hackathon, and I saw how much work you need to put in. Moreover, I discovered qualities of mine that I didn't know I have, such as being skillful and handling new situations and dealing with them properly.
What I learned
I learned how to create a site using Wix, a platform that I didn’t use before. Also, I learned how to edit a simple video in Microsoft Video Editor and how to edit photos in Microsoft photos. I discovered sites (that had videos and pictures uploaded by photographers) that helped me find beautiful photos that I used in the creation of my own. Moreover, I learned how to design a site, how to edit and position a text in a page, how to add effects, how to use strips and I uploaded my first video on YouTube with the occasion of this hackathon.
What's next for Crosswalk detection
I want to further develop my idea and improve it to make it even better. I will work at my site more to modernize it by learning how to properly web design. I also want to learn the process on how a professional makes a site and the thought process and work behind that.
Built With
adaboost-classifier
figure-ground-segmentation
hog
integral-framework
mrf
proximity-sensor
radar-sensor
stereo-vision
Try it out
stefanivan41.wixsite.com | Crosswalk Detection | Each year, more than 270.000 pedestrians lose their lives on the world’s roads, even though laws exist. A car that detects crosswalks and avoids the possible accident will reduce these types of events | ['Stefan Ivan'] | [] | ['adaboost-classifier', 'figure-ground-segmentation', 'hog', 'integral-framework', 'mrf', 'proximity-sensor', 'radar-sensor', 'stereo-vision'] | 7 |
10,338 | https://devpost.com/software/all-a-s-dfykw5 | User friendly Login
User interface inside the APP
Global Messenger
Global Messenger
Special Needs Learners
User interface inside the APP
Global Messenger Settings
Inspiration My inspiration started when i watched the movie ..... Social Network and i am a huge fan of Mark Zuckerberg. this then led me to create a global APP which will enhance the lives of kids by providing them a solution to a better and brighter education using online technology as well as allowing all students from across the world to make contact with each other just by a simple swipe of a finger and search for active users across the globe.
What it does its a fully functional educational resource and global messaging service for every user to easily connect with others via their online profiles.
How I built it i used appy pie and my ideas put together to create this global APP
Challenges I ran into the challenges was that of many to mention but the more server ones was time and this was not on my side as i had to work and still do development after work which was becoming rather difficult. i then decided to resign from my job and focus solely on the development and it was at this point were i was able to build my APP to an amazing state
Accomplishments that I'm proud of i have been featured on a few radio stations i was also on TV and most of all the most important achievement is helping people get an education. as well as to note that ALL A's has made it onto windows, IOS and Android.
What I learned is that time is something that can never be wasted and taken for granted as i know the true value of a second, a minute and an hour.
What's next for ALL A's to become the global leader in E-Learning.
Try it out
play.google.com | ALL A's | Global E - Learning App empowering the world by means of education. | ['Zayne Chan'] | [] | [] | 8 |
10,338 | https://devpost.com/software/online-booking-slot-for-public-places-services | Inspiration During this Corona Virus time main issue is Community Gathering, But we have to go to Public places either for Grocery Shopping, Bank, Salon. And we have to stand in long queue which is very hectic and frustrated.
What it does
In this app you can register and choose your service after login book Slot and get notification about the status of your queue number live. If you are not using app, can make call on our toolfree number in any can talk in any language for booking slot or any other update. Store owner can manage there inventory easily and RPA Bot will track Covid 19 safety rules like Face Mask Detection, Social Distancing. RPA bot will make call to Store owner in case of rules violation and play alarm. People can use chatbot as well
How I built it
RPA(Automation Anywhere )+ Python + Microsoft Azure + Twilio
Challenges I ran into
Integrating Multiple Technology
Accomplishments that I'm proud of
End to End Platform for Current Problem
What I learned
Handling Situation within time
What's next for Online Booking Slot For Public Places Services
Live streaming with thermal camera for temperature detection.
Hosting computer vision module and other application modules in the Azure cloud.
OAuth/LDAP based authentication.
Adding Vaccine Certificate Validation.
Voice Chatbot.
Multi tenant - focus on all the Architecturally significant requirement (NFRS)
Q&A Maker Chatbot Enhancement.
Toll-free IVR Calling.
Live information about Containment zone if anyone is coming from that area.
User Guide for application and Website.
Built With
artificialintelleginece
automationanywhere
machine-learning
python
rpa
Try it out
drive.google.com | Online Booking Slot For Public Places Services | This App will help you prebooking slots for Public Places like Supermarket, Salon, etc for saving time and keeping less community Gathering and keep monitoring Safety Rules like Social Distancing | ['tanya Lakhotiya'] | [] | ['artificialintelleginece', 'automationanywhere', 'machine-learning', 'python', 'rpa'] | 9 |
10,338 | https://devpost.com/software/healthrific-your-health-pal | todo
Built With
bluetooth
dart
flutter
Try it out
tiny.cc
github.com | na | no | ['Anubhav Sinha'] | [] | ['bluetooth', 'dart', 'flutter'] | 10 |
10,338 | https://devpost.com/software/aivo-health-assistant | IBM Watson based chat assistant
Online medical store
Assistant in Slack
Inspiration
A potential challenge during the pandemic outbreak like COVID19 is overwhelming hospitals. Due to the increase in the number of COVID patients, doctors are giving less attention to a non-COVID patient. Right now, hospitals don't have the capacity for the large number of incoming patients. Not just during COVID but also during normal time we need some platform that guides us through our health problems. It should help each and every person either educated or uneducated to diagnose their disease and get out of danger. Our project addresses all these issues.
What it does
Aivo platform offers an ideal way to let people know what medicine to take for symptoms they tell and also know more about the disease they have by describing the symptoms. This tool can be deployed in large scale as it is useful for everyone right from mobiles to Kiosk alike model in every Pharmacy stores.
How we built it
We used the IBM Watson along with Alan studio for this project.
IBM Watson
User Interaction
Realtime Database
Store Vital Data and User Information
Cloud Functions
Other IBM
IBM API for websites
Bootstrap HTML/CSS/JS
Bootstrap Framework
Use of JQuery
Use of SmartForm for Contact
Frontend Framework
GitHub
File Management
Hosting
Alan Studio
Voice based interaction
Smart communication with website and AI functionalities.
Aivo - Alan is a Smart Assistant that we have built for users to ask simple questions.
You can ask it I have a Cough
and it will respond
Challenges we ran into
There were many challenges we ran into, but that's what programming's all about. One of the difficult challenges we ran into was making sure the UI worked. Another challenge was figuring out how to to extract information from the JSON file to the website.
Accomplishments that we're proud of
We are proud of so many things. We made use of this project to the best of our abilities. We got to use the IBM Watson, which is a first for all of us, we had used IBM Watson before and we will continue to use this platform. Additionally, we combined all of our skills to create a website that use multiple frameworks and we are proud of this website. We love the UI/UX and we love the Backend, it was our first time as well using these frameworks. Finally, we are proud of the amount of work we pulled of. We would have never thought we could accomplish this much in such a small amount of time.
What we learned
Creating realtime databases
Alan Studio
User Authentication
IBM Watson
## What's next for DrFit
Implement IBM Watson instead of Alan (Wider range of possibilites)
Implement more Google Cloud Features including Tensorflow AI for medical classification and image classificatin to find various conditions
Implement a TeleHealth API platform for virtual doctor visits
Implement a precise Covid-19 screener questionaire for the workplace and schools
Built With
alan
github
ibm-cloud
ibm-watson
Try it out
mohinishteja.github.io
web-chat.global.assistant.watson.cloud.ibm.com
github.com | Aivo-Health Assistant | Aivo is a samrt health assistant which helps people diagnose their health condition based on symptoms they tell. It also acts as a good platform to get medicines by voice interaction. | ['Mohinish Teja', 'Abhijith Gunturu'] | [] | ['alan', 'github', 'ibm-cloud', 'ibm-watson'] | 11 |
10,338 | https://devpost.com/software/compc-empowering-people-through-technology | Inspiration
As most of us are working from home, attending school/colleges from home but it’s still difficult for most of the students/lower level employees to afford a laptop/pc. After every few couple of weeks, a new phone or laptop is launched.
With upcoming 5G technology it is possible to provide a Cloud PC to users which will decrease the initial investment to 1/ 10th.
User just have to pay for the subscription amount(Hardware will be free of cost) and need to pay only for the services they are taking.
Benefits :
Minimal Hardware:
Low-Cost User Devices.
Only I/O Devices and 5g connectivity chip at User Device.
Thinner phones, smaller Laptops, lighter CPU’s possible.
Hardware advances are slower, hence longer service life.
Remote Desktop Connection:
No load at server when machine is switched off.
Computing power available on demand.
1 Server can serve as many as 100 laptops.
Servers can be upgraded without inconvenience to user.
5G Connectivity:
Extremely fast, real-time connection to server.
Tech stack
Windows Communication Protocols
[MS-RDPBCGR],[MS-RDPCR2],[MS-RDPEA],[MS-RDPEAI],[MS-RDPECLIP],[MS-RDPEGDI],[MS-RDPEVOR]
[MS-RDPBCGR],[MS-RDPCR2],[MS-RDPEA],[MS-RDPEAI],[MS-RDPECLIP],[MS-RDPEGDI],[MS-RDPEVOR]
Business Model
Service based model
Yearly Subscription starting from Rs 4500/-.
8000 customers required for yearly revenue of 10 Cr.
A unique product made for digital users.
Low cost solution for schools, colleges, offices and start-ups.
Specifications
Latency < 1 ms
Remote PC, cloud gaming, cloud computing at affordable rates
Server & Client side remote desktop protocol | ComPC - Empowering people through Technology | With upcoming 5G technology it is possible to provide a low cost laptop/mobile to users connected through servers to host and process data which will decrease the initial investment to 1/ 10th. | ['Saurabh Singh', 'Nidhi Yadav'] | [] | [] | 12 |
10,338 | https://devpost.com/software/generation-of-child-progress-card-and-sending-mail-to-parent | A sample format of Generated Progress Report Card
Inspiration
I have been upskilling my selves in the field of RPA using UiPath Academy and in Process of Learning, I got an Idea where if this kind of Bot is available to the Educational Institutions it can replace lot of Repetitive and Calculation tasks.
What it does
It reads the data from the Marks of students which are in Excel files, Generates Progress Report Card and Sends the PDF Format of Report card through Email to the respective guardian
How I built it
I had used all the essential Activities like Sequence, Read Range, For Each Data Table, Multiple Assign, Word Application Scope, Click, Type Into, Send HotKey, Save Word File, Export to PDF, Get Password, Send SMTP Mail Message.
Challenges I ran into
There are very small Challenges where I ran into, Sometimes the Bot does not recognize the Elements later I had reselected the elements so that it works absolutely fine.
Accomplishments that I'm proud of
I have been developing bots for the last three months and I feel I had developed a lot of skills which are very essential in coming days
What I learned
Using this kind of Bot we can Automate lot of Tasks done by Administrative people in the Universities, Organizations, Schools etc.... This kind of Bot is used in both Attended vs Unattended Automation if required. There is a huge amount of revenue can be saved with this kind of Bot.
What's next for Generation of Child Progress Card and sending mail to Parent
We can publish it to the Orchestrator so that we can deploy it remotely and operate when we are unavailable at the moment or when we are out of the station.
Built With
c#
email
excel
visual-basic
word
xaml
Try it out
drive.google.com | Generation of Child Progress Card and sending mail to Parent | There is a lot of repetitive tasks involved in Generation of Progress Report Cards, this Bot reads the data from Excel Files, Create Report Card and Sends to the respective Parent/Guardian | ['dattatreya thunuguntla'] | [] | ['c#', 'email', 'excel', 'visual-basic', 'word', 'xaml'] | 13 |
10,338 | https://devpost.com/software/healthrific | Contact free basin modified design
Actual picture of Basin
Actual hardware pic
SignIn page
SignUp page
Forgot Password page
Kiosk Test
Self Assessment Test
Covid 19 Updates
Health Tips
Results of Self assessment test
UV-C
todo
Built With
bluetooth
dart
firebase
flutter
Try it out
github.com
docs.google.com
drive.google.com | no | na | ['Haripriya Baskaran', 'Mohammed Mohsin'] | ['Script Foundation: Best Healthcare Solution'] | ['bluetooth', 'dart', 'firebase', 'flutter'] | 14 |
10,338 | https://devpost.com/software/up-g | Inspiration
As technology enthusiasts, we were inspired by the interconnectivity of 5G and the challenging times of the pandemic.
We came up with Up&G as an answer to the cancelled entertainment events of 2020 and a solution for people who miss the fun atmosphere.
What it does
With the help of 5G technology, Up&G is able to connect local entertainment points with hotel chains or individuals.
Live streams from local entertainment events (concerts, theaters, philharmonics, stand-up comedy shows) will be available in the app and enjoyed by users at their own comfort with the help of 5G devices, which will intuitively adapt the light and the sound to the events atmosphere.
By creating a personal account, users will be recommended events based on their cloud data, preference questions and events that already have been liked and watched.
Notifications are also part of our app, letting the person know when their favorite artist makes an appearance or similar shows are taking place.
Our clients will be able to make in-app purchases in order to have access to live streams via digital fingerprint.
Withal, Up&G represents a marketing platform for brands that want to promote their event in the local area.
How we built it
Our project is still at the concept stage, but we've put together a demo website:
https://sites.google.com/view/up-g-submission
Challenges we ran into
Shaping the idea represented one of the challenges that we’ve ran into.
As 12th grade students, we had to do some research in order to get a better understanding on the technologies that our app uses.
Accomplishments that we're proud of
In a short period of time we’ve learnt a lot about the topic of this hackathon and came up with an idea that will benefit tourism in the future.
What we learned
5G technology was not a foreign topic to us, but we believe that getting a better understanding of the subject benefited our knowledge a lot. Even so, the most important thing we learned from this experience is teamwork and how valuable it is.
What's next for Up&G
We are looking forward to an app development, features that will enable communication and connect users through virtual rooms.
Built With
5g
google-sites
qr-code
Try it out
sites.google.com | Up&G | an entertainment marketing & tourism platform, offering users the opportunity to experience live entertainment events at their own comfort, adapting the ambiance of their room to the atmospheres event | ['Ivan Maria', 'Ioana Buia'] | [] | ['5g', 'google-sites', 'qr-code'] | 15 |
10,338 | https://devpost.com/software/self-aware | Medi-Box 3D Designing
Medi-Book Web Application Interface
Medi-Box
After 3D Printing, Final Design
hardware
Medi-Box
Doctors List on Medi-Book
Medi-Box
hardware
this picture shows our software with hardware and mobile application
working with ecg module
working
Inspiration
I have seen many peoples who live in remote areas, who move from one city to another in case of job postings. These people don't know about availability of hospitals, clinics, medicals and verified doctors near to them. So, we have developed a platform where people can easily connect with verified doctors near to their area by searching for doctors on our platform based on location.
The people of remote areas even big city people don't know about the latest medical schemes provided by the government. So, they can't use these very crucial medical schemes for their own. Our project will aware all patients about government medical schemes with eligibility criteria.
Their are so many people who are handicapped and faced difficulty in going to the hospitals for regular checkup of basic body parameters. Our project have IoT based box (a wellness device), which will help patients to have their normal body parameters reading at their own home and they can share their readings with doctor.
What it does
This project is for all those peoples who live in remote areas, valleys, hills, for those who are often move from one city to anoher because of buisness meetings and other things. All these peoples do not know about the availability of doctors, hospitals, clinics near to them. Even in case of COVID-19, this software is best to search doctors, hospitals, medical shops and clinics near to them. On MEDI-BOOK, patient can search doctors based on location selected and specilization of doctors. The major advantage of this web application is that peoples can see Government provided Medical Schemes very easily. This feature is not available on any existing projects. This software also have chat system through which patient can send their symptoms, previous medical reports and readings from MEDI-BOX to the selected doctor of any country and doctor from their end can prescribe patient very easily. Patients can have their MEDI-BOX readings on this software. Pateints can book appointments of any doctor. One of the major feature of MEDI-BOOK is that it will show live tracking of COVID-19 cases and news on it for the sake of patients and every time new case occurs in the area of patient, he/she will get notification of it automatically. If we see on larger picture, this software will going to help a lot to the world if we launch it.
With this, we have a wellness device "THE MEDI-BOX" which is a small box that can be connected with an android application and measures the human body parameters which includes "BODY_TEMPERATURE, PULSE RATE, ECG, HEART BEAT" and also "LIVE READING OF POLLUTION, AREA TEMPERATURE and HUMIDITY" of the area in which patient is currently stay, to check whether the current environment is suitable for the pateint or not. This box is easy to carry. All the readings will automatically send to cloud, MEDI-BOX mobile application and MEDI-BOOK software and these details will shared with doctor. We are now working to convert this box into a wearable band.
How I built it
It is built using basic programming languages and backend languages. I used thingspeak cloud for medi-box data storage and mysql for medi-book data storage.
Challenges I ran into
Sending real time data to cloud, but I made it.
Accomplishments that I'm proud of
Patients now will be aware about medical schemes which they can use for their own welfare.
Patients can easily connect with verified doctors near to their area.
Patients can have their wellness checking at their own home very easily.
What I learned
How to gather all data and use of web scraping also.
What's next for Self Aware
We will work on it and we are working on turning the medi-box into a wearable band and adding more functionality to them.
Built With
3d-designing
3dprinting
android-studio
arduino
bootstrap
css3
dht11
ecg-module
esp8266
firebase
google-maps
html5
java
javascript
jquery
lm35
mit-app-inventor
mq135
mysql
php
thingspeak
Try it out
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com | Self Aware | The project is for the remote areas people and handicapped people who faced difficulty to go hospital/clinic for regular treatment. This project made simple for them to connect with doctors from home. | ['Rishabh Gupta', 'VIVEK CHHABRA', 'Amit Goyal', 'Rajneesh chaturvedi'] | [] | ['3d-designing', '3dprinting', 'android-studio', 'arduino', 'bootstrap', 'css3', 'dht11', 'ecg-module', 'esp8266', 'firebase', 'google-maps', 'html5', 'java', 'javascript', 'jquery', 'lm35', 'mit-app-inventor', 'mq135', 'mysql', 'php', 'thingspeak'] | 16 |
10,338 | https://devpost.com/software/lazarus-network | Welcome To Lazarus Network
Inspiration
The real motivation for this project was to allow users access a Safer Internet wherever they are and whichever Device they use (From Smartphones to IoT Devices). From using 3rd Party Services and Self Hosted solution, I learnt about a lot of challenges in connectivity, security and most importantly privacy in VPN Systems. Hence we built a Decentralized VPN Services Marketplace where a common standard in the network would be followed across multiple service providers or self hosted solutions. Given the isolation currently being experienced due to the COVID-19 pandemic, almost all of the people are working from home and not all of them have access to the enterprise firewall in their homes. The most vulnerable are the startups and small businesses who would be soft target to phishing attacks, ransomware, malware or internet viruses. Hence we decided to work on a secure firewall which filters the internet based on blacklisted Websites/IP/domains and only allows the users to access safe websites.
What it does
We leverage AI and Blockchain Technologies For Cyber Defense to protect individuals and companies from cyber-attacks like ransomware, email spoofing, phishing etc. We help them by securing the network layer within their home/office so that all applications can only access authorized services and malicious services are blocked. Our technology can be used from our cloud and the companies can also choose to host it On Prem to save costs and have freedom to customize it as per their needs.
How We built it
We do this by Leveraging AI and Blockchain Technologies to create a Smart Contract based Firewall on the Network Layer for all devices connected to Home or Office Internet.
Our Products:
Lazarus VPN
Lazarus Firewall
Lazarus Blockchain
Lazarus Drive
Lazarus Stream
Lazarus VPN offers encrypted tunneling solution for end users offering WireGuard VPN Tunneling, secured by Ed25519 Private Key Encryption, Multi Region Network, Peer to Peer network access and a lot more.
Lazarus Firewall is incorporated on the network layer (DNS Layer) for detecting and eliminating cyber threats which try to attack the application system. Our system filters the web based on blacklisted Websites/IP/domains and only allows the users to access safe websites based on our database. We also would connect to 3rd party APIs to get more list of malicious domains and validate it across the Alexa rank to have it blocked on our network. We also enable users/administrators to create a database of whitelisted and blacklisted domains to improve the network overtime.
Lazarus Blockchain is the underlying technology for the smart contract and keep an immutable record of transactions in the network.
Lazarus Drive provides seamless data storage and sharing solution to the users. IPFS makes distribution of high volumes of data with high efficiency. The users would be able to host their data on the network of computers reducing the cost of storage.
Lazarus Stream Service offers Secure and Decentralized Live Video Streaming using IPFS. The stream will be more secure as it uses end to end encryption.
The decentralized network allows our users to stream content without any restrictions and reduce the cost of live Streaming. Lazarus Email and Teams solution is targeted towards the enterprise users who would want to track the data accessed within the network and protect the systems from phishing attacks.
Challenges I ran into
One of the major challenges we encountered was in handling the private keys for their account and we decided to change our UX and allowed the user to come with his own private keys for achieving better security in using our services. Another one was to create and deploy docker images for the specific services when the user creates a private network for his home/enterprise
Accomplishments that I'm proud of
Creating Lazarus Tunnel Solution. This allows any system to open ports on the local machine bypassing the firewalls and NAT to the Internet.
What I learned
A Lot:
Flutter,
GoLang,
Docker,
VPN Systems,
Firewalls etc.
and why decentralized systems are the future of Internet.
What's next for Lazarus Network
Launching Token Curated Registries for the Blacklisted IPs/Domains
Mobile Application
Streaming, Chat and Email solution.
Built With
blockchain
flutter
gcp
golang
google-cloud
javascript
php
solidity
Try it out
Lazarus.Network
app.lazarus.network
github.com | Lazarus Network | Safe Internet & CyberSecurity For All - Providing Cyber Defense solution to Individuals & Startups. | ['Seunghyeon (Patrick) Yang', 'Melany Hulianovych', 'Shachindra Kumar', 'Meit Maheshwari', 'Einstein Rojas', 'Anish Mishra', 'Gaurav Kumar'] | [] | ['blockchain', 'flutter', 'gcp', 'golang', 'google-cloud', 'javascript', 'php', 'solidity'] | 17 |
10,338 | https://devpost.com/software/teachthem-ghlw8i | Inspiration
This project is designed to promote continueous learning. There is no doubt that so many children and adult were restrained from acquiring knowledge that will mold them, as a result of covid-19 pandemic and restraining orders. Lots of extra curricular activities were placed on hold. Knowledge acquired through education goes a long way to produce lots of creative skills that can solve many problems. So this project was designed to prepare students to be fully equipped with all knowledge in our fast paced changing society.
What it does
Teachthem is an online space and app for shaping destinies online, offering quality education and creating room for employment.
How I built it
This was built online with programming language by Chinwendu #C++, site built on strikingly. Flutter integration, Adobe graphics, android studio.
Challenges I ran into
Poor network and power supply. We had to muti-task on high level. There were little support, but glad all were achieved
Accomplishments that I'm proud of
Site clearly states mission and vision of the whole idea.
What I learned
We must keep researching and building to transform so many things, for the future.
What's next for Everyday passion Academy
We hope to bring all activities to live with the right support.
Built With
adobe-graphics
android
site-built-on-strikingly.-flutter-integration
Try it out
bit.ly | Teachthem | Teachthem is an online space and app for shaping destinies online, offering quality education and creating room for employment. | ['Chinwendu Maduakor'] | [] | ['adobe-graphics', 'android', 'site-built-on-strikingly.-flutter-integration'] | 18 |
10,338 | https://devpost.com/software/earning-tips-and-trick-and-smart-phone-basic-information | Inspiration yes
What it does
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for Earning Tips and trick and smart phone basic information
Built With
app
Try it out
youtu.be | Earning Tips and trick and smart phone basic information | I am smart phone spaicilist and my work has been earning tips and tricks and explained the smart phone basic and earn the money and data entry facebook 3years old account and over 500 hundred friend | ['Monu Kumar'] | [] | ['app'] | 19 |
10,338 | https://devpost.com/software/patient-health-history-record-system-ekgbxc | Inspiration
poorpeople
What it does
Patient Health History Record System
How I built it
Flutter, DataLake and Bolckchain
Challenges I ran into
Help poor people in heath area
Accomplishments that I'm proud of
Finish the MVP
What I learned
Deal with data base
What's next for Patient Health History Record System
Government Health History Record System
Built With
blockchain
datalake
flutter
Try it out
github.com | Patient Health History Record System | We have developed a project for the health area that use to control of pandemic and be able to project future disease outbreaks through artificial intelligence and mathematical projection models. | ['Jose Alexandro Acha Gomes'] | [] | ['blockchain', 'datalake', 'flutter'] | 20 |
10,338 | https://devpost.com/software/automated-green-house-utcoa5 | This is the robot i mentioned
AUTOMATED GREENHOUSE.
As the technology advance , we saw it is important to bring new technology to agriculture where by products with high quality will be produce and also it helps to meet the market demand.Here in Africa we depend so much in Agriculture and automating Agriculture here will be a huge step forward.
Our green is able to manage the essential needs for particular crops grown for them to perform better, Greenhouse can then send all the conditions to the cloud where by you can login in anywhere you are to see what is going on. With the security also CCTVs camera can be installed and real time images send to the cloud in which it act like security for instance when the bulb is not functioning you can notice through the camera if you are away from the green house.
We use materials that was available to bring our idea to the table that is automated greenhouse a greenhouse ,with technical part we use Two Arduino .relay ..sensors ,Fan ,FRID and other components. Node mcu to send information to cloud.5G will really help us here in Africa to deal with Industry 4.0.
Challenge i ran into was so many but finance is worthy to mention. we do love tech and skills we already have.
Green house could function as expected so cool.!!
Anything can be achieved passion and hard work is only needed.
What is next for us is to add more components so as to use internet to send all the information from green house to the cloud ,5G will help here because it is faster so as to check what is going on without any delay.
we love Technology and hardwork with our passion we believe it will take us Far .
Other project
we also tried to do garbage collector robot i have attach an image with the greehouse.NB robot is still under improvement
-----we as starteq automation if we could find investors anywhere we are going automate Africa in whichever way----
Built With
ai
c
c++
hardware
iot
programming
sensors | Automated Green house | How about food security with 5G -technology? | ['limo patrick'] | ['Best Hardware Hack presented by Digi-Key'] | ['ai', 'c', 'c++', 'hardware', 'iot', 'programming', 'sensors'] | 21 |
10,338 | 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'] | 22 |
10,338 | https://devpost.com/software/amazon-sqs-uipath-integration-activities | Inspiration
The inspiration for development came from a problem of account migration process. We need to migrate accounts from one application to our internal app. but the issue was there was no direct way to insert data through backend due the rules that need to be applied while creating account through UI Only.
So now the data from backend was sent to SQS queue and RPA bot consumed the message and created the account via Ui automation
What it does
This Package contains below Activities
Connect SQS — This activity creates a connection object which can be passed to other activities to define connection.
Send Message — This Activity is used to send the message to SQS Queue.
Receive Message — This Activity is used to receive the message(s) from SQS Queue.
Delete Message — This Activity is used to Delete a message from SQS Queue.
Purge Queue — This Activity is used to Delete a message from SQS Queue.
How I built it
Activities were built using UiPath Activity Creator (a visual studio Extension )
Challenges I ran into
Making connection to SQS using .NET AWS SDK
Accomplishments that I'm proud of
These activities can be used in multiple scenarios and help RPA to leverage AWS's Cloud.
Some of the use cases can be
Found Here
and 2nd thing these activities are not available on UiPath AWS official Activity Package, so this is new .
What I learned
Use of AWS SQS
What's next for Amazon SQS UiPath Integration Activities
Built With
amazon-web-services
c#
sqs
uipath
Try it out
connect.uipath.com | Amazon SQS UiPath Integration Activities | Amazon SQS UiPath Integration Activities are developed to access AWS SQS queue via UiPath. | ['Shubham Pratap'] | [] | ['amazon-web-services', 'c#', 'sqs', 'uipath'] | 23 |
10,338 | https://devpost.com/software/castme-pdst1m | MainMenu
Motion capture demo
Female Avatar Professor teaching
Male Professor teaching
Presentation Screen
Front view from the back
front view from the middle
Customize Chareacter
castme.life website
Try it out here:
1 Intro Demo (2 min):
https://youtu.be/Xm6KWg1YS3k
Complete Demo:
https://youtu.be/1h1ERaDKn6o
Download pipeline here:
https://www.castme.life/wp-content/uploads/2020/04/castme-life%20Win64%20v-2.1beta.zip
Documentation to use this pipeline:
https://www.castme.life/forums/topic/how-to-install-castme-life-win64-v-2-1beta/
Complete source code (1.44 GB):
https://drive.google.com/open?id=1GdTw9iONLywzPCoZbgekFFpZBLjJ3I1p
castme.life website:
https://castme.life
Inspiration
Video lectures are present in abundance but the mocap data of those video lectures is 10 times ahead in the form of precise data. High quality and a large amount of data are one of the requirements of best argmax predicting ML models, so we have used here the mocap data. Despite the availability of such promising data, the problem of generating bone transforms from audio is extremely difficult, due in part to the technical challenge of mapping from a 1D signal to a 3D transform (translation, rotation, scale) float values, but also since humans are extremely attuned to subtle details in expressing emotions; many previous attempts at simulating talking character have produced results that look uncanny( two company- neon, soul-machine). In addition to generating realistic results, this paper represents the first attempt to solve the audio speech to character bone transform prediction problem by analyzing a large corpus of mocap data of a single person. As such, it opens to the door to modeling other public figures, or any 3D character (through analyzing mocap data). Text to audio to bone transform, aside from being interesting purely from a scientific standpoint, has a range of important practical applications. The ability to generate high-quality textured 3D animated character from audio could significantly reduce the amount of bandwidth needed in video coding/transmission (which makes up a large percentage of current internet bandwidth). For hearing impaired people, animation synthesis from bone transform could enable lip-reading from over-the-phone audio. And digital humans are central to entertainment applications like movies special effects and games.
What it does
Some of the cutting edge technologies like ML and DL have solved many problems of our society with far better accuracy than an ideal human can ever do. We are using this tech to enhance our learning procedure in the education system.
The problem with every university student is, they have to pay a big amount of money for continuing to study at any college, they have to interact with the lecturers and professors to keep getting better and better. We are solving the problem of money. Our solution to this problem is, we have created here an e-text data to human AR character sparse point mapping machine learning model to replace the professors and use our ai bots to teach the same thing in a far more intractable and intuitive way that can be ever dome with the professors. The students can learn even by themselves AR characters too.
How we built it
This project explores the opportunities of AI, deep learning for character animation, and control. Over the last 2 years, this project has become a modular and stable framework for data-driven character animation, including data processing, network training, and runtime control, developed in Unity3D / Unreal Engine-4/ Tensorflow / Pytorch. This project enables using neural networks for animating character locomotion, face sparse point movements, and character-scene interactions with objects and the environment. Further advances on this project will continue to be added to this pipeline.
Challenges we ran into
For Building, first of all, a studio kind of environment, we have to collect a bunch of equipment, software, and their requisites. Some of them have been listed following.
Mocap suite- SmartSuite Pro from
www.rokoko.com
- single: $2,495 + Extra Textile- $395
GPU + CPU - $5,000
Office premise – $ 2,000
Data preprocessing
Prerequisite software licenses- Unity3D, Unreal Engine-4.24, Maya, Motionbuilder
Model Building
AWS Sagemaker and AWS Lambda inferencing
Database Management System
Further, we started building.
Accomplishments that we're proud of
The thinking of joining a virtual class, hosting a class, having a realtime interaction with your colleagues, talking with him, asking questions, visualizing an augmented view of any equipment, and creating a solution is in itself is an accomplishment.
Asking questions with your avatar professors,
discussing with your colleagues,
Learning at your own time with these avatars professors
and many more. some of the detailed descriptions have been given in the submitted files.
What we learned
This section can be entirely technical. All of the C++ and Blueprint part of a Multiplayer Game Development. We have started developing some of the designs in MotionBuilder, previously we have been all using the Maya and Blender.
What's next for castme
We are looking for a tie-up with many colleges and universities. Some of the examples are Galgotiah University, Abdul Kalam Technical University (AKTU), IIT Roorkee, IIT Delhi.
Recording an abundance amount of the lecture motion capture data, for better training our (question-answering-motion capture data) machine learning model.
Built With
blueprint
c++
php
python
pytorch
tensorflow
unreal-engine
wordpress
Try it out
castme.life
github.com
www.castme.life
www.castme.life | castme | We are revolutionizing the way the human learns. We uses the Avatar Professors to teach you in a virtual class.Talk to your professors,ask questions,have a discussion with your colleagues in realtime. | ['Md. Zeeshan', 'Rodrixx Studio', 'Google Inc', 'Rodrixx One'] | [] | ['blueprint', 'c++', 'php', 'python', 'pytorch', 'tensorflow', 'unreal-engine', 'wordpress'] | 24 |
10,341 | https://devpost.com/software/lgmp | Inspiration
A few months ago during the Coronavirus pandemic, a new headline was brought up - "Why Farmers are Destroying Millions of Pounds of Food." The reason? Farms were losing their main customers such as restaurants, cruise, and carnivals as the country closed up. Now, farms had up to millions of pounds of food, but no one to take it. With no choice, farmers had to start destroying their crops.
The only people still buying fresh produce were supermarkets and consumers.
However, even supermarkets could not take all of the farmer's food as they had limited space. Thus, the only line of business left for the farm was the direct consumer. Even though they normally buy produce from supermarkets, buying produce directly from the farmer ensures freshness, a large quantity, and minimal interaction with the food.
Another big inspiration for us was the current state of unemployment. It shocked us that in the United States, 1 out of 10 people does not have a job, largely due to COVID-19.
The last big inspiration for us was the lack of volunteer hours available to high school students due to COVID-19.
When we starting thinking of ideas for this hackathon, we wanted to find a way to get small businesses to be able to sell their products and the unemployed to be able to have a means of making money again.
What it does
Loconomic Fulcrum allows local small businesses (such as farms) to list produce they grow, and also easily hire people for jobs such as the delivery of their products to the consumer. The unemployed (or even volunteers) can list their hours of work. Then, small businesses can look and select who they would like to higher for a certain job.
How we built it
We built the project using a Python web framework model called Flask. We used Python as our backend language, with HTML, CSS, and Javascript on the frontend. We used MongoDB to securely save all our data.
We used Bootstrap styles and its grid system in order to ensure our site was mobile-friendly. Heroku was used to host our app.
Our development server was a Raspberry
Pi
.
Challenges we ran into
The main challenge we ran into was organizing our code, due to this project being so big with lots of functionality, it also had LOTS of code in it- with a big file, it was hard to find bits of code and overall be able to map the flow of the application and we saw this problem the most when we joined all the parts of the code together. We got through this though by reorganizing the code so we could understand it better and fix the errors.
Accomplishments that we're proud of
Having a working user login/signup and email verification system
The small business being able to upload listings of their products and customize it by adding images and descriptions of their products so they make it appeal to the customers
People being able to upload and edit job availability effortlessly
Small businesses being able to hire easily and safely because they are provided a background check certificate of the person they are hiring
The ability for volunteers and students in need of volunteer hours to serve and help the community even during Covid-19
An easy to use, the user interface for searching and purchasing items
What we learned
We learned the importance of refactoring code, as well as the value of a good team and staying positive.
What's next for Loconomic Fulcrum
We plan to integrate the ability for one to use a credit card to pay the small business, as well as more user verification for businesses and workers.
Built With
bootstrap
flask
heroku
mongodb
python
Try it out
loconomic-fulcrum.herokuapp.com | Loconomic Fulcrum | Giving life to small businesses. | ['Rohan Vij', 'Diya Vij'] | ['1st Place PRIZES', 'Top 3 PRIZES', 'Top 10 PRIZES', 'AIRPODS PROS'] | ['bootstrap', 'flask', 'heroku', 'mongodb', 'python'] | 0 |
10,341 | https://devpost.com/software/merry-machine | MerryMachine Homepage
Get your news!!!!!!
Every time you turn on the TV to watch the news or scroll through a media website to read up on the daily, you might have noticed that almost everything is negative. Sometimes, this brings you down. At one point, you don't even want to know what's going on for the sake of keeping your mood up.
What if
you could change that. What if you could read something positive to boost your mood and show some of the good in the world? That is what
MerryMachine
is for!
Through this project, we have learned how to develop a Machine Learning model for text classification and how to develop a server on Heroku with a client on Github Pages. We faced many challenges such as developing our model and making our model accurate, fixing issues with WebSocket connections, and figuring out how to port our model to Heroku's small size on a free server.
Repo @
https://github.com/halihuang/Merry-Machine
Built With
css
heroku
html
javascript
jupyter-notebook
python
tornado
Try it out
halihuang.github.io | Best Main Prize - ML for Social Impact - MerryMachine | Are you tired of being depressed when watching the news? | ['Amar Maksumić', 'Hali Huang'] | ['2nd Place PRIZES', 'Top 3 PRIZES', 'Top 10 PRIZES', 'HYPERX GAMING GEAR'] | ['css', 'heroku', 'html', 'javascript', 'jupyter-notebook', 'python', 'tornado'] | 1 |
10,341 | https://devpost.com/software/colossal-tortoise | Main page of Colossal Tortoise. Lists jobs.
Shows this when clicked on one of the jobids. Shows more info about the clicked jobid.
Create/Edit Job menu.
Consent popup on using the user's processing power.
Inspiration
With the prevalent COVID-19, strong computing hardware is in high demand by scientists and researchers. Because of the disease, we are staying more at home, and consequently, using devices to browse the web a lot more. What if we could take advantage of the increased time spent at a browser and use the browser computing resources to solve the very problem that causes us to use the browser more?
What it does
Colossal Tortoise's purpose is to provide heavy processing power for scientists and researchers to run heavy parallel simulations like evolution simulations and protein folding. The processing power comes from the user browser device's cores. With many users using the browser, if the website appended the worker script tag to their website, they can join the Colossal Tortoise network and help many scientists and researchers fight diseases like COVID-19 by running many simulations and protein folding sessions.
How I built it
I built the frontend and backend using pure javascript, with the exception of some nodejs libraries.
Challenges I ran into
I ran into the issue of distributing the work. I learned to circumvent this by keeping a
jobs
variable and assigning a flag to see when will it finish.
Additionally, I ran into compatibility issues on iOS Safari. For some reason, the window load randomly fires on Safari iPhone 7 Plus. I figured out that
document.readyState
strangely is 'complete', even before loading the entire DOM. To solve this, I added an if statement for the
document.readyState === 'complete'
condition.
A small compatibility issue was that the iframe's onload on Safari doesn't render scrollHeight for some reason, so I had to setInterval to check for the actual 'loaded'.
Another compatibility issue was WebWorker nesting. On what platform did the compatibility issue arise? You guessed it. iOS Safari. I found out that you can WebWorker nest in Chrome but not on Safari. I solved this issue by having the WebWorker postMessage to the main thread on the request of creating another WebWorker.
Accomplishments that I'm proud of
I'm proud that this project has the potential to both utilize the idleness of the cores in our devices and support scientists and researchers at the same time, all while giving the opportunity for the user to contribute to the scientists and researchers who are working on products that change our lives.
What I learned
Worker management, distributing workloads across many remote cores, and using the
express-ws
library. For the workers, I learned how to use WebWorkers.
What's next for Colossal Tortoise
If the popularity of Colossal Tortoise increases, there is likely to be abusers who will send false results back to the server or spam the job creation form. To circumvent this, there will be a feature that requires captcha verification to submit a job (not to edit a job though) and a result verification function that is optional for the programmers to program in their simulations.
Potential
There is just an infinite amount of possibilities for utilizing the browser supercomputer. You could run algorithms, simulations, support a blockchain network, and anything that is supported in javascript. The limit is just two things: the developer's imagination, and the Colossal Tortoise network.
More details
All the holistic details can be found in the GitHub repo on
https://github.com/scheng123/colossal-tortoise
Built With
express-ws
express.js
md5
node-fetch
Try it out
github.com
colossal-tortoise.tbt.mx
colossal-tortoise.tbt.mx | Colossal Tortoise | A browser supercomputer. Many user browsers all working together to compute a solution. | ['Simon Cheng'] | ['3rd Place PRIZES', 'Top 3 PRIZES', 'Top 10 PRIZES'] | ['express-ws', 'express.js', 'md5', 'node-fetch'] | 2 |
10,341 | https://devpost.com/software/actalytics | Inspiration
This project was inspired by our own political work and involvement, as well as the current movements that are occurring. Specifically, one of our team members was a volunteer with the Sunrise Movement, and was part of a campaign to bring renewable energy to Massachusetts. In order to achieve this, they wanted to contact political figures and tell them about the campaign; however, they were unable to find contact information for these figures, and the campaign was not as successful as it could be. In addition, there are numerous movements that are spurring at the moment, and we wanted to create a platform to aid those who are stepping up. Overall, after intensive research and brainstorming, we realized that campaigns don't use the same data driven insights and tools available to startups, we wanted to bring our data science knowledge to create the activism of the 21st century.
What it does
Actalytics provides key performance metrics and recommendation to guide strategy for campaign organizers. The primary feature of our beta release was ranking the probability of voting on climate action for MA House of Representatives. We came up with a score for each rep, and display the top 5 most likely to engage with a climate campaign. Also, Actalytics tracks key metrics for each outreach channel (email, direct confrontation, print campaign, strike) to provide feedback on the most effective methods of escalation and confrontation. We hope to expand into a full fledged campaign management tool, with contact management, relationship tracking and email bots.
How we built it
Like most data science, most of the work was data collection and cleaning. We wanted a broad range of features and had to scrape (using scrapy spiders) from a lot of sources. After that, we used pandas and numpy to clean, combine, and format (lengthiest part) into model-ready form. Flask backend with html/css/js created the actual platform, using data from the LogisticRegression model made in sci-kit learn.
Challenges we ran into
We wanted to try collaborative filtering for the recommendation system, but we could not find enough bills with public voting record to get any accurate results. Also, integrating the model into the front end was also a challenge, since we did not do such things in the past. Finally, developing the front end required much thought because we had to think about how the user would approach the page and how they would react, so that we could allow the website to be user-friendly.
Accomplishments that we're proud of
We're proud of learning scraping quickly, as we previously didn't have those skills. Our knowledge of Flask integration also increased. Making the model obtain a relatively high degree of accuracy was quite nice as well, and overall, we were able to acquire many new skills.
What's next for Actalytics
We really hope to expand our model beyond the one use case of climate in Massachusetts House. Going nationally, for all areas of activism, for both the senate and the house will drastically increase our attainable user base. Of course, the platform needs to be filled out as well, but there's a lot more data collecting to be done to expand beyond this Proof of Concept.
Built With
flask
html/css/js
numpy
pandas
scikit-learn
scrapy
Try it out
github.com | Actalytics | An innovative platform that provides data-driven profiling of legislators, encouraging activists to speak up regarding concerning issues. | ['Riya Bhatia', 'Samarth Agrawal', 'Julian Dai'] | ['Top 10 PRIZES'] | ['flask', 'html/css/js', 'numpy', 'pandas', 'scikit-learn', 'scrapy'] | 3 |
10,341 | https://devpost.com/software/bah_biotrack_conqueringcovid-19 | Homepage
Login Page
Plan Page (1)
Plan Page (2)
Discussion Page
Understanding COVID-19 Page (1)
Understanding COVID-19 Page (2)
Understanding COVID-19 Page (3)
Destress Page
Register Page
Seek Immediate Help Page (1)
Seek Immediate Help Page (2)
About Us Page (1)
About Us Page (2)
Inspiration
We personally felt that very little attention has been paid towards mental health during the COVID-19 pandemic. This is further demonstrated through the lack of funding that goes towards improving mental health compared to the funding that goes into health care. As a result, we took the initiative to develop a website that people who are struggling with mental health can use to improve their mental health, meet new people, and reduce stress.
What it does
Our website has several features that help users stay informed, involved, and prepared:
Plan: Users can develop a plan for themselves to help them accomplish their goals and understand what needs to be done to accomplish these goals.
Discussion: Users can talk to one another, enabling them to interact with people they don't know.
Understanding COVID-19: Users can learn more about the symptoms that one experiences if they were to be infected. They can also learn about precautions they can take as well as the effectiveness of these precautions.
Destress: Users can apply the de-stressing techniques from this page to relax whenever they feel too much stress or pressure.
Seek Immediate Help: Finally, if someone were to need immediate help from a professional, there is a page with all the important information and hotlines that they can use.
How we built it
We first developed the webpages using html. Then, we used Python and Flask to make certain pages interactive for the user such as the discussion page and planning page. In order to develop the login and register system, we used postgreSQL and the database we used is on Heroku.
Challenges we ran into
We often ran into challenges related to the homepage, Python, and SQL. For the homepage, we wanted it to look aesthetically pleasing for the user and interesting, so we wanted to add icons that the user could interact with on this page. It was difficult to position the icons and make sure that they were in the right spot. Additionally, we facd challenges with the Python code as we often found it hard to work and display to the user the way we wanted it to.
Accomplishments that we're proud of
We are proud that we were able to make a website that looks clean and professional. We are all beginners to hackathons, and we all have less than 1.5 years of coding experience, one of our members has 0 years of experience. We were glad to be able to work together and learn from one another to develop a project that we are proud of, despite the outcome.
What we learned
We learned a lot about COVID-19 and its affect on mental health. When we originally started this project, we were brainstorming ways to help people learn more about how to prevent the disease and create a system to mark certain areas as high risk, but then we found articles on how mental health across USA has been terrible, yet the US government has done very little to help mental healthcare.
Additionally, we learned a lot more about HTML, CSS, Python, and SQL. We learned about different ways we could implement it effectively and efficiently.
What's next for ConqueringCOVID-19
We hope to continue developing the website and make certain pages look cleaner. We hope that we can make the website go public, so that people could use this website to improve their mental health. We plan on working on this project further in the next 2 months and make this website accessible for anyone to use.
Built With
css
flask
heroku
html
postgresql
python
Try it out
github.com | Best Main Prize - BioTech/Health - ConqueringCOVID-19 | With this website, our goal is to aid people in the process of improving their mental health by helping people regain structure in their lives and improve confidence in themselves moving forward. | ['Suhanth Alluri', 'Risab Sankar', 'Nate Kattady', 'Chadvik Maganti'] | ['Top 10 PRIZES'] | ['css', 'flask', 'heroku', 'html', 'postgresql', 'python'] | 4 |
10,341 | https://devpost.com/software/vigil-rw68fs | System Architecture
Mobile Application for users
Mobile Application for users
Web Application for authorities
Inspiration
Currently videos are recorded through CCTV cameras, and manual surveillance is undertaken which requires a lot of human intervention and there is no facility for real-time emergency support. The services provided are excruciatingly slow which can have very bad result in cases of accident or fire etc. leading to several deaths around 100,000 annually and excessive loss of property.
What it does
Speed up the deliverance of services
Use an Anomaly Detection Deep Learning model
Detect events such as fire, robbery, accident.
A mobile application for the citizens
A web application to monitor the intensity and service request.
Crowd–Source to reduce false alarms
In a nutshell, saves life in situations where every second counts.
## How I built it
Proposal to speed up the deliverance of services and help like, Police Backup in case of theft and robbery, hospital aid in case of accidents etc. via IoT coupled with Fog and Cloud Architectures, and effective surveillance. Various unusual events are detected (with the help of Deep Learning techniques) sourced from single static cameras and notifying the concerned authorities about the event with its timestamp and additional details like extent of damage, parties involved and location which assist the authorities in identifying the cause of the anomaly and take necessary action. The anomalies proposed to be detected include:
• Abrupt Fire
• Accident
• Burglary
• Physical Assault
• Robbery
• Shop Lifting
• Traffic Rules Violation
In case of events requiring an immediate attention, we propose to notify the crowd in the vicinity of the region where the event has occurred so that they can voluntarily choose to help which can minimize latency in saving a life or even catching a perpetrator.
Challenges I ran into
Acquiring Dataset
Heavy Computational power
## Accomplishments that I'm proud of
Able to achieve a low false rate of 1.9, which allows classifying most of the anomalies correctly.
What's next for Vigil
Integration Fog Computing for decreasing latency.
Deploying on real ground.
Built With
css3
flask
html5
opencv
python
react-native
tensorflow | Best Main Prize - Machine Learning - Vigil | Life saving application capable of recording and providing immediate help for 13 different anomalies ranging from accident, theft, assault to arson,burglary and kidnapping. | ['khanzaifa37', 'Aniket Singh'] | ['Top 10 PRIZES'] | ['css3', 'flask', 'html5', 'opencv', 'python', 'react-native', 'tensorflow'] | 5 |
10,341 | https://devpost.com/software/project-oogway-zsc374 | Main Page
A directory on what features our website has
About Page
Our Mission statement and our mascot
Thanking someone who helped design our logo
Team
Resources to help the ocean
Ways you can change to help save the ocean
Our AI chatbot, G-Bot, in action!
Charities and organizations that also share our mission. has links to check them out and donate
Inspiration
As a group of high schoolers, we discovered a very serious problem with our planet Earth. The ocean part of our planet is getting destroyed by chemicals by the moment, yet there is barely enough awareness about ocean acidification, and I am willing to bet that most of you don’t even know what ocean acidification is! In addition, there’s common things like rising sea levels, plastic pollution, and overfishing. On top of all that, 8 million metric tons of plastic waste enters the ocean every year, posing a health hazard to all marine wildlife. Most importantly though, we realized that it is not us who are at fault for not caring about the ocean. People are not educated on those topics in general, and as a result they find no reason to help contribute to this cause.
What it does
Our solution? Project Oogway. We designed a website that raises awareness about the current issues the ocean is facing with fun and interactive visuals as well as an AI Chatbot that is our tour guide for this website and has a collection of ocean puns that it can tell! Our goal is to make marine conservation an easy and fun topic to approach so people can get more involved and ultimately halt all the issues the oceans are facing, and hopefully reverse them so we have a healthy ocean again!
How we built it
We built the website using mostly html/css, and there is a little bit of javascript. Our AI chatbot was built using Twilio, which is in json, and we were able to integrate it with Whatsapp using Twilio's built-in Whatsapp api. For certain features of the bot, we built a python backend with the flask framework.
Challenges we ran into
One of our team members fell ill at the beginning of the project
Another team member got his computer taken away by parents
Limited experience in all the languages and tools we used
Accomplishments that we're proud of
We learned git, which was new to us
We linked several html pages together
We were able to import fonts that are not built into html by default.
We built a Whatsapp AI chatbot with Twilio
We used flask for the first time to integrate python functions onto twilio's bot
What we learned
During the school year, week-long hackathons are really a rare sight, and this is our first time experiencing something like this, so here are some thoughts. First off, having a week to work on our project allowed us to be more relaxed and actually take the time to understand the skills we need for our project. The downside however, is that we can’t pull all nighters like we would in a 24 hour hackathon, and therefore we had to really schedule our time well to stay on track and motivated. Secondly, it is really difficult to solve problems together when we can’t just go over to their screen and find little things they didn’t catch. The concentration issue is even worse when we are trying to find snippets of time where we would be able to call and do progress check ins. Last but not least, being at home means we must still do our daily activities like SAT test prep, taking care of our pets, spending time with our family, etc, so we were not able to spend as much time on our project as possible. Overall though, all three of us would admit that we enjoyed this hackathon the most compared to our past experiences, as it was more challenging from both life and knowledge, but also pushed us towards self discipline and self study.
What's next for Project Oogway
As Wren from corridor digital once said, “no film is ever finished, it just gets released”, our website is also the same. We have poured a lot of hard work into this website, and if you check on us a few months later, I bet you would be able to find some new features, including but are not limited to:
the addition of a google maps api and load some GeoJSON data into it so it displays markers on the locations of sea turtles or plastic.
allow users to create accounts, and incentivize it with rewards so it increases user interaction with our website.
some ocean related games with javascript for our younger audience to spark interest for ocean conservation at a young age.
Built With
css3
flask
html5
javascript
python
twilio
Try it out
github.com
docs.google.com
www.twilio.com | Project Oogway | A website with the purpose of inspiring people, educating the public, and changing our habits to help reverse the damage done to the ocean. | ['Riley Chou', 'Damian Yang', 'Arthur Hua'] | ['Top 10 PRIZES'] | ['css3', 'flask', 'html5', 'javascript', 'python', 'twilio'] | 6 |
10,341 | https://devpost.com/software/sign4good | Hand tracking
GIF
Working Gif
GIF
Multi Gesture Translation
GIF
Words to Try: Yellow
GIF
Words to Try: Red
GIF
Words to Try: Green
GIF
Words to Try: Bright
GIF
Words to Try: Opaque
GIF
Words to Try: Light-Blue
Inspiration
Today, around one million people use Sign Language as their main way to communicate, according to
https://www.csd.org/
. We decided to create an application that will help bridge the gap for those who have impaired hearing. Additionally, it also helps people who do not know sign language. Using this app, communication will be easier for both parties and people who have their voices drowned out will have a way to speak up.
What it does
Sign4Good allows users to sign a word (full gesture) which is then translated into text. This allows people to communicate without having to fully learn sign language
How I built it
The hand tracking application was built with opencv. It segments the hand from the frame using masking techniques. The translation of the sign is done using a deep neural network that uses a CNN which recognizes the features of the image. These features are then fed into an RNN which checks the differences between high level frames.
Model: "sequential_1"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 256, 256, 32) 896
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 128, 128, 32) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 128, 128, 64) 18496
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 64, 64, 64) 0
_________________________________________________________________
conv2d_3 (Conv2D) (None, 64, 64, 128) 73856
_________________________________________________________________
max_pooling2d_3 (MaxPooling2 (None, 32, 32, 128) 0
_________________________________________________________________
conv2d_4 (Conv2D) (None, 32, 32, 256) 295168
_________________________________________________________________
max_pooling2d_4 (MaxPooling2 (None, 16, 16, 256) 0
_________________________________________________________________
reshape_1 (Reshape) (None, 16, 4096) 0
_________________________________________________________________
lstm_1 (LSTM) (None, 16, 64) 1065216
_________________________________________________________________
lstm_2 (LSTM) (None, 16, 32) 12416
_________________________________________________________________
lstm_3 (LSTM) (None, 32) 8320
_________________________________________________________________
dense_1 (Dense) (None, 6) 198
=================================================================
Total params: 1,474,566
Trainable params: 1,474,566
Non-trainable params: 0
_________________________________________________________________
Challenges I ran into
Segmenting the fingers from the hand in the hand detection
Handling the large amounts of data
Accomplishments that I'm proud of
Being able to achieve a model with high accuracy
Segmenting fingers for the hand tracking
Supporting multi gesture translation
What I learned
Working with Video Detection
Limitations:
Due to the nature of sign language, some gestures closely resemble others and because of this our current model has some difficulty recognizing words like opaque and green. Since they both have a similar gesture when looked at from the pov of the masked pink glove.
At the moment Google’s mediapipe supports only single hand detection. This prevented us from training on gestures that require both hands. Mediapipe is an open source software that has a very good tracking algorithms implemented. As soon as it supports dual hand recognition this issue can also be resolved.
What's next for Sign4Good
Train using more words
Train using different sign languages
Dataset Used
Sign Language Used
Built With
artifical-intelligence
google-mediapipe
keras
opencv
python
tensorflow
Try it out
github.com | Best Main Prize - ML for social good - Sign4Good | Sign Together 4 The Better. Bridge the gap for the determined and their obstacles. | ['Zafir Khalid'] | ['Top 10 PRIZES'] | ['artifical-intelligence', 'google-mediapipe', 'keras', 'opencv', 'python', 'tensorflow'] | 7 |
10,341 | https://devpost.com/software/vigil-6udnxj | Introduction
The Problem
What Vigil stands for
Vigil's Solutions
Vigil's Target Market
What Vigil needs for it to function in the future.
A demo of Vigil
Summary
Inspiration
Because of the current covid-19 pandemic, staying safe, alert, and healthy is more important than ever. Being aware of which locations have been affected by covid-19 as well as knowing if you are at a high risk of exposure may be difficult to figure out, which is why Vigil was created.
What it does
Vigil is an app that showcases covid-19 hotspots as well as alerts users how prone they are to covid-19. Using the user's address as well as their recently visited locations, the app alerts the user of their exposure, provides medical centers and hospitals to get covid-19 tested, and displays a map of high-risk locations in their radius they should steer clear from.
How I built it
Using Java, I created a program that detected how prone a user is to covid-19. First, the program uses a scanner and takes in the address of the user. The program also has 2 text files, one text file detailing the number of covid-19 patients, and another text file detailing the total population of their address (city). Using a buffered reader, the program reads the file and puts it into two Hash Maps.
After doing so, the program calls the Hash Maps and based on the user's address, it takes the total number of covid-19 patients in the location and divides it by the total population of the location. The program then provides an answer of how prone a user is to covid-19 and recommends whether or not they should get tested.
To build the graphics of Vigil, I used the prototype platform, Framer.io.
Challenges I ran into
One challenge I ran into in my code was figuring out if I should use two Hash Maps or one and which one was more efficient. With one hashmap, I would have to create a hash map within another hash map, which would be more time-consuming and would take more code. I ended up using 2 hash maps instead, as it would be easier to keep track of the addresses information.
What's next for Vigil
In the future, I plan on increasing the efficiency of Vigil and using the Johns Hopkins covid-19 interactive map for more accurate information. I also plan on making Vigil a 501(c)(3), making it available and free to all users.
Check out the presentation up above (next to the video) to learn more about the business aspects of Vigil as well as its future!
Built With
framer.io
java
Try it out
github.com | Best Main Prize - Healthcare - Vigil | Vigil is an app that showcases locations that have been affected by covid-19. | ['Vineeta Muvvala'] | ['Top 10 PRIZES'] | ['framer.io', 'java'] | 8 |
10,341 | https://devpost.com/software/best-echoar-hack-societal-change-plantar | Login Page
Registation Page
AR Garden Selection Options
AR Garden
Market Place
Market Place - Cart
Market Place - Successful transaction
echoAR dashboard
echoAR dashboard- 2
Inspiration
30% of the Earth is covered in forests, but around 50 thousand square miles of it is lost.Whereas games like Farm Ville made over a $100M. So as to tackle this major problem we bring to you PlantAR an AR based garden farming game which allows you to help increase afforestation and reforestation.
What it does
This app has a built in AR garden which the user can populate using seeds.
Once the seeds are planted they need to be grown using rainfall.
The seeds can be bought in the in-game store which allows both in-game cash as well as external payments.
Out of every purchase made by the player a certain amount is given to an NGO which then plants an actual tree for the same.
How We built it
We used Unity along with Vuforia package for Augmented Reality. We further used ARCore for spawning models. We used echoAR for spawning the models. We also used firebase for user authentication.
Challenges We ran into
Unity Collab crashed while working making it harder to collaborate and co develop.
We had to figure out echoAR from scratch to use.
Accomplishments that I'm proud of
Having completed a prototype of an AR game like farmville.
Implemented a Market Place with Cart functionality.
What We learned
We got to understand how to make a simle market place using Unity.
We learned how to use echoAR for storing and loading models into Unity.
Learned how to develop a simple backend for the coin transfer.
What's next for Best echoAR Hack - Societal Change - PlantAR
A plant identification feature can be added to the game where you can click photos of plants and upload them to earn in game currency based on the rarity of the plant.
More plants can be added in the market place.
In the coming future this game can be given more of a realistic feel to it by adding seasonal plants and also allowing users to plant only based on the demographic they currently in, this will allow diversity in reforestation.
Built With
arcore
c#
firebase
unity
vuforia
Try it out
drive.google.com
github.com | Best echoAR Hack - Societal Change - PlantAR | Grow but not just for the Show - PlantAR | ['Wahib Kapdi', 'Abhijeet Swain', 'Akash Jha', 'Anshuman Singh'] | ['echoAR Challenge Prizes'] | ['arcore', 'c#', 'firebase', 'unity', 'vuforia'] | 9 |
10,341 | https://devpost.com/software/testtrack | Test Track Home Page
The Test Track Process
Inspiration
With the COVID-19 pandemic increasing in scale, testing has become extremely crucial in containing and tracking this virus. Recently, there has been a significant demand in testing and it has become extremely hard for people to find testing centers and efficiently get themselves tested. After reading these headlines every day, we wanted to provide a way to make it easier for the public to locate the closest COVID-19 centers and get tested right away in an efficient manner.
What it does
TestTrack is a website that will help people keep track of the coronavirus testing locations around their area. The website will prompt the user to type in their zip code or address and will call certain Maps API’s to locate the closest COVID-19 testing locations. We will also specify the wait time allocated with each close testing location in order for them to optimize their time and get tested as soon as possible. We will observe the wait times by using the google distance matrix api at the user’s particular time. The wait times depend on the time that the user uses the website; for a more accurate result, the user can also use the website right when they reach the center to see the wait times at that exact time.
How we built it
Website and Front End:
We used HTML code to build the basics of the website
Using CSS and JavaScript, we stylized our website and made it more contemporary in order to appeal to more people and make our website more professional.
We also used php and javascript validators to provide a contact section to our website, allowing the user to input any questions or notes they may have about our project.
Back End: Maps/Search Queries for COVID-19 Testing centers:
To display and configure a world map in our website, we used the Google Maps Javascript API. Using the Geocoding API, the search function converts an address or zip code to longitude and latitude coordinates (using an HTTP request). Another API we used is the Places Search API, that showcases the close proximity COVID-19 testing locations within a specific area. Using the Distance Matrix API to Calculate waiting times..
Challenges we ran into
Integrating 3 different APIs was a difficult process for us because we had to make sure all of them were in the right order. It was also difficult establishing the correct margins and troubleshooting several times to achieve the best view and layout for our website. Also, while integrating api's, it was difficult to combine them into our html code and it took a while for us to achieve what we wanted.
Accomplishments that we're proud of
We are proud of all that we have learned from TestTrack, from Google API's to Php servers. In addition, we are proud of the idea that we had to help all of the people around the world deeply affected by this pandemic and how our simple idea can in fact change some lives around our nation.
What we learned
After this week, we learned a lot about API’s, libraries, Php systems, and other important systems and elements of coding that we wouldn’t have known about before. We are mainly proud of what TestTrack has taught us in terms of website design, libraries, etc and we wish to take that with us to further projects.
What's next for TestTrack!
Once we become sure of the fact that our website works for everyone around our nation, our goal is to make TestTrack into an app in addition to our website. Through this, more and more people can have access to our project and we can further help people around the US get tested as soon as possible and find their desired testing center within minutes. In addition, we wish to further develop our wait times software and make it more functional to regular public in order for them to use it with ease.
Built With
apis
css3
google-maps
html5
javascript
libraries
php
Try it out
github.com | TestTrack | A website to track the nearest COVID-19 center testing sites. | ['Aarushi Ramesh', 'Aishwarya Ramesh'] | ['Best Beginner Hack PRIZES'] | ['apis', 'css3', 'google-maps', 'html5', 'javascript', 'libraries', 'php'] | 10 |
10,341 | https://devpost.com/software/speak-now-yd87ht | Grid of the alphabet
Shows words startting with "H" after the "H" button is clicked
Suggested words
Add a new word
Inspiration
I was inspired by a relative who had suddenly started showing signs of uncontrollable motor movements (such as in Parkinson's Disease), which meant that soon she was not able to communicate using word of mouth as fluently. Most of the time, those who would take care of her, were not able to understand what she was trying to convey, and the situation quickly spiraled out of control. When I went to visit her, I had thought of a contraption to help communicate with her: using a simple word bank in which she could pick-and-choose what word or message she wanted to convey. This greatly improved her communication dynamics with those around her. Because this idea was an instant hit, I decided to digitize the process.
What it does
The app comes with a pre-made dictionary of words which would be common for people with her condition, however, this list can be edited. The first tab contains a grid of the alphabet. If a letter is clicked, it would show a drop-down list of all the words that start with that letter. The user can click on any word shown if requested by the patient. This system is like a physical dictionary; where all the words are sorted in their specific letter category (ie starts with A, or B, etc). This makes the process of choosing a word more convenient, organized, and efficient. The next tab is a "Suggested" tab that takes into account the most-clicked words and the time of the day and uses NLP to display the 12 most relevant words at that time. This serves as a quick-access panel. The 3rd and last panel simply serve to edit the dictionary; if the patient tries to convey a word that doesn't exist in the list, the person using the app to help communicate can easily add it for future use.
How I built it
I built this version using Java in Android Studio and Firebase to use my NLP model. I am currently working on a version that works cross-platform as well.
Challenges I ran into
I ran into issues into creating my NLP algorithm, but I ended up fixing all my issues. I also had trouble for a long time integrating it with the frontend, but I finally got it to work on time.
Accomplishments that I'm proud of
I'm proud that I have created a functioning app that is actually tested and is being used by several people. I am also excited that I was able to integrate NLP into this app.
What I learned
I learned how to use file storage for storing each user's custom settings, how to use NLP and integrate it into an app, and how to start beta-testing. I feel that getting Beta Testing is one of the most important aspects of this project because it proves that the app and the concept actually works well.
What's next for Speak Now
Next, I am planning to contact doctors and have even more people test it so I can have a greater understanding of how I can remove the communication barriers of disabled patients.
Built With
android
android-studio
java
Try it out
github.com | Speak Now | Speak Now uses Natural Language Processing to help those who are verbally disabled communicate with others. | ['Shreyas Rana'] | ['Best Solo Hack PRIZES'] | ['android', 'android-studio', 'java'] | 11 |
10,341 | https://devpost.com/software/visiblur-029ve7 | Inspiration
With social media platforms and other news outlets being incredibly public, videos oftentimes must be anonymized before posting in order to preserve the identities of bystanders, minors, and those who do not consent to being in the video. By providing a platform that gives users the option to detects and selectively blurs out faces in videos, we can bring attention to important issues and allow users more freedom with sharing their videos, while still taking less time and resources than manual video and photo editing.
What it does
This project is a web application that aims to provide robust and quick sensitive information processing in images and videos. After processing a file through ML model, the user can manually choose which information to blur or not blur. The user can then download the anonymized video from our site.
How we built it
We split this project into front-end and back-end components. For the back-end component, we leveraged Flask and the Pytorch machine learning pipeline where we used Facenet to detect faces then ran it through an unsupervised clustering pipeline (UMAP and DBSCAN) to identify unique faces in the video frames.
Challenges we ran into
Because video files and processors can take up a lot of space, we faced issues with memory usage and processing speed, which we were able to fix by hosting our project on AWS and utilizing a file wrapper/processor. We also initially ran into challenges with multiple edge cases when processing with our ML model.
What I learned
We learned a lot about the PyTorch library, and were able to explore the diverse functionalities and freedom that it provided us. We also learned a lot about video processing and how to increase the efficiency of the processing.
What's next for Visiblur
In the future, we hope to incorporate an option to also detect and blur out sensitive information displayed in the video.
Built With
bootstrap
dbscan
facenet
flask
python
pytorch
umap
Try it out
github.com
ec2-3-129-74-29.us-east-2.compute.amazonaws.com | Visiblur | Protecting Your Identity: Selective Facial Blurring | ['Luvena Huo', 'James Wang', 'Cheryl Cai', 'Angela Zhang'] | ['Best Undergrad Hack PRIZES'] | ['bootstrap', 'dbscan', 'facenet', 'flask', 'python', 'pytorch', 'umap'] | 12 |
10,341 | https://devpost.com/software/best-beginner-hack-financial-technology-sbconnect-yc4dot | Inspiration
Our inspiration for this project was to create a website to help the small businesses affected during the coronavirus pandemic. Many small businesses have lost customers and we wanted to make something that would help them.
What it does
It is a website for small businesses to advertise and link with other small businesses. It is also an easier way for customers to shop from small business. The businesses are sorted into categories, which make it easier for users to browse.
How I built it
We built this website using HTML and CSS. Each page has its own unique code and styling.
Challenges I ran into
Some challenges we ran into included making the form for the publish page, as well as designing each page and making sure the layout looked nice. Another struggle was keeping the video in the 3-5 minute limit.
Accomplishments that I'm proud of
I am proud of learning new HTML and CSS throughout the course of this week. I learned how to make a form in HTML as well as many CSS attributes that contributed to the look of the website.
What I learned
I learned a lot about the process of making a website. It showed me how much trial and error there is behind every step of the way, how important it is to be precise, and how little mistakes can affect the whole website.
What's next for Best Beginner Hack - Financial Technology - SBconnect
We hope to expand and improve the functionality of our website. We want to make it so that the website can automatically upload information onto the browse page.
Built With
css
html5
Try it out
atdpsites.berkeley.edu | Best Beginner Hack - Financial Technology - SBConnect | A website for small businesses to advertise and link with other small businesses. The businesses are sorted into category to make it easier for the users to browse. | ['Aditi Sethi', 'Shuban Sagar', 'Anushka Bora'] | ['RAFFLES', 'SWAG'] | ['css', 'html5'] | 13 |
10,341 | https://devpost.com/software/c-trac-sxocie | Website Home Page
Mobile App - Home Page
Tag Location for Covid-19 Safety
Review Location Safety
Inspiration:
When we learned that 6.15 million people in the world have contracted the novel Covid-19 disease and 374,000 people have died of Covid-19, we were shocked. Even though so many people are getting infected, many people still do not follow the social distancing rules or wear face masks in public places, and this is not just a concern of mine, but for many other people also. This very clearly causes more community spread and leads to more Covid-19 cases, we wanted to help people from being infected from the Covid-19 through an online platform that would control and display is places were following social distancing guidelines.
What it does:
Our mobile app, C-Trac, has two main components: an accurate database of information about public locations following Covid-19 safety rules and the ability for users to tag/leave reviews about locations. As we could not complete the mobile app development, we created a website with a built-in calculator that can show the risk of getting infected by infectious diseases. The calculator takes three inputs - A location's number of Covid-19 infections, deaths, and if your location is following the Covid-19 rules. It then calculates (just a prototype) whether your location is at risk.
How we built it:
We built this website using HTML, JavaScript, and CSS. In addition, we also incorporated google maps. This website is an extension of our mobile app (conTrac). Since we could not complete the mobile app, this website that we started working on this morning contains a prototype of what we would build in the future. To understand what the app would look like, we made a Canva mock-up.
Challenges we ran into:
When we were building my website, we ran into data issues where we could not get Covid-19 infection rates and death rates accurately. We ended up asking the user to enter this data. Writing JavaScript functions was tricky since we were not too familiar with it. We have never coded from scratch before, and we usually use drag-and-drop platforms like Thunkable and MIT App Inventor to code apps. We are just getting started with HTML, CSS, and Javascript and we used W3 school's blog and other online resources to understand how to code.
Accomplishments that we are proud of:
We are proud of developing a solution for consumers to safely visit a location knowing it is safe to go. We are also proud of ourselves for creating a website in little time and for helping people for being exposed to an infectious disease. Over the past week, we surveyed over 50 friends and family to confirm the need for an app like C-Trac. The survey validated the problem of not having access to data regarding Covid-19 safety at public locations. We also developed mock-ups to visually represent how my mobile app would look like and work. Validating the user needs and developing the mocks were the most important steps to build my app.
What we learned:
We learned how to use javascript within HTML. We tried using Google Maps. Also, we learned how to use Canva for building UI mocks which we enjoyed. When we first started this competition, we thought we could not finish, but we did it. Doing this competition helped me believe in our teamwork.
What's next for C-Trac
For the app development which will be named conTrac, we plan to learn how to use Swift and xcode and start using it next week. For the users, currently, we don’t have a way to verify if the reviews left by a user are true. In the future, we want to include a leaderboard that showcases and highlights users of C-Trac that are very active and provide the most valuable feedback.
Built With
creativetim
css
google-maps
html5
Try it out
github.com | Best Beginner - Health Solutions - CTrac | Come together to control the spread of coronavirus | ['Ad J', 'Risha Jain'] | [] | ['creativetim', 'css', 'google-maps', 'html5'] | 14 |
10,341 | https://devpost.com/software/covid-network | Landing Page
Login Page
Maps page where you can see where you had your encounters
All your logs
Dashboard
Health Related News
Covid statistics by country
Disarmed Stage(Dark Mode)
Disarmed Stage(Light Mode)
Login App
Armed Stage(Light Mode)
SignUp App
Data page on app displaying encounters and location
Inspiration
As we saw many people in our community and the rest of America not following social distancing guidelines, we wanted to create an app that made sure people stay safe and follow these guidelines. We wanted to make sure the surge of cases reduce so that our lives can return to normal.
What it does
Our app and website have a variety of features. When you press the arm button on the app, it will start collecting data via Bluetooth. Whenever you walk past someone it logs it so you know how many encounters you have had. As well as logging the number of encounters, it gets your exact location as well, so it plots it on a map you can later see on the website. It will tell you exactly how many encounters you have had in one location. Depending on how many encounters you have had per log, an icon will be shown(Checkmark, Warning, Danger), depending on how many encounters you have had per log. This will allow you to know if you should get tested or not depending on how many encounters you have had. On the website client, you can see where you had your encounters on a map, as well as how many encounters you have has per log. For example if I went on a trip to the grocery store, it will log all the encounters I had for that trip. And on the map, it will display the grocery store. We also have COVID statistics per country, as well as the latest health-related news.
How I built it
We built our app using flutter. Using different packages such as the vibrate package, the google maps, as well as the Bluetooth package, were able to create all the features we have. We adjusted the RSSID strength of the Bluetooth signal to adjust distance so we can get the closest to 6ft as possible. This guarantees you to follow social distancing guidelines. We used a google maps API that gets your exact location as well as plotting it and displaying it on the map. The website was built with VUE js which is a javascript framework. We used a News API for the health-related news and a COVID statistics API for the COVID stats data. We used firestore to store all the data for the backend. Both the app and the website were connected.
Challenges I ran into
Some challenges that we ran into was implementing the Bluetooth feature in the mobile application. It was hard for us to differentiate smartphone devices from other Bluetooth devices, but we found a way around that and were able to successfully implement the feature into our app. We also had some issues
Accomplishments that I'm proud of
My team and I are proud of all the features we were able to implement in a week. Its amazing to see how your phone vibrates and gives ding sound as you wall by someone. The fact that it also gets your location as well as plotting on the map is very cool as well.
What I learned
What's next for COVID Network
We hope to implement many more features such as notifications, reminders to wear your mask and many more features.
Built With
bootstrap
covidstatsapi
css3
firebase
flutter
google-maps
html5
javascript
newsapi
vue
Try it out
github.com
github.com | COVID Network | Arm Your Phone and Stay Safe | ['Shabd Veyyakula', 'Pranav Krishna', 'Holland Pleskac', 'Kushagra Singh'] | [] | ['bootstrap', 'covidstatsapi', 'css3', 'firebase', 'flutter', 'google-maps', 'html5', 'javascript', 'newsapi', 'vue'] | 15 |
10,341 | https://devpost.com/software/drivesafe-ai-driving-assistant | Step 5: Full detection of distraction/sleepiness, alert text, and alert sound playing constantly
Step 3/4: Eye localization, eye-aspect ratio monitoring, and face detection with bounds
Step 2: Face detection with bounds
Inspiration
After observing the community around us, we realized that there are greater than 6 million car accidents per year, and close to 23 percent of them end in fatalities. Car accidents are the second leading cause of death for teens, 87 percent of which involve distracted drivers. We created DriveSafe to tackle this problem and make an effort to reduce these numbers.
What it does
DriveSafe is an automated computer vision driving security assistant. It uses Deep Learning and Computer Vision to identify if and when a driver is distracted or feels sleepy, and accordingly alerts the driver and/or passengers.
How it works
The DriveSafe automated driving assistant was built through a 5-step cumulative process:
A stable, face-monitoring video stream was set up with the use of a webcam
The stream is fed to the laptop, which uses deep-learning facial recognition algorithms to detect the presence of the face in the stream
Once a face is detected, the algorithm performs eye localization and draws eye-shaped bounds around the driver’s eyes
An eye aspect ratio is determined and updated constantly based on the height of the top eyelid to the bottom eyelid.
If the height difference ever crosses a certain threshold (reduces) for a given amount of time, the driver is determined to be distracted or sleepy
Upon identification, a sound is played constantly until the driver is predicted to be focused
How We built it
DriveSafe was built using OpenCV, Python, deep learning facial recognition/object localization algorithms. The website was developed using HTML, CSS, and javascript.
Challenges I ran into
Implementing the face detection with eye detection made it so that there was a lot of lag between frames, leading to less consistent eye detection. We optimized the face detection to have it run a minimal amount of times, and the lag was fixed. A lot of the issues lay with consistency - we had to keep experimenting with parameters to make sure that it would work at least 90% of the time.
What's next for DriveSafe: AI Driving Assistant
Currently, DriveSafe can only be implemented with a webcam and computer--we only had a day to create it. We want to make it more convenient and make it a mobile application that can link with a webcam. In addition to functionality with webcams and Bluetooth webcams, the mobile application will utilize GPS libraries to determine if the driver is exceeding speed limits. This product will essentially eliminate common risks that drivers encounter.
Built With
css
html
javascript
opencv
python
Try it out
github.com
github.com | DriveSafe: AI Driving Assistant | Revolutionizing Driving Safety with Deep Learning and OpenCV Implementations | ['Shrinandan Narayanan', 'Krisha Chokshi', 'Siddarth Mamidanna'] | [] | ['css', 'html', 'javascript', 'opencv', 'python'] | 16 |
10,341 | https://devpost.com/software/melanomai-atm1ne | Thanks Page
Landing Page
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 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 and 1 in 4 people should not have to suffer due to an accident that can be avoided.
More so with the current Covid Situation, remote diagnosis is as important as ever as a extra few trips to the hospital could mean the difference between life and death.
This leads us to the question, how can we accurately and remotely diagnose melanoma?
MelanomAI is the answer to this problem.
What it does
MelanomAI analyzes the image of suspected melanoma to detect whether or not it is melanoma. Once the analysis is complete the user gets and email confirming their results where they can then seek out the proper help based on the diagnosis.
With MelanomAI, a diagnosis is just 5 steps away, and the need to go to a dermatologist or run multiple tests is severely lowered. The AI is on par, and sometimes even more accurate than current healthcare professionals which means that users can trust the AI's results.
The best part is that it doesn't require a checkup, testing, or other measures. Its as simple as uploading an image.
How We built it
We used a pretrained model: VGG16 for the Convolutional Neural Network and it had 6 layers. We trained it on a kaggle dataset with over 20 thousand dermascopy images and we were able to achieve an accuracy of about 90%.
We used the django framework to develop the website which used bootstrap, css, and html. Hosting was done on heroku.
Challenges I ran into
One of our members lost half of their files during a crucial time 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. More so, integrating the AI into the website prove to be more challenging than expected, but after some troubleshooting we were able to make it work!
We tried to host the Machine Learning model on the website, but the files were too large and it was quite difficult to figure it out. In the end we were unable to host the model, but given some more time to learn new technologies we are confident that we can fully integrate the AI.
Accomplishments that I'm proud of
We are proud of how we were able to create a working website and integrate the AI into it. In previous hackathons we were unable to integrate both the AI and Website, but this time we managed to do so which was a large milestone for us.
What We learned
We learned how to host a website as this was out first time hosting.
We learned more about pytorch, tensorflow, and django.
What's next for MelanomAI
We want to refine the algorithim to work more efficently and predict more accurately. As of now it seems to have some bugs where it doesn't predict, but given some time we are confident we can work them out and increase our accuracy to close to 100%.
After refinement, our next step would be to host our website on a powerful server that can handle deep learning models. We hope to accomplish this task in the oncoming weeks and are excited to make this a reality!
Built With
django
email
heroku
keras
python
pytoch
tensorflow
Try it out
github.com
melanomai.herokuapp.com | MelanomAI | The Future of Dermatology | ['Gaurish Lakhanpal', 'Anish Karthik'] | [] | ['django', 'email', 'heroku', 'keras', 'python', 'pytoch', 'tensorflow'] | 17 |
10,341 | https://devpost.com/software/stress-free-lfnuoq | Inspiration
COVID-19 has been a challenging and stressful time for all of us.
Playing games and yoga has helped me relieve stress. I thought I could spread my love of games, yoga, and also share information on COVID-19. As time progressed I expanded my idea to include ore topics, and also make this website like a One-stop shop website for any COVID-19 related issues. I want to create a online-live help, chatbox, information showing COVID-19 cases within your localty, etc that will help people during these difficult times.
What it does
This is a One-Stop-shop website that everyone can go to for any COVID-related issues - the website will have tons of information including local COVID-9 cases, online help, chat centers, stress-relieving techniques, fun activities and many more. This will be the go-to website for any COVID-19 related issues.
How I built it
I built it using HTML, javascript, CSS - will be using php and python for enhanced features
Challenges I ran into
Time has been a constraint.
Accomplishments that I'm proud of
I like the fact that my idea kept growing on. I like the idea of a One-stop website .
What I learned
I learnt more javascript
What's next for Stress-Free
Enhance the features and soon publicize the one-stop website
Built With
css
html
javascript
php
python
Try it out
glitch.com
bay-area-hacks-project.glitch.me | Stress-Free One Stop Website for COVID-19 | My idea is to create a website which will be like a One-stop shop for all Covid-19 related issues, including providing stress-free activities, fun games, online help and many more. | ['Sophia Jacob'] | [] | ['css', 'html', 'javascript', 'php', 'python'] | 18 |
10,341 | https://devpost.com/software/fiitshare | Personal dashboard
Group page
User profile
Workout creator
Workout screen
Fiitshare
A fitness website for the community, by the community.
Share your workouts!
What you can do
Join a workout group to access personalized workout schedules.
Create custom workouts with a convenient user interface, share your custom workout's URL with friends.
Follow along to custom workouts with an automatically generated, step by step video.
Track your progress on your profile page.
Built with
We built our web app with Next.js (React + Node.js). We used Firestore as our database and FirebaseUI Auth for user authentication.
Challenges we faced
Setting up Firebase Authentication was difficult because our team didn't have experience with it before.
Built With
firebase
firestore
nextjs
node.js
react
Try it out
github.com | Best Main Prize - Health - Fiitshare | A fitness website for the community, by the community. | ['Serena Li', 'Alina Li', 'Sean Yen'] | [] | ['firebase', 'firestore', 'nextjs', 'node.js', 'react'] | 19 |
10,341 | https://devpost.com/software/breast-cancer-detection-r48eab | Breast-Cancer-Detection
A ML solution for the health industry to detect breast cancer at an early stage.
Built With
html
jupyter-notebook
matplotib
panda
pandas
python
scipy
sklearn
Try it out
github.com | Health check | A cost effective and time efficient solution for the health industry. | ['Saurav Nayak'] | [] | ['html', 'jupyter-notebook', 'matplotib', 'panda', 'pandas', 'python', 'scipy', 'sklearn'] | 20 |
10,341 | https://devpost.com/software/digi-text | Web App Digi-Text
Inspiration
I have been learning Machine Learning for a couple of months but I haven`t created any final projects. I have been learning python and machine learning algorithms. When I saw Bay-Area-Hacks with the theme of Machine Learning, I felt like this is an opportunity to learn and grow my skills. So, I tried to give my best to the hackathon project as I could give.
What it does
My project is a Web App, It takes images from the users that have text, and only shows the text that is in the images using Artificial Intelligence and Machine Learning Service from Azure. It can be used to digitize any hand-written, or picture receipts/bills.
For example: If some students have hand-written notes, or pictures of whiteboard notes from teacher taken on class, then they can easily convert and extract text from these images using my webapp.
A person taking notes on paper at the shop can digitize his whole bills/account with the help of this app and it would be really time-saving to people.
How I built it
I built it using Python-Flask and using the cognitive Machine Learning services provided by Microsoft Azure.
Challenges I ran into
I faced really a difficulty in uploading my site to Heroku. It has created many problems and still, I don't know if my app will be deployed but I m writing this side by side. I completed my project locally but it is not running on Heroku. And Only half-hour is left now. So I am really afraid about project and my hard work too.
Accomplishments that I'm proud of
I am proud that I successfully built and useful machine learning application and deployed it too. Literally, I am really proud.
What I learned
I learned the CLI commands to deploy the flask app to Heroku and learned to use machine learning APIs and services provided by Microsoft which I had never done before.
What's next for Digi-Text
Due to time limitations, I could not do all the features that I wanted to do but I am sure I can add a Language translate feature within my app so anyone can translate the images in any language and read them out from the images and be able to copy the extracted text too.
Built With
azure
cognitive
flask
heroku
python
Try it out
digi-txt-app.herokuapp.com | Best Solo Hack- Machine Learning/AI - Digi-Text | Digitize Any Image with Text with help of our AI Based Text Translator | ['Naseeb Dangi'] | [] | ['azure', 'cognitive', 'flask', 'heroku', 'python'] | 21 |
10,341 | https://devpost.com/software/water-level-predictor | water level for post - monsoon (2018)
The idea
Inspiration
India is backed up by agriculture and Ground water becomes a necessary source for irrigation. That's why we decided to step up and do our job to help agriculture and as well the environment.
What it does
The decadal average of the pre and post monsoon groundwater level is compared with the present situation. The villages,blocks,districts and states showing improvement / decline with time ( one decade ) are located
The
random forest regression prediction model
is used to categorize the trend of the improvement / decline in terms of villages,blocks,districts and states with high improved accuracy. Based on the predictions, the improvement / declining trend, critical zones are identified and represented in maps
How we built it
We used Jupyter Kernel to train and test our models (using scikit-learn) and geoplot, geopandas to plot the values to a map.
Challenges we ran into
The dataset we had was limited to a particular state (TamilNadu) and the dataset itself had a lot of anamolies and NaN values. This made preprocessing difficult.
Accomplishments that we're proud of
Build a model and plot it in a graph
What we learned
Learnt a lot about Tech and Machine learning stuffs
What's next for Water level predictor
More complex analysis with huge area of consideration
Built With
geopandas
geoplot
jupyter
numpy
pandas
python
scikit-learn
seaborn
Try it out
github.com | Machine Learning -Water level predictor | To predict the trend of the improvement / decline in ground water level in terms of villages,blocks,districts and states. | ['Ben Stewart', 'santhosh njg', 'Mr.D Nagarajan', 'SivaK18 Kailash S'] | [] | ['geopandas', 'geoplot', 'jupyter', 'numpy', 'pandas', 'python', 'scikit-learn', 'seaborn'] | 22 |
10,341 | https://devpost.com/software/fake-news-detection-3u4npo | Labels on the Data
Error Rate before Fine Tuning
Learning Rate Plot
Error Rate after Fine Tuning and Freezing
Confusion Matrix after model predictions on Validation Set
Sample Fake News
Fake News Predictor
Inspiration
Recently, with the explosion of social media, the issue of fake news has become extremely prevalent, resulting in many illegal and dangerous activities. With deceptive words, online social network users can get infected by these online fake news easily, which has brought about tremendous effects on the offline society already. When misinformation is repeated and amplified, including by influential people, the grave danger is that information which is based on truth, ends up having only marginal impact. This project thus aims to detect any such fake news that might have spread due to social networking and social messaging platforms.
What it does
Faker-Detector is an application which allows you to verify whether a certain news related to COVID is true or false. It provides a simplistic, user friendly interface in which users simply have to enter the text of the news which they want to verify and produces a result in terms of whether the news is True or False.
How we built it
Our Machine Learning Model was trained using fastai, an easy to use and a very well established deep learning library. The web application was built using React, Flask, JavaScript, CSS and HTML.
Challenges we ran into
The data set used in building this application was extremely biased and required significant formatting to make it usable. In addition to this, there were a few difficulties in using fastai as we were working with it for the first time. We tried to make a simple UI for deploying and using the app on web. However, we faced a lot of difficulties in deploying the model. We were successful in making a UI for the app, but we could not link the model to the web app.
Accomplishments that we're proud of
We were immensely proud to create an application that allows people to verify the authenticity of different news reports regarding COVID and this, in turn, would significantly improve the trustworthiness of the information found online.
What we learned
We learned how to train models using fastai. Moreover, the concept of flask was also a new chapter in our development lives.
What's next for Faker-Detector
We will try to expand it and make it able to detect fake news related to other social issues. In addition to this, we intend to further improve its UI and make it more interactive for users. Furthermore, we will be working towards converting the model into a web app and deploying it so that people can use it in their daily lives and benefit from it.
Built With
fastai
flask
jupter-notebook
react
Try it out
github.com
drive.google.com | Best Main Prize - ML - fakerDetector | A user friendly application designed for verifying the authenticity of news reports. | ['Muhammad Raahim Khan', 'Farrukh Rasool', 'Ramez Salman', 'Hamza Farooq'] | [] | ['fastai', 'flask', 'jupter-notebook', 'react'] | 23 |
10,341 | https://devpost.com/software/safegadget-safewatch-with-safebot | Inspiration
What it does
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for SafeGadget(SafeWatch with SafeBot)
In today's day to day life, almost 80% of accidents are occurring all over the world. In this 80% accidents, 75% of deaths of victims are due to lack of immediate first-aid. There are many reasons behind accidents, some of them are -
Rash driving, drunk and drive, underage driving, crossing speed limits, etc. Whatever the reason there should be immediate response for victims. If not this will leads to death. I am also a victim in road accident. I met with an road accident and fainted with injuries. It is a place where there is no hospital in my surroundings and one no came across to help me. At last after half day, ambulance arrived and took me to hospital. This situation is the inspiration to built SafeGadget. To avoid this problem, I am developing a smart watch to detect accident and sends information to hospitals and personal contacts. Again, I met with another problem that is vehicle theft. I can't find vehicle and I can't afford a new branded technological vehicle. To avoid this problem I am developing a bot which can accessed through watch and detects your face when you start the vehicle. And it can also detects alcohol, if alcohol crosses the limit then the vehicle will slow down and stops after some peak point. SafeGadget is a combination of both SafeWatch and SafeBot. Any one can use SafeWatch and any vehicle can use SafeBot. This SafeGadget is synced to android application and images which all are acptured by SmartBot will stored in this app. I hope this SafeGadget saves victims and minimize reasons behind road accidents. The above video is another version of SafeWatch. We have to improvise that kit into Watch and Bot.
Built With
android-application
arduino
c
imagevision-facedetection
python | SafeGadget(SafeWatch with SafeBot) | SafeWatch is to detect accident and inform to certain people, SafeBot is to detect face of driver and also detects alcohol in vehicle. | ['BINDU Kavuru', 'chandra Kesava'] | [] | ['android-application', 'arduino', 'c', 'imagevision-facedetection', 'python'] | 24 |
10,341 | https://devpost.com/software/cookbookcv | Instantly, find recipes using certain foods you want to get rid of, right from the comfort of your phone camera.
CookBookCV
Instantly, find recipes using certain foods you want to get rid of, right from the comfort of your phone camera.
Inspiration
Every year, just in the United States, a third of food is wasted. This equates to just about 133 billion pounds and 160 billion dollars worth every year in just one country across the world. Coming from India, a place where millions of individuals starve to death do not have access to even drinking water, this problem truly resonated with our team. That's how we came with the idea for CookBookCV, simply take a picture of the food you have and we instantly return a delicious recipe complete with instructions on how to proceed.
What does CookBookCV do?
Our application has three main aspects:
First, the user must open up our iOS application and snap a picture of the leftover food they have. Our Machine Learning algorithm then instantaneously recognizes the foods in the photo and sends the array of ingredients directly to our Python Flask server which calls upon our recipe-finding function. Now, using Pandas and NumPy, the function parses through a CSV file with over 60,000 recipes scraped from several food-related websites and matches the inputted ingredients with one of the recipes. Once the recipes are identified, the function returns them back in an array including the title, ingredients, and instructions on how to actually make the dish. This process, while it may seem tedious, occurs in only a couple of seconds!
Challenges we ran into
Our major challenge when creating CookBookCV was to train our Machine Learning model to get a high-enough accuracy on the object (food) detection. We wanted this application to be as seamless and easy-to-use as possible for the end-user and this required us to put in countless hours in trial and error to optimize our code and make it work within seconds.
Accomplishments that we're proud of
We're proud that we were able to get the entire app functional after several trials and errors. Initially, it was difficult to connect all the individual parts of our code but with teamwork and perseverance, we triumphed at the end. Within a week, we were able to create an app that essentially has unlimited potential all across the world, and our team is very proud of that.
What we learned
Overall during this past week, we learned:
How to work together efficiently and effectively with team members to create a functional product with the end-user in mind
Using Flask to connect the Swift application to the Python recipe function
Optimizing functions to run in the least amount of time as possible using different techniques with Pandas and NumPy
Reading files from a server with Flask
Built With
flask
machine-learning
python
ruby
swift
yolo
Try it out
github.com | CookBookCV | Instantly, find recipes using certain foods you currently have, right from the comfort of your phone camera. | ['Shashank Vemuri', 'Shrey Jain'] | [] | ['flask', 'machine-learning', 'python', 'ruby', 'swift', 'yolo'] | 25 |
10,341 | https://devpost.com/software/funding | Login
Payments
Business Information
Highlights
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
An app that promotes small businesses and leverages the power & success of women entrepreneurs and businesses of color by helping them 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.
Built With
dart
firebase
flutter
square
Try it out
github.com | funding | A platform that democratizes access to capital for small businesses via crowdfunding | ['Rishav Raj Jain', 'Sulbha Aggarwal', 'Rupakshi Aggarwal'] | [] | ['dart', 'firebase', 'flutter', 'square'] | 26 |
10,341 | https://devpost.com/software/best-beginner-hack-ai-for-e-c-fight-fast-fashion | home page
home page w/ search query
loading results
results on mobile device
footer
Inspiration
I was inspired by the hackathon’s suggestion to use artificial intelligence to make environmental change. I’ve been reading a lot about how the fast fashion industry contributes to climate change recently (
this article
from the New York Times sums it up pretty well) and have wanted to shop more sustainably. Not only is the fast fashion industry harmful to the environment, it is also a social justice issue. People who work in or live near textile manufacturing facilities often receive a disproportionate burden of environmental health hazards. Employees of fast fashion companies are also often overworked and underpaid in bad working conditions to produce cheap clothing items. One of the best ways to avoid fast fashion is thrifting, which is also an affordable option. There are also many people in the fortunate position where price isn’t driving their purchases who are looking to shop more sustainably.
Unfortunately, a typical search online will result in mass market options and I often have trouble finding sustainable alternatives. I wanted a resource that would highlight slow, sustainable fashion alternatives to fast fashion products. Thus,
fightfastfashion.com
was born!
What it does
When users visit
fightfastfashion.com
, they can search for sustainable products based on keywords or by inputting a link to a fast fashion item. They are then redirected to a search page that shows a loading screen before revealing sustainable products with links to the retailers that sell them. In the footer, there are also direct links to shop at some featured retailers and resources to get educated about the issue.
How I built it
I built this project using a Python Flask backend with HTML/CSS/JS templates. I used the BeautifulSoup web scraping tool to scrape the user-inputted fast fashion link to find keywords to input into my algorithm, and to scrape sustainable sites for matching products. I also set up an email newsletter with MailChimp. My project is hosted on Heroku with a domain purchased from Google Domains.
Challenges I ran into
I initially hoped to provide a lot of sample data to train my algorithm to find more precise matches. However, I ran out of time (I was working solo for this project and this week I have also been working a full-time job as an instructor assistant at
Kode with Klossy
) and couldn't get it to work the way I intended, so thought I could refine that feature as a part of version 2.0 of Fight Fast Fashion!
Accomplishments I'm proud of
I’m proud that my web app functions and looks quite polished with a good domain name. This was the first time I was able to successfully set up a domain for an app on my own. I’m also proud of the color palette and design because in past projects I have been more focused on the backend and less on the design, and I think the website looks nice as well. Although drawing and art doesn’t come easily to me (I consider myself to be more of a math/logic-oriented person), I’m pleased with my custom logo drawing. Also, I only participated in my first hackathon in January, and am pretty new to the coding world. This is only the second hackathon I have competed in on my own, and I'm proud that I was able to juggle all the different responsibilities without having to rely on other team members like I have in the past.
What I learned
My main takeaway from this hackathon was learning not to be overly ambitious and to simplify to an MVP whenever possible. In previous hackathons I’ve worked with a team so this was the first time when I’ve been the one doing everything. I’m also currently working full-time as an Instructor Assistant at Kode with Klossy, so my time was limited. This meant I had to really prioritize my work. I learned to be okay with including features in version 2.0 instead of trying to do everything, although I’m very happy with what I was able to accomplish and ultimately, I also learned that I am capable of more than I think.
What's next for
FightFastFashion.com
?
I would like to develop a chrome browser extension to automatically find sustainable alternatives when it recognizes a user is about to check out at a fast fashion website.
Built With
A Python Flask backend
HTML/CSS/JS templates
BeautifulSoup
Flask-WTF
Heroku Hosting
Google Drive API
Disclaimer
I had trouble deciding which prize track to submit to, because although I am a beginner I also did this project completely on my own so I debated submitting it to Best Solo Hack. I was rather proud of how it turned out too so I contemplated submitting to Best Main Prize as well, but then again the algorithm wasn't working as precisely as I had initially hoped so this track felt most appropriate.
Try it out
fightfastfashion.com | Fight Fast Fashion | find ethical slow fashion alternatives to fast fashion items! | ['Isabella Hochschild'] | [] | [] | 27 |
10,341 | https://devpost.com/software/heimdall-the-guardian | Inspiration
The world is under Covid-19 alert. As many countries ease lock-down restrictions, residents are returning to old spaces. Amidst all this, from time to time, people forget to keep all the necessary equipment with them to keep them safe.
Presenting Heimdall: Your personal protector.
What it does
Every time you are about to step out of the door, you will have to stand in front of Heimdall (on-screen display with a camera attached to your main door) which will check if you have your mask on. Then, it'll present you with a checklist including essential items like hand sanitizer and gloves to keep you safe.
Once you have completed the checklist, it'll send a signal to Arduino which will activate a servo and unlock the door.
How we built it
A JS client-based library called p5.js, which is based on the core principles of processing, has been used for creating the basic graphic layout
ml5.js, which is fundamentally a HLL to TensorFlow.js, is used for deployment of Machine Learning in the web browser.
A pre-trained model called 'mobilenet' from ml5.js has been used for the implementation of this Deep Learning project wherein the principles of Transfer Learning has been used to train the model through new images.
An Arduino has been used to control the servo
Challenges and Accomplishments
We had some difficulties connecting everything together. We are proud of how robust the model turned out to be and how well the end project looks.
Built With
arduino
javascript
machine-learning
mobilenet
p5js
tensorflowjs
Try it out
github.com | Heimdall: The Guardian | Every door guardian | ['blackcrabb Niyati', 'Jatin Dehmiwal'] | [] | ['arduino', 'javascript', 'machine-learning', 'mobilenet', 'p5js', 'tensorflowjs'] | 28 |
10,341 | https://devpost.com/software/dermi | Dermi focuses on helping the community by having
early diagnosis
of skin diseases so that treatment can happen sooner, reducing deaths, and it is less expensive (reducing the burden on systems such as Medicare).
Inspiration
Many die and become disabled every year from skin diseases. If early detection can solve the issue, we need to make it more available. I aim to do that using deep learning.
What it does
Suggests skin disease from image.
How I built it
First I collected a dataset using a web scraper. Then I created a ResNet50 model using Pytorch..
Afterwards, I created a Flask server for inference and used Ngrok to make it publicly available.
Created an Android app using Kotlin and Room for on-device database.
Note: long press on a diagnosis allows you to delete it.
Accomplishments that I'm proud of
I am proud of the application and the speed at which I built it.
What I learned
Learning how to create a ngrok server on Colab itself.
What's next for Dermi
Larger dataset
Using several models to be able to create the most accurate diagnosis.
The current app uses 1 model, however, I previously created another model with another dataset, which I chose not to use for this hackathon due to the time restriction.
Using other available datasets (this app can integrate with other models, making it extensible)
iOS application
Built With
android
fast.ai
kotlin
pytorch
room
Try it out
github.com | Dermi (rash edition) | Simple but powerful skin rash classifier. | ['Vijay Daita'] | [] | ['android', 'fast.ai', 'kotlin', 'pytorch', 'room'] | 29 |
10,341 | https://devpost.com/software/covid-control-4wubm5 | Inspiration
The inspiration for our project came from the fact that Covid 19 has changed all of our lives in a significant way, and ensuring everyone is safe and healthy is a primary priority. Therefore, our app uses bluetooth technology to detect people within a 6 ft radius of eachother and alerts them if they are at risk for Covid-19.
What it does
When two people come between a 6 foot radius of eachother, the app uses bluetooth technology to exchange private codes which will be stored on each person's phone. Then if someone tests positive for covid, they upload their code to a database, and each person's phone checks the codes stored on their device to see if they have the code which tested positive for covid and if so, is given rigorous quarantining instructions.
How we built it
We built the app in javascript and html.
Challenges we ran into
We ran into many challenges in making the UI, and also the back end framework.
Accomplishments that we're proud of
Buidling the app.
What we learned
We learned many interesting things about the feasibility of javascript, and how it can work well with other plugins.
What's next for Covid Control
OUr next plans are to make the UI better and keep the back end fully functional.
Built With
html
javascript | Covid Control | An app that uses bluetooth to detect 6 feet radii between people, and to keep them safe and healthy by alerting them if they are at risk of Covid-19. | ['Anirudh Venkatraman', 'Josh Choi'] | [] | ['html', 'javascript'] | 30 |
10,341 | https://devpost.com/software/secure-your-space | Inspiration
What it does
,
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for Best Beginner Prize -- Healthcare
Built With
api | Best Beginner Prize -- Healthcare | An app that helps healthcare | [] | [] | ['api'] | 31 |
10,341 | https://devpost.com/software/coincounter-huo35v | Home
Counter manual
Converter [not finished]
Counter test
NOT FINISHED YET -- need to update the webscrapper to get the currencies.
Introduction
Coin Counter is an easy-to-use Android application that can count how much money there is in coins, using the smartphone camera. It also provides a currency-convert calculator.
Inspiration
This application was designed to make the tedious task of counting coins quicker and less tiring, especially for small commerce, who always receive a lot of them from their clients. It also intends to help small business owners and costumers not to touch in coins as a measure of preventing the spread of COVID-19.
Initially, our machine learning model was projected to achieve its task in a raspberry pie 3, ideally stopped at a determined position with a dark background allowing better recognition, but due to a loss of hardware we opted to implement it in an Android application which is also a good fit for this model.
What it does
It uses the smartphone camera to identify the value of each coin in an image and displays the sum of them. It also has a currency-convert calculator, where you can fill an amount and an exchange rate, and it returns the conversion result.
How we built it
Using the Android Studio API, as well as Pytorch and OpenCV.
Machine Learning
We trained a Convolutional Neural Network model called MobileNetV2, which we download from the Torchvision Python package. This model is more suitable for use in mobile devices, as it optimizes the number of floating-point operations needed for inference.
To train this model, we created a dataset from scratch (link:
https://www.kaggle.com/ronaldosm96/brazilian-coins-dataset
) and labeled all images using the software Colabeler (Link:
http://www.colabeler.com/
)
Precision
Recal
0.98
0.98
0.95
0.97
0.97
0.98
0.98
0.97
1.00
0.98
Confusion Matrix:
[49. 0. 1. 0. 0.]
[ 1. 58. 0. 1. 0.]
[ 0. 1. 65. 0. 0.]
[ 0. 2. 0. 63. 0.]
[ 0. 0. 1. 0. 58.]
How to use this application
Once you access the app, you can choose to use the counter or the currency converter.
If you choose the counter, you must point your smartphone's camera at the coins, which must be on a flat, opaque surface, and then you can view the count value.
If you choose the converter, you must inform the quantity and the exchange rate, and then you can view the converted value.
Challenges we ran into
We have almost no experience in programming in java and XML, and it's the first time we made an application that uses the android camera, pytorch_android and OpenCV for Android.
What we learned
We learned significant aspects of the Java language, as well as how to perform image morphology with OpenCV for Android and how to translate a PyTorch model to Android.
What's next for My Coin Counter
For now, this application only supports the Brazilian currency ("R$"), but it can be improved to support other currencies as well. Also, it will be useful to get the exchange rate between coins from the internet rather than ask the user to fill it.
Built With
android-studio
java
jsoup
opencv
python
pytorch
Try it out
github.com | Best Beginner Hack - Machine Learning - Coin Counter | Coin Counter is an easy-to-use Android application that can count how much money there is in coins, using the smartphone camera. | ['T K', 'Ronaldo Moura'] | [] | ['android-studio', 'java', 'jsoup', 'opencv', 'python', 'pytorch'] | 32 |
10,341 | https://devpost.com/software/enhance-bpjaez | Inspiration
Many people across the world don't want to or can't shell out hundreds for a high-resolution camera/smartphone. But we think everyone should be able to have crisp, high-resolution images of their memories regardless of the quality of their physical camera. With Enhance, anyone across the world with access to the internet will be able to upscale their images.
What it does
Enhance is a web application that takes low-resolution images as input and upscales them by 4x with deep learning, making features more distinguishable and increasing image resolution.
How I built it
Enhance uses a novel Generative Adversarial Network architecture trained on two diverse high resolution image datasets: the DIV2K dataset and the Microsoft COCO dataset. We did modeling with Tensorflow and Keras, and to prevent our computers from catching fire, trained it through Google’s Cloud ML Engine. Reprocessing was done through basic libraries like NumPy and Matplotlib.
We then strapped up an easy-to-use, intuitive web application in Flask so anyone can use our model.
Try it out
github.com | Best Main Prize - Machine Learning - Enhance | Upscale your images on the web with a novel deep learning architecture | ['Mark Zhao', 'Adam G', 'Dante Smokes'] | [] | [] | 33 |
10,341 | https://devpost.com/software/s-l65a3j | 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 quick, accurate 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.
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. Using the CocoaPods Framework, we were able to file a report into Google Firebase Realtime Database and send the picture to Google Firebase Storage. 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. The website feature a Map powered by the JS open-source library.
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. Also XCode comes up with a .DS_Store file which makes it very hard to communicate code and send temporary files, we faced this issue which really made it hard for us to collaborate.
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. We plan on expanding our database to hold reference and data for all power lines across California to catalog and detect them.
Built With
css
firebase
html
javascript
swift
Try it out
github.com | Best Main Prize - Spark | An iOS application created to simplify the process of reporting hazardous vegetation and wires near power utility poles. | ['Aditya Sharma', 'Ishan Goyal'] | [] | ['css', 'firebase', 'html', 'javascript', 'swift'] | 34 |
10,341 | https://devpost.com/software/fix-your-posture | Inspiration
The inspiration for this project arrives from my visit to a blind school. My family used to donate a bit to the blind school every month and I noticed some difficulty they face using talkback features on their phones.
289 Million people are Visually Impaired
33 Million are completely Blind
⅓ of the blind population is in INDIA
What it does
It takes the input from the visually impaired person from the IoT device in the braille language itself (the universal language for visually impaired people) and it gets into the mobile phone of the user. The Android app also speaks out the input so that the user can interact with the input.
our idea is about making a braille board that blinds can use efficiently to type sentences, communicate with anyone, play games, or even can code using this.
our idea is sustainable since there is a large number of blinds in this world and our product is making their life easier.
Regarding investors, they will pay us for the production cost and the marketing costs.
For customized networking, we will be collaborating with the blind schools over India.
Since we cannot contact each and every blind school in India, we will take help from the Department of Empowerment of Persons with Disabilities.
We once visited a blind school to test our prototype in real-life conditions. And the results were impressive. Below is the link to students using it from scratch.
The present solution in the market has a lot of points lacking which our's one is having.
Our product is much smaller in size and will weigh much lighter.
Easy to use and adapt than the current ones which are too much difficult to use.
compatibility with Android, ios, PC, and any other Bluetooth device. (current ones are limited to pc only)
Price less than 1/10th of present models.
Can be embedded in the mobile back covers as well.
How I built it
I used an Arduino nano, multiple tact buttons, bluetooth sensors and Li-Po battery. For Android Application, i used MIT application builder
Challenges I ran into
Integration of android application with popular applications like WhatsApp, google, youtube
Accomplishments that I'm proud of
Testing it out on the actual audience. As I go frequently to the blind school, I took this braille board to them. And tried getting honest feedback from them. The response from them got fetched in our hearts. You can the video here
https://youtu.be/jbIzWm6MsHQ
What's next for Braille Code Board
Integrating this board into the back cover of the phones to increase its mobility.
Built With
3d-modelling
android
Arduino
Bluetooth
c++
java
machine-learning
python
Built With
android
bluetooth
c++
machine-learning
python | Best Undergraduate Solution - Best Healthcare - Braille Boar | An IoT device that integrates with the Mobile phone and works as a keyboard for visually impaired people | ['Raghav Dhingra', 'Gursewak Singh'] | [] | ['android', 'bluetooth', 'c++', 'machine-learning', 'python'] | 35 |
10,341 | https://devpost.com/software/digital-counsellor-nql7wu | Our portal
Take test
Scores and assesment
Login portal
Inspiration
The unprecedented situation that has fallen upon us is taking a toll on the mental health of many people. Psychiatrists sense a rise in acute stress reaction and post traumatic symptoms among people with no history of mental illness. According to the experts, the monstrous novel corona virus will be going to have gruesome psychological scars as well. In fact, the cases have already started coming up in bulks. We know very well that people having mental problems find it hard to talk about it in person
What it does
How we built it
Taking this into account we have built a mood detection analyser which will talk to a person having mental problem and would suggest some remedies to get over it. The details about the person's mental state would be documented and sent to his email with proper guidance measures.
The system uses various techniques like speech recognition and video analysing to document the reports
Challenges we ran into
Assimilating audio, video analysis into one system
Detecting minor shivering in voice
Dividing the scores into positive and negative domains
Accomplishments that we're proud of
Even minor shivering,sadness and nervousness in voice is taken into account.
The system would interact with the user in friendly manner analyse everything and generate the report card.Suppose a user seeks help of our bot. Then the user only needs to answer few questions in front of the video. The system would first identify the gender, generate the subjectivity score and give the details about the state of mind of the person. More the subjectivity score more is the accuracy of the system.
Built With
flask
opencv
python
speechrecognition
tensorflow
Try it out
github.com | Best Main Prize - Healthcare Solution - Digital Counsellor | Mental health caretaker during the global pandemic | ['Avinash Kumar'] | [] | ['flask', 'opencv', 'python', 'speechrecognition', 'tensorflow'] | 36 |
10,341 | https://devpost.com/software/dl-income-mapping | This program implements several machine learning models for mapping income distribution using satellite imagery.
python main.py
There are several optional command line arguments:
--model: Machine Learning algorithm, including 'lr', 'rf', 'knn', 'svm', and 'cnn'.
--arch: ResNet architecture, such as 'resnet18' or 'resnet34'.
--regularize: Regularization techniques, such as 'ridge' or 'lasso'.
--batch-size: Size of a training batch for CNN.
--lr: Learning rate for CNN.
--epochs: Number of training epochs for CNN.
Built With
numpy
pandas
python
pytorch
scikit-learn
Try it out
github.com | DL-Income-Mapping | A deep learning project for mapping income distribution. | ['Tai Vu'] | [] | ['numpy', 'pandas', 'python', 'pytorch', 'scikit-learn'] | 37 |
10,341 | https://devpost.com/software/ai-implementation-in-credit-card-scam-detection | Inspiration
In this digital world, most of the transactions are occurring via credit cards while using cash will become rare in future days. At the same time, the information system is putting more efforts to make the credit card system more reliable and trustworthy. AI has made this task as easy as it can be and Python data science packages have made it easier for data analysts. Using the methods followed by the data scientists, I tried to detect the fraud by exploring the dataset. Fraud detection in credit cards is necessary for the future as the hackers always look for vulnerability so we must update our ideas and AI machine learning has created the opportunity to do so.
What it does
It just explores the dataset, cleans it, and by running the classifiers detects the rows as fraud or not a fraud.
How I built it
I used Jupyter Notebook and Python data science packages to build it.
Numpy, pandas, scikit learn, matplotlib, seaborn, etc. data analysis and data visualization packages have been used throughout the project.
Challenges I ran into
Data cleaning is an important task to do in this kind of project and it was tough to detect the outliers for such a big dataset. The cleaning of null values, irrelevant, and outliers were challenging.
Accomplishments that I'm proud of
I had got really a little time to work on this big dataset yet have completed successfully what I have intended to do. This is a real-world project which can contribute to better human life. I'm really proud of what I've made despite knowing that I could do more better and investing a lot of time in building an ML project is really praiseworthy. I had to seek help from the developers to fix bugs and errors while data explorations which gave me a lot of insights regarding the techniques to be used in pandas and NumPy.
What I learned
I learned how to work with
sklearn packages
and which classifiers work better in which condition and discovered the latency of the
pandas package
.
What's next for AI implementation in Credit Card Scam Detection
It's just the starting; it can be developed for making future sophisticated machines and AI ML models. The more open source datasets must be available for the better training of the models. The scarcity of open-source datasets is also challenging for the development of such models.
Built With
matplotlib
numpy
pandas
python
scipy
seaborn
sklearn
Try it out
github.com | Best Main Prize - Fin tech - Credit Card Scam Detection | It analyzes the and labels the output whether it's fraud or not fraud according to the test dataset. | ['Md Abrar Jahin'] | [] | ['matplotlib', 'numpy', 'pandas', 'python', 'scipy', 'seaborn', 'sklearn'] | 38 |
10,341 | https://devpost.com/software/tweetanalysis | . | . | . | [] | [] | [] | 39 |
10,341 | https://devpost.com/software/opportunity-recommendation-system-9jo8zs | . | . | . | ['Pulkit Midha'] | [] | [] | 40 |
10,341 | https://devpost.com/software/cogate-7nmfor | Inspiration
A smart AI-based gate which will open if the person will be wearing the mask with a sanitizing pathway based on liquid sanitizing for humans and UV sanitization for electronic gadgets.
The problem CoGate solves
There is widespread Corona Virus in the entire country and we have no solution rather have precautions and wearing masks is one of the essential. Since we found many people are entering without the mask to offices so we made this project.
As per the problem, we have come with an excellent solution which will solve this problem.
Introducing CoGate, a smart AI-based gate that will only allow those who will be wearing masks and not allow who are not having masks.
How I built it
The gate is based on realtime Computer Vision and Machine Learning. It is built with a camera that is connected with Google's Teachable Machine Image processing platform. The camera will detect whether the person is wearing a mask or not. If the person will be wearing the mask then it will send the signal to open the gate, to the microcontroller (here, Arduino) via Serial Port Interface (we are using p5 Serial Port). If the person will not be wearing a mask then the gate will not open.
Not only this, but the pathway of CoGate will also have a sanitizing chamber, of liquid for humans and a UV sanitizing chamber for electronic gadgets, and at the last, there'll be another gate to let the person enter into the office/building. The last gate can be used as a counter (in malls especially) to enter a particular number of people to avoid crowds over that place.
So, this is our project idea, we have thoroughly explained in the PPT (link) attached. In this way, we can make people to use masks more and more and make people aware of to wear masks.
CoGate: How it works?
The AI-based Gate: The gate is based on realtime Computer Vision and Machine Learning. It is built with a camera that is connected with Google's Teachable Machine Image processing platform. The camera will detect whether the person is wearing a mask or not. If the person will be wearing the mask then it will send the signal to open the gate, to the microcontroller (here, Arduino) via Serial Port Interface (we are using p5 Serial Port). If the person will not be wearing a mask then the gate will not open.
The UV & Sanitizing Chambers: The pathway of CoGate will also have a sanitizing chamber, of liquid for humans and a UV sanitizing chamber for electronic gadgets, and at the last, there'll be another gate to let the person enter into the office/building.
The crowd controller: The last gate can be used as a counter (in malls especially) to enter a particular number of people to avoid crowds over that place.
Challenges I ran into
We are very basic to Machine Learning, therefore we faced major problems but thanks to Teachable Machine from Google which solved our major problem as they provide the ML platform.
Technologies we used
-HTML
-JavaScript
-Machine Learning
-Arduino Uno
-AI Computer vision
Complete Explanation Video Link:
https://www.youtube.com/watch?v=7VTW0m-YJbI
Built With
arduino
html5
javascript
tensorflow
Try it out
piysocial-india.github.io
github.com
bit.ly | CoGate | A smart AI-based gate which will open if the person will be wearing the mask with a sanitizing pathway based on liquid sanitizing for humans and UV sanitization for electronic gadgets. | ['Saswat Samal', 'Sanket Sanjeeb Pattanaik'] | ['First Overall'] | ['arduino', 'html5', 'javascript', 'tensorflow'] | 41 |
10,341 | https://devpost.com/software/physio-assist-xfbq6n | Inspiration
Siri is the best assistant
What it does
Gives you tips for physical exercises
How I built it
Siri SDK
Challenges I ran into
None
Accomplishments that I'm proud of
Built it completely
What I learned
Siri Development
What's next for it
Alexa and Google Assistant
Built With
ios
siri | Amazing Assistant | Assistant that can turn your life : by being a nice physio | ['Shivay Lamba'] | [] | ['ios', 'siri'] | 42 |
10,341 | 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'] | 43 |
10,341 | https://devpost.com/software/medbot-eby8c9 | medBOT
medBOT work process
medBOT Architecture and Design
Inspiration
The post Covid-19 situation will increase the demand for essential medicines to ensure better healthcare and personal hygiene. Finding the required medicine, without going out of home,from the nearest shop has become a preference for all. To assist this cause, the project we have build is
medBOT.
What it does
medBOT
helps the users to query about the nearest medicine shop for the essential medicine. It automates the query process through a chatting experience so that the user doesn't have to go through a catalog of shops to set an order.
medBot
recommends and performs order placement in nearest medicine shop for the user.It finds the requirements through Natural Language Processing. Also it has a suggestion module for the
How I built it
I used python to build the
medBOT
. Python's Natural Language Processing package 'NLTK' performs tokenization and stemming the words. Then pyTorch was used to train the model using the stems. Google Colab was used as IDE.
Challenges I ran into
pyTorch installation in local machine is a cumbersome process .
Making the dataset from scratch was a tiresome work.
Training on a large dataset without GPU support creates a long loading runtime issue.
Hosting the server in local host has been an issue in my part so I had to end up using co-lab command based IDE for demonstration.
Accomplishments that I'm proud of
I could implement the chatBot that will work as a Brain/Backend for my system. As I was a one man team,this was a great thing for me.
What I learned
I learnt Natural Language Processing, NLTK tokenizing, building and training neural networks using pyTorch.
What's next for medBOT
Giving a nice appbased UI
Recommendation of shop using Travelling Salesman Recommender system
Built With
google-colab
nltk
python
pytorch
Try it out
github.com | medBOT | medBOT aims at meeting the demand for essential medicines of an individual through an automated order placing and chatting experience. | ['Araf Mustavi'] | [] | ['google-colab', 'nltk', 'python', 'pytorch'] | 44 |
10,341 | 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'] | 45 |
10,341 | https://devpost.com/software/sanchar | Inspiration
xyz
What it does
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for xyx | xyx | xyz | ['Harshita Sachdeva'] | [] | [] | 46 |
10,341 | https://devpost.com/software/hashfly | Our drone testing whether it can carry a fire extinguisher or not
Inspiration
My grandfather:- When I was 15 years old , while my grandfather was using industrial pesticide over his garden , accidentally it got spilled over his legs and a smoker unknowingly threw his cigarette over our house boundary and it touched my grandfather and he was shouting with fire over him this continued for 3 minutes but none came near him as none was there in house even the smoker was drunk and he took long to call the firemen . And along with my grandfather our house also burnt with fire and it was a big incident. Since then I was involved in heavy research with making a drone or using top technology to dive into detecting fire in almost all areas.
What it does
Earlier I won a Trello drone from IBM because of my project and this time my Parrot AR Drone drives into detecting fire in almost all areas in in it's vicinity.
How I built it
Mainly I used Python scripting and Azure cognitive services to ensure user gets access to it easily . We have launched it successfully
Challenges I ran into
We faced many bugs and while implementing the code in the model we faced issues like loose connections and malfunctioning of parts . It was difficult for me to build a prototype without access to good resources but finally we did that.
Accomplishments that I'm proud of
I am proud that I implemented my code alone and built a small project or better say prototype of the actual one and resolved all issues successfully
What I learned
I learned how to work even when our minds are blocked with failures or issues. I faced even breakup so was very sad. Now I want to excel in life after losing so much. I learnt how to overcome failures.
What's next for Hashfly
Using speech to code converter and accordingly we can set the payload so that it can carry strong fire extinguishers and using AI models and algorithms we will surely get through it if Microsoft or any company gives us a small motivation like an award for our work.
Built With
azure
behavioral-media-networks-cognitive-insights
deeplearning
python
Try it out
github.com | Hashfly | My projects is based upon AR Drone 2.0 and used python and other API libraries along with Azure Cognitive services to detect fire | ['Abhik Chakraborty'] | [] | ['azure', 'behavioral-media-networks-cognitive-insights', 'deeplearning', 'python'] | 47 |
10,341 | https://devpost.com/software/sarcasmo | Sarcasmo
Radar Graph
LIME interpretation
Inspiration
We live in a technology-centric world. As communication between people shifts from in-person to online, multiple problems present themselves. One such problem is sarcasm. Sarcasm is easy to detect in person because we can detect tone, sentiment, and meaning all through how a person talks. Over the internet, we can’t, and if the other person can’t tell you’re being sarcastic, you could be in trouble.
What it does
Sarcasmo uses natural language processing to detect sarcasm throughout the web.
How we built it
For the front end, we used Flask in order to run a local host web app. For the model, we used a TF-IDF vectorizer and a Support Vector Machine (SVM). The model interpretations were created by the LIME library.
link
. The dataset we used was from a research paper called "A Large Self-Annotated Corpus for Sarcasm"
link
.
Challenges we ran into
We tried to make it a google chrome extension, but ran into compatibility issues. We were limited by how much of our 1.3 million comment data set we could utilize due to low processing power.
Accomplishments that we're proud of
This is one of our first times attempting to use machine learning. We are very happy that we were able to create a machine learning model that we could train and test on 200k comments.
What we learned
We learned how to use machine learning for natural language processing. We also learned how to create a web-app interface between our machine learning model and an HTML page.
What's next for Sarcasmo
We hope to expand this as a tool that chat apps can use in order to label messages sent as sarcasm (at user's preference).
Built With
css3
flask
html5
lime
python
sklearn
Try it out
github.com
sarcasmo.ucraft.site
www.kaggle.com | Sarcasmo | Sarcasmo is a machine learning model trained to detect sarcasm. | ['Mohsin Zaidi', 'Tanush Chopra', 'Michael Li'] | [] | ['css3', 'flask', 'html5', 'lime', 'python', 'sklearn'] | 48 |
10,341 | https://devpost.com/software/nai-artificial-intelligence-desktop-navigation-lho2pw | GIF
Artificial Intelligence
Controlling mouse with corresponding gaze direction. Blink for mouse click.
Gaze estimation using Deep Learning.
Naruto Eyes (Fun mode)
Navigation of desktop using Artificial Intelligence. (GUI)
Inspiration
Millions of great people, are not able to use their electronic devices as efficiently as they potentially could, because of some uncontrollable circumstances. Because of that, many potentially brilliant writers, engineers, musicians, etc. could not conveniently follow their passions and create great things for humanity, and enjoy their lives a bit more. We decided that we are willing and we are capable of taking action towards helping those people. We decided to build software that solves this problem for physically disabled people and makes this world a little bit better.
What it does
Our first prototype enables people to navigate around their desktop, using only their eyes. This includes moving the mouse and pressing the buttons. It also has fun Naruto eyes mode.
How we built it
We built the base in Python 3, we used PyQt5 to create a GUI. Then we used OpenVINO and dlib library's pre-trained models and applied some transfer learning on them, in order to estimate the real-time gaze direction. We used OpenCV for detecting blinks and pyautogui library for controlling the mouse movements, and we used Docker for containerizing our application.
Challenges we ran into
First and the biggest challenge was the optimization of the inference of our deep learning models in order to make our app run faster.
Solving all the version compatibility issues(we ended up using Docker to solve this problem).
Accomplishments that we're proud of
The biggest accomplishment that we are proud of is the fact that we were able to turn what we had imagined into life.
We are also very proud that even the first version of our software is readily available to help disabled people immediately.
What we learned
We gained more experience in working with Deep Learning applications and learned new cutting edge technologies like Docker.
We also felt all the huge importance and power of good teamwork.
What's next for NAI - Artificial Intelligence Desktop Navigation
Our further improvements are:
Packaging app into ".exe" file, so it could be downloaded and run by anyone on any kind of operating system.
We are working on a website enabling people to download our software from the web.
Working on the sensitivity of the models, so our app works better, faster, and more precisely. Training our own model, instead of using OpenVINO models for better performance.
Adding NLP and voice control options to our application.
Adding more functionality and options to GUI.
Creating a mobile version of the app, using TensorFlow lite, to run our models on Android and iOS.
Built With
c++
dlib
keras
opencv
openvino
pyautogui
pyqt5
python
Try it out
github.com | AI Desktop Navigation | We are utilizing AI to create an innovative way for all people to control their electronic devices by using their gaze. | ['Matvei Popov', 'Sharan Babu', 'Srikar Samudrala'] | [] | ['c++', 'dlib', 'keras', 'opencv', 'openvino', 'pyautogui', 'pyqt5', 'python'] | 49 |
10,341 | https://devpost.com/software/daily-routine-manager | Inspiration
After researching the effects of our increasingly busy world on society we determined that one of the core issues was the lack of management in people's schedule's. That is why we decided to create the daily routine manager as an all in one solution to the problem. We sought to ensure that people were able to manage their schedules effectively while maintaining their emotional health.
What it does
The program we're designing will not only allow you to set up a daily and weekly schedule, but it will also allow you to create and add integrations to make your plan work the way you want it to!
How I built it
We are building our product using python for machine learning and HTML, CSS, and JavaScript for the web application aspect. We are using flask to integrate the ML capabilities with the website interface.
Challenges I ran into
One challenge we ran into was identifying an problem that impacted the most people. We anted our solution to be something that could impact everyone in society.
Accomplishments that we're proud of
Our team is proud of being able to successfully identify a problem that impacts everyone and find an effective and scalable solution to it. We are also proud of the technical knowledge we were able to gain, not only in programming concepts, but also in the industry. We were able to learn more about the development process and market as we sought to broaden our technical capabilities through the project as well.
What I learned
We learnt a lot about the ideation process and found it to be one of the most crucial components of creating a product.
What's next for Daily Routine Manager
Our next steps are to take the program to multiple platforms and scale it up so that we can reach a larger audience.
Built With
css
flask
html
javascript
machine-learning
python | Best Main Prize - Machine Learning - Daily Routine Manager | A solution to the lack of management and care in the busy society.of today. | ['Megan Jacob'] | [] | ['css', 'flask', 'html', 'javascript', 'machine-learning', 'python'] | 50 |
10,341 | https://devpost.com/software/collabcircle | Log in page
Find friends page
Sign Up page
Portable Piano- 3D model
Arduino UNO Setup
Inspiration
Finding new teammates during a hackathon is challenging for everyone. So, our team tried to find a solution for it
What it does
CollabCircle is a website that lets the user to find teammates according to their interest. CollabCircle asks user to sign up and add their interest like their hobbies, skills and other favorable thing. In return, CollabCircle will provide list of users with similar interests. Also keeping in mind, during hackathon, it lets teammates to entertain themselves during hangouts when physically apart by using a Portable Piano by our team.
How I built it
We used node.js for backend programming and algorithms that makes the project 'Unique'
Used Bootstrap Studio for frontend designing which gives the project most 'Unique' User Interface
Used Arduino UNO for the portable piano which gives the user 'Unique' way of entertainment.
Challenges I ran into
Different Time Zones: Every teammate belongs to different part of the world which was difficult for all of us to give time to the project
Unfamiliar with some software: No one of us has equal skills in software development so, we divided work and tried to do as much as possible.
Accomplishments that I'm proud of
Got to know about hardware development
Got experience with software development
Got to know more about cultures of different countries
What I learned
Got experience with bootstrap studio.
Tried to work with node.js for first time
Improved my skills at website development
Working on Arduino UNO improved my knowledge with hardwares
Team Work
What's next for CollabCircle
We will try to make Mobile app that will let user to contact with the team anywhere
We will make a chat area in the project where users may chat with their teammates
Will use Machine Learning to improve team finding
Introduce a software through which user can get tutorials for beginners, music notes by music genre.
Built With
bootstrap
express.js
javascript
mongodb
node.js
Try it out
naseeb0.github.io
collabcircle.online | CollabCircle | Collaboration Made simple around the world! | ['Naseeb Dangi', 'Wei Sheng Tan', 'Keshav Majithia'] | [] | ['bootstrap', 'express.js', 'javascript', 'mongodb', 'node.js'] | 51 |
10,341 | https://devpost.com/software/best-beginner-hack-health-fitme | Inspiration
I got inspired to create Virtuthon because during these social distancing times we are not able to walk or run with each other.
What it does
Virtuthon is an iOS app that enables users to view each others step count and be empowered to improve their own. The app enables users to compete for who has the most steps so that even during these social distancing times we can continue to be healthy while challenging ourselves. Before the COVID-19 pandemic walkathons and other group exercising events were taking place. My app will help people to stay more healthy.
Some possible uses for the apps are for walkathons that want to continue during the COVID-19 pandemic. Another use for the app is allowing parents to monitor their children's step count so that they can see if their child is healthy and exercising properly. Other ways that Virtuthon can be used is by Doctors. Doctors can monitor their patients step count without being near each other and this enables them to suggest for the patient to walk more or less.
How I built it
I build Virtuthon using Swift 5 and Xcode. Virtuthon monitors a users step count and distance by using the iPhones in-built pedometer. To store the users step count and distance so that other users could view it I used the Firebase Database.
Challenges I ran into
Some challenges I ran into were properly using the pedometer to increment the current value in the database. I also ran into some issues while implanting the group functionality of the app.
What I learned
I learned about how to use the iPhones in build pedometer (CMPedometer).
Built With
cmpedometer
pods
swift
xcode
Try it out
apps.apple.com | Virtuthon | Exercise with each other even when your not together | ['Adrit Rao'] | [] | ['cmpedometer', 'pods', 'swift', 'xcode'] | 52 |
10,341 | https://devpost.com/software/healthrific | Contact free basin modified design
Actual picture of Basin
Actual hardware pic
SignIn page
SignUp page
Forgot Password page
Kiosk Test
Self Assessment Test
Covid 19 Updates
Health Tips
Results of Self assessment test
UV-C
todo
Built With
bluetooth
dart
firebase
flutter
Try it out
github.com
docs.google.com
drive.google.com | no | na | ['Haripriya Baskaran', 'Mohammed Mohsin'] | ['Script Foundation: Best Healthcare Solution'] | ['bluetooth', 'dart', 'firebase', 'flutter'] | 53 |
10,341 | https://devpost.com/software/cubba | Main Picture
Why?
How It Works
Setup?
What Happens After Detection?
Who doesn't like memes, right?
Inspiration
We all deal with potholes on a daily basis considering we all need to use the roads of the cities we live in and for sure, we all hate them. Major Californian cities such as San Diego, San Jose, San Francisco and Los Angeles has over
%64
of their roads in mediocre and damages conditions. United States of America is estimated to have approximately
55 million potholes
. A comprehensive study made in 2018 by AAA shows that over the past five years around
16 million drivers
across the States have suffered damage from potholes.
The pervasive potholes in question wreak havoc on drivers' car suspensions and cause a considerable amount of traffic issues. Well, that is a problem we need to fix.
On average, a little over
3 million drivers
in the US suffer pothole related damage every year. This can be anything, from popping a tire, to bending a rim, to blowing out a shock absorber. The direct financial costs of fixing these damages adds up to nearly
120 billion dollars
for America's drivers. Even worse than a financial annoyance, a pothole can cause various problems and crashes for even the most experienced drivers. Of approximately
33,000 traffic deaths
a year, as many as one third are attributed to poor road conditions like potholes. These losses must be avoidable.
So, what are our options? Can't we just build new roads? Building roads is insanely expensive and they are not the easiest thing to manage in a big, crowded city. Designing better foundations for our roads featuring improved drainage wouldn't decrease the frequency of potholes, on top of that these improved foundations are so much more expensive to build. Maintaining America's large four million mile road system and enabling our level of travel would be a serious burden to have. The American society of civil engineers who know a thing or two about roads, estimates that the cost of maintaining United States' roads properly is between
150 billion
and
200 billion dollars
a year for the next
50 years
. But the States' budget is limited with only
60 billion dollars
. Now I may have only taken math for the humanities in high school, but that seems a few bucks short of what roads need.
What it does
Raspberry pi records a video footagw while you are driving your car. Then, the recorded video in question will be converted to images. Image classification will decide if image has pothole or not.
How I built it
Raspberry Pi (or any small computer that can fit in front of car) and camera. When you start your car, the power goes to the raspberry pi and it automatically runs a python script that records the video.
Challenges I ran into
Raspberry Pi is compact but not as powerful as needed (at least before raspi4).
What I learned
Well, if you do want the pictures of potholes or road disorders ahead, maybe you shouldn't (you definitely shouldn't) put a camera in front of your mom's car.
Even though image classification is not a hard code to write, it still requires a decent amount of study.
What's next for CUBBA
A decent change of name, it's in Turkish.
Better dataset and images
Object detection
GPS and stats
a lot of stats
...
Built With
camera
python
raspberry-pi
tensorflow
Try it out
github.com
cubba.ml | CUBBA | Dedect potholes with raspberry pi and camera! | ['Umut YILDIRIM'] | [] | ['camera', 'python', 'raspberry-pi', 'tensorflow'] | 54 |
10,341 | https://devpost.com/software/solve-q603hg | Inspiration
To ease the stress from scratch in getting r.mesults from a dataset.
What it does
It carries out analysis on the data input and give future prediction.
How I built it
I imported some python packages and specified how different datasets showed be arranged either containing dates and time or not. Then split the data's and run predictions on them from different machine learning models, so the best model is choosen for prediction.
Challenges I ran into
How to clean any form of CSV datasets that will be imported for prediction.
Accomplishments that I'm proud of
Finally figured out to a larger extent on how clean datasets.
What I learned
How to reduce time working on a machine learning project.
What's next for Solve
Looking to making other forms of data possible like audios, images, videos and other data format.
Built With
flask
python
Try it out
github.com | Predictor | A app that can run predictions and give results from data input | ['Ugochukwu Nnachor'] | [] | ['flask', 'python'] | 55 |
10,341 | https://devpost.com/software/best-beginner-hack-machine-learning-covid-19-predictor | Inspiration
I am always curious about how machine learning was able to predict and generate future data using regression. I am passionate about coding and wanted to learn more about ml and the mathematical algorithms implemented in them.
What it does
My web application uses polynomial regression to predict COVID 19 cases in several countries using JSON data that was provided by Github. The application trains a model using the data provided and gets the most optimal values for a,b and c. These weights are then put into the ax^2 +bx +c equation with an x value to get the number of cases.
How I built it
I know running the training process in the browser would be very slow. Hence decide to use node.js and create my own API for the front end to interact with. For this, I used node.js and some other libraries to create the front end and back end. For the front end, I mainly used HTML, CSS and javascript to interact with the API. I created several posts and get requests allowing the front end to interact with. Most of the training and processing are done in the node.js allowing the front end to be fast and efficient.
Challenges I ran into
The challenges I faced while creating this web application was mainly getting an accurately predicted result. At first, I used linear regression which took me 2 days to understand the concept and how the mathematical algorithms work. However, soon I realized that linear regression was not the best fit for the COVID-19 data. Due to this I started learning polynomial regression and was able to get better results. Another section of the web application that challenged me was the front end and getting the data in a certain way. This was mainly working with the uploaded JSON as well as the date that was selected by the user.
Accomplishments that I'm proud of
I am proud to be able to implement polynomial regression and understand the mathematical algorithm used in it. I was mainly proud of being able to train all the various covid-19 countries with a 100k iteration , and seeing the weights coverage to a more optimal value.
What I learned
I learned more about the front end as well as the back end this allowed me to understand more about designing a web application. I also learned about polynomial, linear regression and how mathematically these regression work.
What's next for Best Beginner Hack-Machine Learning-COVID 19 Predictor
I would like to use the mappa.js to provide much better visualization of the COVID 19 prediction across the world.
Built With
api
chart.js
css3
express.js
fs
github
html5
javascript
json
node.js | Best Beginner Hack-Machine Learning-Covid 19 Predictor | A web application that uses real life covid -19 cases to predict the future cases using machine learning | ['Noel G'] | [] | ['api', 'chart.js', 'css3', 'express.js', 'fs', 'github', 'html5', 'javascript', 'json', 'node.js'] | 56 |
10,341 | https://devpost.com/software/safe-school | Life Saver is a project that uses machine learning and ai to detect the distance between people in public spaces and warn them about their risks of catching COVID-19.
Built With
css3
google-cloud-vision
heroku
html5
javascript
jinja
machine-learning
mongodb
react-js
sass
Try it out
github.com | Life Saver | Don't complain, Don't whine, Cause we keeping everyone fine. | ['Mihir Kachroo'] | [] | ['css3', 'google-cloud-vision', 'heroku', 'html5', 'javascript', 'jinja', 'machine-learning', 'mongodb', 'react-js', 'sass'] | 57 |
10,341 | 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'] | 58 |
10,341 | https://devpost.com/software/emergex-oa2ikt | 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 tourist 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 teamwork and work together even though not being in touch physically. We interacted with online and distributed tasks 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
Try it out
github.com | Safety Travel | AI powered holistic solution for inducing confidence in people to travel safely again. | ['Siddhant Kumar', 'Vedant Kumar', 'Parth Shingala', 'Pradhuman Singh'] | [] | ['angular.js', 'machine-learning', 'node.js'] | 59 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.