hackathon_id int64 1.57k 23.4k | project_link stringlengths 30 96 | full_desc stringlengths 1 547k ⌀ | title stringlengths 1 60 ⌀ | brief_desc stringlengths 1 200 ⌀ | team_members stringlengths 2 870 | prize stringlengths 2 792 | tags stringlengths 2 4.47k | __index_level_0__ int64 0 695 |
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10,341 | 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'] | 60 |
10,341 | https://devpost.com/software/ridhima-s-covid-app | This is the downloaded app on the phone
Inspiration
COVID-19
What it does
Self declaration for COVID
How I built it
I built it with my imagination and the situation the world is in right now
Challenges I ran into
The code kept disappearing
Accomplishments that I'm proud of
That I finished I nice project even if I do not win
What I learned
How to code better than I used to
What's next for Ridhima's COVID App
Enhance for more features of sending alerts and notifications
Built With
code.org-local-school-database
Try it out
studio.code.org
github.com
docs.google.com | Ridhima's COVID App | Self Declaration for COVID | ['Ridhimasgame Bembey'] | [] | ['code.org-local-school-database'] | 61 |
10,341 | https://devpost.com/software/virtuquiz | Thousands of videos, understand your lessons clearly.
Inspiration
There are so many students around the world who are weak at studies. Many children don't like the traditional learning or the e-learning method.
Although there are many learning apps, there are some features that I thought of that no other app has. Including all these features I wanted to create a learning app, and thus Virtuquiz, which is not limited to quizzes, was born....
What it does
Virtuquiz is a learning app which anyone can download on their mobile phone and start to learn. This app is recommended to students of grades 6-12, but other grades will be added sooner.
Virtuquiz has 2 main sections, one is learning and the other is quizzes.
Leaning Section
The learning section features 3 sub-categories which include videos, a homework checker and an extra knowledge bot.
Videos
There are thousands of videos under different topics which you can refer to. The video section consists videos from an online school 'Khan Academy.' Watching videos here is simple. Scroll down on the topic list, select the topic, then select a video and watch it. All videos are in English.
Homework Checker
This is a feature where anyone can submit there homework for a re-check before submitting it to a teacher. You can either send a picture or document. Then we will re-check it with automated systems as well as manual systems and send whether the work is correct or point out the mistakes and analyze them. We have clearly said that no one can use this feature for cheating.
Extra Knowledge Bot
This bot which is called as the Virtubot can be used for learning good qualities and learning about the society. This is also an essential part which education systems have missed out today. The Virtubut is still under development, it only has 3 questions yet. Using it is simple, the bot asks questions; for example how will you handle a situation where your friend is scolding you for what you didn't do.
There will be some options of what you can do. You will have to chose the wisest solution. You will be judged and given feedback (You are rude, or , very good you are generous).
Quizzes
After you have learned using the video feature you can check your knowledge using the quizzes. There are 20 quizzes with 10 questions each at the moment, more will be added too. Quizzes are under 5 main topics. (Science, History, Technology etc.)
Answering questions in quizzes is simple, all the questions are multiple choice questions, you just how to select the answer and press next. Finally after finishing all the 10 questions you will get a report on your performance. The pass mark for all quizzes is 70%.
How I built it
The Virtuquiz app was built using different app building platforms, the questions were built created by me with the help of online articles. The video feature was added in collaboration with Khan Academy Videos. The Virtubot was built using the virtual bot creator. The app was finally compiled using Android-Studio.
Challenges I ran into
There were many challenges.
The first was finding videos, I couldn't do all the videos myself. But finally I found a Khan academy feature which allows you to add the videos which belongs to them.
Another challenge was creating quizzes, I had to make 200 questions and add different answers. This was all done within 12 hours..
Also the Virtubot was difficult to create. I failed in creating the bot and integrating it successfully at the beginning, but later I was successful.
Accomplishments that I'm proud of
I am proud of adding a bot which is a unique feature and also a feature that plays a role in social-good.
Also I am proud of successfully creating this app.
What I learned
While building my app, I had to read many educational articles, I gained a lot of education through this. Also this was one of the most difficult apps I built, it really taught me a lot about programming etc.
What's next for Virtuquiz
I have to let people know about my app, although it's good and working many doesn't know that something like this exists. So, I need to promote.
Also I will have to develop this app more in the future.
Built With
android-studio
appsgeyser
appy-pie
gimp
Try it out
github.com
play.google.com | Virtuquiz | The Ultimate Learning App, quizzes, video lessons and even problem solving bots included... | ['Senuka Rathnayake'] | [] | ['android-studio', 'appsgeyser', 'appy-pie', 'gimp'] | 62 |
10,341 | https://devpost.com/software/alexa-let-s-code | Best Main Prize - Machine Learning - Alexa, Let's Code
Inspiration
With the recent COVID-19 pandemic, students worldwide have transitioned to online schooling. For some students, however, the transition has been harder than for others. Near where Veer lives is the oldest school for blind students: Perkins School for the Blind. Veer had always wanted to help them, and, during these times, he decided to help them when they needed it more than ever. Together, our team worked on an online platform dedicated for the blind and targeted for our favourite lesson: programming.
According to the National Federation of the Blind, COVID-19 has had a disproportionate impact on the blind, with many facing additional challenges during the pandemic. From an education standpoint, blind students and blind parents face uncertainty about the types of electronic materials they will be expected to use for the remainder of the academic year, making it hard for them to keep up with classes. Lastly, it is difficult for the visually impaired to learn how to code on their computer, a challenge which has been exacerbated by the pandemic.
What it does
We utilized a complex tech stack incorporating alexa skills, flask endpoints, rest api's, google cloud speech to text, and a python desktop application in order to build a speech-to-text editor which can listen to speech, translate it to Python code, and then display the code in an desktop text editor. The platform is complete with voice enabled git commands which the user can perform using the amazon alexa.
We used natural language processing to:
Allow the visually impaired to code in python by simply speaking
Provide a handful of voice enabled git commands and speech recognition features to effectively teach coding and version control
Display the spoken code in an online IDE, where one can run it and get the output
How we built it
We used:
Amazon Alexa
Flask
Python
Natural Language Processing
Google Cloud Speech API
Challenges we ran into
At first, we wanted to run everything through Alexa; however, we soon learned that we could not read raw text directly from an Alexa action. Thus we decided to pivot to using Alexa for specific commands and the GCP to intake and process all the commits. We also faced difficulty with time zone differences and staying connected.
Accomplishments that we're proud of
We're proud of how we handled the situation once we figured out Alexa couldn't process raw data. We were able to pivot our project nicely and create a product we're proud about. Despite never having met in person, our team as a group was able to be flexible and adapted to the situation.
What we learned
We learnt how to use speech recognition and execute the code in string form. We also learned more about linking Alexa skills and git commands with Python, as well as connecting to flask endpoints through desktop applications, especially for real-time work. Overall, three of our four teammates learned about Alexa and its compatibility, and we all tried to learn more by combining different technologies together.
What's next for Alexa, Let's Code
We eventually want to push this out for all Alexa users. In addition, we want to connect our application with popular text editors, such as VSC, Repl.it, and Atom. We want to eventually expand our project to more languages and functionalities to ease the life of developers.
Built With
amazon-alexa
flask
google-cloud
natural-language-processing
pyqt
python
Try it out
github.com | Alexa, Let's Code | Using Alexa to empower the visually impaired to code simply by speaking | ['Veer Gadodia', 'Nand Vinchhi', 'Shreya C'] | [] | ['amazon-alexa', 'flask', 'google-cloud', 'natural-language-processing', 'pyqt', 'python'] | 63 |
10,341 | https://devpost.com/software/the-foodie | Inspiration
Great inspiration
What it does
orders food online
How I built it
built with amazon developer console
Challenges I ran into
all challenges
Accomplishments that I'm proud of
everything
What I learned
everything
What's next for The foodie
upgrade it
Built With
amazon-alexa
github
Try it out
github.com | The foodie | Order food from home | [] | [] | ['amazon-alexa', 'github'] | 64 |
10,341 | https://devpost.com/software/sentiment-analysis-of-covid-19-tweets-dashboard | Inspiration
Our objective is to ensure people’s mental health in the special COVID-19 pandemic. And we will give detailed suggestions to people who feel mental discomfort during the quarantine period. This is the logic of our project : Our data source is Tweets with the hashtag #StayHome on Twitter, and our main analysis method is to understand the emotions of people and identify possible factors that influence their emotions, like a specific topic or activity. The main tool we use is NLP, including sentiment analysis, word clouds, and topic modeling.
Presentation:
Twitter Sentiment Analysis-COVID-19-Visual Dashboard
What it does
Based on the analysis on topics and single word, we give the following suggestions to people who feel mentally discomfort. There are several popular that are proved to be very positive: including listening to and singing songs, watch movies or TV series, virtually connecting with your closed ones even though you are physically distant, and workout. Besides, we also found several activities that are surprisingly very helpful to your emotions:
First, help others, whether sharing free food or donating money helps you feel better
Second, say a prayer does help release your emotional discomfort
Third, ordering food online rather than cooking has a more positive effect on your emotion, where you can enjoy more delicious food
Last but not the least, Stop playing games all day. It’s not a very good way to make you happy.
Social Impact:
Besides the sentiment of topics, we are also curious about what activities people do across different cities. So we listed the top3 activities in each city based on the number of tweets related to the topic. We got several interesting findings:
Watch videos, workout and delivery are the popular activities in many cities.
People in New York prefer staying with their friends and family, people in LA most like watching shows and movies
Communication through word, message and picture is very popular in Boston. People in different cities do have preferred activities!
Accomplishments that I'm proud of
Analyses twits classify it to Positive negative and neutral, Processed data using Natural Language Processing and Used various analysis methods to show in graps
Scope:
We started from conducting sentiment analysis on our data. We analyzed the tweets and tried to understand people’s opinion expressed by the text. Using the textblob library in Python, we can quantify the sentiment behind each tweet with a positive or negative value, called polarity. We also plotted the average sentiment score over time, and we can see that generally people’s tweets are becoming more and more positive.
After dividing the tweets into positive, negative, and neutral categories based on polarity, we calculated the word frequencies for positive tweets and negative tweets separately and drew a word cloud for each of the two categories.
From the first word cloud, we can see that positive tweets often contain positive words like “safe”, “great”, “happy”. There are also words like “video”, “music” that imply positive activities.
Built With
data-science-toolkit
natural-language-processing
python
testblob
twitter
voila
Try it out
drive.google.com
drive.google.com | Sentiment Analysis of Covid-19 Tweets- Visual Dashboard | Our objective is to ensure people’s mental health in the special COVID-19 pandemic. And we will give detailed suggestions to people who feel mental discomfort during the quarantine period. | ['Pramod Paratabadi', 'Supriya Shivanand Madiwal .'] | [] | ['data-science-toolkit', 'natural-language-processing', 'python', 'testblob', 'twitter', 'voila'] | 65 |
10,341 | https://devpost.com/software/fast-and-furious-3000 | Initial page
Inspiration
My Grandfather
is my inspiration. Though he is not there anymore but his words inspired me to always move forward to learn for social good and never to look down or feel depressed.
What it does
It is a racing game for children and it is 3D. It's actually to show the developers that React360 makes it very easy to build 3D games. I don't want to get any award but please bring my project into the limelight so that other developers can learn from it.
How I built it
I built it using React360 and CSS. React360 framework really proved very useful in this project.
Challenges I ran into
I ran into challenges getting the icon images which I agree I copied from the internet and am sorry for that. I solved issues like the object was not moving properly then set the height of other objects and then setting up the audio.
Accomplishments that I'm proud of
It was really fun working upon the project and I am a big fan of React360 now. I highly recommend my juniors to use React360 for 3D application development.
What I learned
I learned a treasure a valuable experience of my life. It was a great moment for me to work on this project.
What's next for Fast and Furious 3000
It's my love. I will add levels for the game involving other objects which will try to attack upon the car and the player should avoid that.
Built With
coffeescript
html5
javascript
leap-motion
react360
three.js
webgl
Try it out
github.com | Fast and Furious 3000 | My project is a racing game 3D. It has efficient motion controllers and can prove to be the best gaming experience. One can even use touchscreen mechanism to handle the racing shuttle | ['Abhik Chakraborty'] | [] | ['coffeescript', 'html5', 'javascript', 'leap-motion', 'react360', 'three.js', 'webgl'] | 66 |
10,341 | https://devpost.com/software/covid-19-healtheval | A look at the home page of COVID-19 HealthEval on the computer.
A look at the MH Evaluation Quiz on the computer.
The physical health portion, CoreHealth, home page.
A look at the MH Evaluation Quiz on the iPhone 8.
Inspiration:
For this project, my inspiration came from my surroundings. For both my family, friends, and myself, life had become extremely boring during lockdown. Doing physical exercise was difficult, since gyms were closed and sports teams had been put on hold. Mental health had also begun to deterioriate, after sitting in the house for prolonged periods of time, and due to pessimism about the entire situation of the pandemic. That's why I decided to make COVID-19 HealthEval, which helps to solve both of these problems.
What it does
COVID-19 HealthEval allows you to evaluate your own physical and mental health using a short and simple quiz for each. For the mental health quiz, you get personalized advice about coping with your current detected stress levels. For physical health, there are different quizzes for different body parts that you want to make stronger, or exercise more. Based on the results of the physical health quiz for a specific body part, you get a personalized diet, a sample meal plan, and a workout routine that has been designed for people to be able to easily do at home, without any equipment that you would use at the gym.
How I built it
I built COVID-19 HealthEval with HTML, CSS, VanillaJS, and JQuery. Here's a breakdown of how I did each section of this project:
Home Page: HTML + CSS
Mental Health Home Page: HTML + CSS
Mental Health Evaluation Quiz: HTML + CSS + VanillaJS + JQuery (The quiz was made with the JS and JQuery)
Physical Health Home Page: HTML + CSS
Physical Health Application (CoreHealth): I made an entirely separate website for the physical health section, also called Core Health, due to the many pages. I did not want to crowd it all into one website.
Home: HTML + CSS
cH (Core Health) Quiz: HTML + CSS + VanillaJS + JQuery
Diet: HTML + CSS
Workout: HTML + CSS
About: HTML + CSS
Challenges I ran into
The main challenge for me was the media queries, and adapting the website to be functional on the phone. For the different versions of phones, there are different widths and heights that need to be adjusted to, which required lots of precision.
Making the design look professional + inviting. I felt that this was very important, as the look of the website when a person accesses it makes the initial good/bad impression.
Accomplishments that I'm proud of
Being able to make the media queries work. This was the most time-consuming portion of the project for me.
My attempt to solve a very prominent problem in today's world. The pandemic has created many difficult situations, and I have put in a lot of effort into trying to fix one of them.
What I learned
I learned a lot about the physical and mental health problem during this pandemic. The personalized advice for each score came from research about mental health. The same followed for physical health.
I learned many new components of HTML, CSS, and VanillaJS that I did not know of before, which has allowed me to expand my horizon for web-design.
What's next for COVID-19 HealthEval
For me, the next step is to learn Swift, and put this out on the iOS App Store. This will make it easier to use for people who primarily use their phones over their computers.
After this hackathon is over, I will definitely be working on this project to improve it. I am alone on this team, and I think that I am the right person for this project, because I really have a passion for computer science and a sincere drive to improve the physical and mental health situation for everyone during this pandemic.
Built With
css
html
javascript
jquery
Try it out
vardaansinha.github.io
github.com | COVID-19 HealthEval | With COVID-19 HealthEval, maintaing your physical and mental health will be easier than ever before during these extraordinary times. | ['Vardaan Sinha'] | [] | ['css', 'html', 'javascript', 'jquery'] | 67 |
10,341 | https://devpost.com/software/quarancare-vgy02f | Welcome page
Sign up- doctor
Doctor- chat with patients
Patient- symptoms page
Sign up- patient
Doctor- sign out
Choosing doctor or patient
Patient- choose a doctor
Patient- sign out
Doctor- profile page
Patient- chat with a doctor
Log in page
Homepage
Inspiration
My inspiration for this app is the Covid-19 cases here in Singapore and back in my homecountry, India. Many migrant workers have symptoms related to Covid-19 such as cough and fever, but they did not want to get them checked out as the medical opinion is very expensive and I am sure that these workers would rather provide their family with food instead. I think that this resistance was one of the reasons that Covid-19 has been spreading so much within the migrant workers and I believe that through this app the spreading of Covid-19 could be reduced as people can get free medical opinion on their symptoms.
What it does
What the app does is connect patients and doctors so that they can chat with one another. The focus audience for this app is patients from low-income families who can not afford to pay for medical care and doctors who would like to volunteer to help patients without getting any income. The user can log in and access chats with different doctors/patients.
How I built it
I used xcode to build the app, most of the app is to do with the user inference as well as some code to save the login details and run the app as it should. I used a lot of help from outside sources such as youtube to guide me along the way.
Challenges I ran into
There were a number of frustrating challenges that I faced when the code was not working as it was supposed to, the login and sign up code was especially challenging, especially since this is my first time participating in a hackathon as well as making a mobile app.
Accomplishments that I'm proud of
I am very proud of myself in finishing this app especially in the time constricts of the hackathon. I put in a lot of hard work and sweat and am pretty glad of how the app came out to me. I do think with more time I could have done a little better with the user interface such as how to add profile pictures or perhaps users can choose to share their information or not and adding more features.
What I learned
I think the most important skill I have learned from this hackathon is time managment and perserverance. There are many times late at night when things were not working out and I simply wanted to give up on that app, but I decided to fight through and I am pleased with the solution that came out as I genuinely believe that it could help and connect people all around the world.
Built With
css
xcode
Try it out
github.com | Quarancare | An app to connect low income families to volunteer doctors in order to get a medical opinion without any cost. | ['Tanya Vaish'] | [] | ['css', 'xcode'] | 68 |
10,341 | https://devpost.com/software/no-touch-disinfectant-wipes-dispenser-53srhw | Future Ideas
The project
The arduino code
The circuit
The problem
Hey, I am Tanya Rustogi and I got the idea of the wipes dispenser when I was thinking of how Covid-19 is affecting developing countries. My first thought was that to open a wipes container like lysol you need to touch at least two surfaces which can spread coronavirus. Additionally, having a container of wipes per person in an office or school is not realistic due to the shortage of disinfecting wipes. Then came the idea of an affordable, easy disinfecting wipes dispenser that can be used for classrooms to day cares to shopping carts everywhere.
The solution
So what this dispenser does is when an object such as your hand comes within ten centimeters of the sensor, the motor starts moving which is connected to a rod with rolled up wipes on it. The rotation of the motor moves the roll of wipes, causing them to unroll and make their may out of the container.
How to build
So, each of the pins except the ground and vcc on the motor driver are connected to pins on the arduino, which we defined in the code. The trigger and echo pin on the sensor are also connected to the arduino which are defined in the code. Then the ground and vcc of both the motor and the sensor are connected to the ground and vcc of the arduino which is connected to the power. The sensor detects the distance by seeing how long it takes a wave to come back. The code on the arduino makes sure that if the sensor detects something within 10 centimeters of it, it runs the function stepper which causes the motor to run. The container is made from the lysol container, hopefully making it cheaper for developing countries. The container has two holes, one for the wipes to come out from and one for the motor. Then we need to connect the motor to the container which I achieved with tape. The rod connects to the motor which is held on the other side through the hole already provided in the lysol container. Now when the motor rotates, the rod rotates as well.
What’s next
This is just a prototype, with more material, the final product would look cleaner with a box covering the circuits and the pcbs and circuits connected to the container.
What did I learn
I think the most important thing I learned through this experience is time-management due to the time constraints of two days to make the whole thing as well as perseverance to be able to try again despite how many times the circuit and the code did not work as it was supposed to.
Built With
arduino
arduinoide
steppermotor
Try it out
github.com | No-Touch Disinfectant Wipes Dispenser | A prototype of a no-touch dispenser that is easy and affordable to make and could be used from cleaning tables to disinfecting carts. | [] | [] | ['arduino', 'arduinoide', 'steppermotor'] | 69 |
10,341 | 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'] | 70 |
10,341 | https://devpost.com/software/utilizing-vtol-to-predict-and-analysis-possible-wildfire | Introduction
Code
Engineering
Results
Inspiration
The current method of predicting forest fire is by using a satellite imaging system. This is very inaccurate as it DOES NOT use real-life samples. This is not only a guessing game but makes it impossible to know where the fire would start or where it will spread more quickly. With all the current technology we have, we should be ashamed that we were not able to stop the great fire in Australia nor predict it. Firefighters were risking their lives to prepare for every situation.So, instead of deploying many firefighters as we can, we should be able to mark the most affected area and stop it from the start. Not only this is a safer way but also a faster method. The goal for this project is to use REAL LIFE samples and make a forest fire prediction model based on these data. The final product should be able to fly by itself through the trees, take its own samples, does not involve any human interaction, and most importantly, it should be able to predict where the next forest fire will start and its path if it happens using the data it gathered.
What was the problem?
Cost and impact of wildfires is rising
California Camp Fire 2018 : 86 dead; $16B damage; $4B uninsured; 62,000 ha burned
Eg. Thomas Fire Flooding (2017) Well known that loose soil worsens floods dramatically after fire Rain 4x higher than any model predicted few months after a major fire
-Fort McMurray, Alberta 2016 – 90,000 people evacuated, $9B (CND) damage, 590,000 ha burned
BC and Ontario 2018 had historic fire year 1985: 2 million ha 2018: 8 million ha 4% of the entire province in burned in the past two years (BC is 2.2 x the size of California)
Current simulation methods have high precision but:
They often underestimate the scale of fires and risk
Computationally expensive to run many times (manual modeling)
Hard to adapt to changing climate conditions or poor regions of the world
What it does
I hypothesize that the utilization of VTOL to predict and analyze possible wildfire will be more effective than the current practical system as it uses the current method but also the samples from the real environment to have more precise and accurate information. The combined utilization of satellite information, real-life samples, and machine learning will result in a better-understood wildfire prediction model which can be used in real-time with the on-board computer. The goal of this project is to create a fully functioning VTOL that follows the original things I described: Use real-life samples and make a forest fire prediction model based on these data, Flyby itself through the trees, take its samples, does not involve any human interaction, and most importantly, it should be able to predict where the next forest fire will start and its path if it happens using the data it gathered.
What plane is it and how does it work?
Depending on the terrain and conditions, fixed-wing aircraft are not always the best working UAV, but the vertical take-off and landing (VTOL) drones are the ones that could work on almost all different types of terrains. Because there are four motors, vertical takeoffs and landings are possible, and because there are more motors, VTOLs can carry more weight. The design of the aircraft shows how it only needs to use one "Pusher Motor" to fly in the air. This will not only save battery life but also fly faster when there is more weight on board. As you can see the tails and the elevator allows the drone to use less fuel since it is only turning the servo motor to change direction instead of changing the speed of all 4 motors.
The steps of building the plane
All the materials were gathered before building, including all the wires, motors, servo motors, foams for the board, glues, soldering tools, and the rest of the tools that were required to craft the plane. The plane was made following a pre-made model called Skyhunter 1800 which is a long-range map surveying plane.
Learning from the flitetest guide(A forum dedicated to people who like building their own plane), I placed all the motors and servo motors to where I was planning to place them. Then I cut and placed all the Styrofoam boards to make the plane outline.
The plane head was made by cutting a Styrofoam box, I placed a strong wood inside to make sure that even if it was to crash, it won't damage anything inside of the head. It will safely keep the data, all the hardware, and all the software.
I followed the wiring diagram from one of the pictures below to connect all the motors, esc and servo motors to the APM 2.8. By doing so, it allows the APM to control the motor so it can fly by itself. It also allows the Arduino sensors to control the plane as well so it will not crash into the ground.
By connecting the runcam to the transmitter, it allows me to view what the plane is seeing through the computer. The range depends on the location but, since I have APM 2.8 and the Arduino sensors, it is really not necessary to have the FPV setup done. However, it will help me to guide the landing of the VTOL.
After connecting all the wires and setting up all the necessary hardware, I used a program called betaflight which is normally for a drone. Since VTOL is primarily based on a drone, I still can use this software but modify it to fit my VTOL.
Challenges I ran into
Well, one of the biggest problems that I had was getting all the money for this project. As a high school student, I do not have many choices as I would if I was an adult. Being so, I have worked on different part-time jobs such as math tutor in order to gain all the funds for this project. As for hardware and software, all the information I need is on books, youtube, and most importantly Google! I also like to mention IEEE for helping me with this project by donating a small funds to cover 25%of my project!
Accomplishments that I'm proud of
I loved the fact that I got to work on something big like this! Due to the situation, I had much free time from school and this allowed me to dig into my own interest which inspired me to plan, start, and finish this project for this hackathon!
I have learned a lot from this project, I learned how to make a plane that can fly by itself and a code that uses the given information to predict the future!
What's next for Utilizing VTOL to Predict and Analysis Possible Wildfire
Feature Evaluation and Dimensionality Reduction
When building models, I did not take into account the statistical significance of each parameter. Instead, I simply chose to include all independent variables. The first method of improving the model is to determine and only use the features which are most statistically significant to the independent variable(s).
Methods
Backward Elimination
A feature selection technique while building a machine learning model. It is used to remove those features that do not have a significant effect on the dependent variable or prediction
of output.
Forward Selection
A type of stepwise regression which begins with an empty model and adds in variables one by one. In each forward step, you add the one variable that gives the single best improvement to my model.
Bidirectional Elimination (stepwise)
A forward selection procedure but with the possibility of deleting a selected variable at each stage, as in the backward elimination, when there are correlations between variables. It is often used as a default approach.
With all of these improvements, I believe it could increase the accuracy of up to 85%(Each one being about 5% from small sample tests). This could be a major improvement as it is reducing a lot of burned areas. However, this will require way more time as I need to be very precise with the variables and the machine will take a longer time to process all this new information with new types of data. I would also love to work with the UN as they have more accurate data of maps for their search and rescue team for national parks. Using these data, I would be able to train the model to learn more about different types of data.
I would also love to work with any organization to improve my project!
Built With
artificial
classification
machine-learning
network
neural
weka | Machine Learning-Utilizing VTOL for Wildfire | The purpose of this project was to use VTOL to improve the analysis of the wildfire and to predict its future path based on the analysis, it also uses real life-time data to have precise information. | ['GyuTae Bae'] | [] | ['artificial', 'classification', 'machine-learning', 'network', 'neural', 'weka'] | 71 |
10,341 | https://devpost.com/software/ar-anatomy-827wgq | Ar view
Inspiration
As we know that this pandemic is really tough for us so I made an AR app which will help the people as well as the doctor
What it does
It will give the virtual world related information of our body parts.
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for AR Anatomy
Built With
augmented-reality
echo-ar
Try it out
drive.google.com | AR Anatomy | AR based app for the hospital | [] | [] | ['augmented-reality', 'echo-ar'] | 72 |
10,341 | https://devpost.com/software/well-beings | WQS self assessment test layout
Media kit
Mind map
Messenger screen #1
Messenger screen #2
Inspiration
Mental disorders affect
one in four people
. Treatments are available, but nearly
two-thirds of people
with a known mental disorder never seek help from a health professional. The stigma around mental health is a big reason why people don’t get help. This needs to change. By changing the attitude towards mental health in a community setup, we believe we can create a domino effect of more people opening up as a result of increased social and sympathetic views on mental health.
Our Solution - Wellbeings: A Community
Wellbeings is a Mental Health Community. Unlike most mental health communities, Wellbeings is inclusive to even people that are unaware of mental health problems. This community is called Wellbeings because we want to de-stigmatize mental health.
Our solution to the problem is to provide access to vital information so that people can educate themselves on types of mental health problems, identify any warning signs by a quick self-assessment, information, and resources including helplines, advice on helping someone else, tips on wellbeing, etc.
We want this done in the most interactive way possible, which we believe we can achieve by creating a chatbot and a community that is synonymous with peer support groups. We want to focus on the idea that people with mental illnesses are not abnormal or some isolated group of people, but as many as 1 in 4 people in the world will be affected by mental disorders at some point in their lives. By creating a community, we want to reach out to the victims as well as the general public because they are likely to know someone who suffers from mental illness.
Collectively in a community setup, we harness a "me too" feeling and help members become advocates of mental health.
To sum up, we aim to
advocate the importance of mental wellbeing,
make information accessible and available,
tackle stigma,
empower community,
support people by aiding recovery through early identification & intervention.
Who are we?
We are a team of 4 people - which consists of a developer, a designer, and 2 doctors. All of us share a common vision to improve the intricate health system with the use of revolutionary technologies. Mental health is one of the issues we feel strongly about.
How we built it
Our messenger bot is powered by wit.ai to handle all the NLP tasks. The webhook managing all the backend logic and scoring is built with flask. For the bot flow, we have used Chatfeul. And for the self-diagnosis of disorder, we have used the WQS standardized test.
Challenges we ran into
Most of the people don't even know that they are suffering from some kind of mental distress, so they usually are not engaged with apps and bots marketed as self-diagnostic/help apps. To even reach to that naive user, we have taken a community approach to engaging him by providing a comfortable community which will be pictured by the user as the answers to his unknown problems. Once engaged, we can help him use our bot to take the assessment and know about his/her mental wee being.
Most of the self-diagnostic tests available are lengthy or too monotonous so implementing it in a bot is not a good experience and the drop out ratio of users becomes high. So our team of health professionals selected WQS from various different standardized tests and modified it to be more interactive and less negative to increase conversion ratio. Also, the questionnaire has around 50 questions but we have made it dynamic to the users are not given disorder-specific questions if his/her response is negative to the screening question. So for a normal user, the effective number of questions is around 15-20 which improves the number of people who complete the test.
What's next for Well Beings
We don't stop here. We aspire to engage as many people as we can and bring this to every person who is unknowingly possessed by this demon. We also want to educate the community about mental well being so that they can understand its importance and observe the silent cues of people in distress.
We plan on scaling this solution in the following ways
Incorporate health care professionals to help members with an accurate diagnosis
Add a database of country-wise helplines
Work on suicide prevention
Improve the self-help questionnaire
Make our bot even smarter (Thanks to wit.ai)
Incorporate CBT (Cognitive Behavioural Therapy) to assess and help people with mild symptoms here in our community only.
Built With
chatfuel
flask
glitch
messenger
wit.ai
Try it out
www.facebook.com
glitch.com
m.me
mm.tt
www.mindmeister.com
www.figma.com | Well Beings | Creating an organic space to nurture mental well being! | ['yash aggarwal', 'Uday Upreti', 'Pallavi Thakur', 'Banipreet Kaur'] | [] | ['chatfuel', 'flask', 'glitch', 'messenger', 'wit.ai'] | 73 |
10,341 | https://devpost.com/software/face-alert-system-c9uo1t | App Logo
Uncomplicated Architecture of the app+
Choosing the best model
Basic Working of App
Problem Statement:
With the outbreak of Covid-19, health care professionals are urging people to regularly refrain from touching their face. There’s no question it’s easier said than done.
According to a study, people touch their faces more than 20 times an hour on average. About 44 per cent of the time, it involves contact with the eyes, nose, or mouth.
From picking up objects to turning doorknobs, we’re constantly touching surfaces contaminated with pathogens.
The coronavirus that causes Covid-19 is believed to be spread mostly by inhaling droplets released when infected individual coughs or sneezes. But the virus can also land on surfaces that we touch with our hands.
But as anyone who has consciously tried to do so knows, it’s hard. Touching our face is an act that most people perform without thinking. Whether it is something intrinsic to our species or learned behaviour, we continue to repeat it even if we intend to or not.
Inspiration
Asthma is one of the major diseases that my grandmother has faced.
Because of which she can’t put on a face mask for the longer duration of time. She always wishes to have something that can perform both jobs parallelly, protect her from coronavirus and also not suffer from difficulty in breathing. That is why this idea of making a face alert system pitched to me.
What Is Being Done?
Government has made the use of face mask mandatory but we have seen at times people don’t put the face mask on due to various reasons such as:
Face masks needed to be changed after every few days hence making the prevention costly.
Many people have reported difficulty in breathing due to face masks.
People do not put on their face masks when they’re at home but the chances of them getting infected still persists.
Eyes of the person aren’t covered which is also a potential target for the virus.
Hand Sanitizers are also used to kill the bacteria but as we all know that hand sanitizers are used less frequently as compared to our hands touching our face.
Our Solution:
An app that works like an alert mechanism to prevent us from touching our face and hence it can help to prevent the spread of covid-19.
If the user moves his/her hand towards their face then the app generates an alert and the phone starts vibrating
It works as follows:
When the user moves his hand, the device collects accelerometer data and sends it to the API as a JSON file.
The API is backed up with a machine learning model.
The machine learning model is well trained to differentiate when a hand is near the face and when it is not.
Our backend algorithm calculates the Roll, Yaw and Pitch using accelerometer data which can be used to define the orientation of the device.
So whenever the user brings his or her hand near the face, the backend model raises an alert and the device starts vibrating.
We’ve further integrated Watson ChatBot with our app to help people with their covid related queries.
WE’VE USED SVM TO TRAIN OUR MODEL AS IT GIVES THE HIGHEST ACCURACY
We’ve currently designed the app for android phones and wearOS smartwatches.
Benefits of using our App:
This app won’t replace the use of facemask and hand sanitizer but it acts as a second line of defence to stop the spread of covid-19.
Facemasks don’t cover eyes and this can be an entry point for the virus. Hence using our solution we can prevent touching our eyes even when our face mask is on.
People generally don’t wear face masks at home, but the danger of getting infected still persists. Hence our app can provide all-round protection without even actually using it.
It’s like a boon to people with Asthma as they can't put their face masks on for a longer period of time.
Hand sanitizers are used less frequently as compared to our hands touching our face. Therefore our solution can help people when hand sanitizers aren’t easily available.
Business Model:
Our product is the second line of defence and it syncs perfectly in the background keeping the user uninterrupted with his daily tasks. And that’s the USP of our product.
SLIDE CHANGE
Our Business model relies on the revenue generated by the ad’s that will pop up on our app. This is a win-win situation for both the users and developers. People need no extra device to implement our system. Hence it can be used by a large number of people. Therefore it can generate a large amount using ad revenues.
The users who want uninterrupted services with additional features like daily statistics can purchase our premium app.
Other sources of revenues can be generated by collaborating our idea with companies that manufacture fitness bands. They can integrate our solution into their mobile app and provide an additional feature to their users. Since no fitness band manufacturers have come up with a solution like this hence we can attract the companies with our idea.
Such a system is non-existent in India (at least) thus making it a one-of-a-kind proposal. Hence this idea can attract a lot of investor’s
Future Roadmap:
Testing of the Fitbit app is under process and the stable version will be released soon also we're focusing to attain compatibility of our app with other fitness bands as well.
We can add an additional feature in future versions of the app that will alert the user if they’re near the infected user. Data of the users will be stored in the cloud Database. Hence this will attract more and more users to use our app.
We’re planning to deploy our system completely locally. Hence, users won’t require the internet to access the services.
FAQ:
Q. What all devices and OS your app has supported?
We’ve recently released apps for smartphones (for testing purpose) and smartwatches (for Wear OS watches), development of the app for other devices are under processes such as Fitbit and Fossil.
Q. What if we don’t have an internet connection?
The first version of our app requires the internet to operate but we’re working on to deploy the system locally and the next version of the app won’t require the Internet to work on.
Q. While I’m on call will my band vibrate continuously?
No, we’ve taken care of that problem therefore when you’re on a call the app gets an alert and it doesn’t vibrate, we’ve achieved this using PROXIMITY SENSOR.
Q. What is the accuracy of the model you’ve used?
We’ve used different models to test and the model with the best accuracy is used for deployment. Currently, it’s accuracy is around 91%
Built With
android-studio
heroku
machine-learning
react
Try it out
github.com | Face Alert System | An app that works like an alert mechanism to prevent us from touching our face and hence it can help to prevent the spread of covid-19. | ['Naman Mehrotra'] | [] | ['android-studio', 'heroku', 'machine-learning', 'react'] | 74 |
10,341 | https://devpost.com/software/truth-seekers-5ofvy2 | Inspiration
News articles found online are usually from untrusted sources and are unverified. The community is at a high risk of falling into the trap of believing fake news articles. Spreading fake news can have severe repercussions such as heavy fines and possibly even jail time. Especially during this period of the pandemic, fake news can lead to mass panic.
What it does
Our application aims to curb the spread of fake news using the EOSIO blockchain platform, ensuring only reliable articles from trusted sources are promoted with the help of validation experts and by providing a community-driven platform.
How we built it
The web application was developed primarily using Node.js and Bootstrap with the EOSIO Javascript API for integration with EOSIO-based blockchain. The mobile application was developed using the Flutter SDK.
Challenges we ran into
One of the initial challenges we faced was the installation of the EOSIO CDT and the software platform. Furthermore, we also spent time familiarizing ourselves with the EOSIO Blockchain Platform and the recommended IDE, EOSIO Studio. But soon after, the platform was easy to use and thus, connect and integrate smart contracts with our application.
Accomplishments that we're proud of
We were successfully able to integrate the EOSIO blockchain platform in our application and thus ensure transparency through the voting transactions and more importantly, provide a secure platform to store the articles and their respective categories.
Additionally, we were able to develop a fully-functional cross-platform web and mobile application built using Node.js and Flutter respectively.
What we learned
We were able to learn extensively about the EOSIO blockchain platform, understand its salient features when compared to other blockchain vendors. Moreover, we have realized the vast potential of research necessary in this field especially during this time of the pandemic in order to enable reliable news from trusted sources.
What's next for Truth Seekers
We aim to partner up with sponsors to grow our reward and badges system. More importantly, be able to find a more optimum strategy to backup our scoring process, as well as, provide a global platform for qualified validators and users to combat fake news as a community.
Built With
adobe-creative-sdk
blockchain
eosio
flutter
node.js
Try it out
github.com | Truth Seekers | Curb the spread of fake news, ensuring only reliable articles from trusted sources are promoted with the help of validation experts and by providing a community-driven platform. | ['Rikesh Makwana', 'Aaishwarya Khalane', 'Alister Luiz', 'Bhargav Modha'] | ['The Wolfram Award'] | ['adobe-creative-sdk', 'blockchain', 'eosio', 'flutter', 'node.js'] | 75 |
10,341 | https://devpost.com/software/covidnet-jq97oa | Our site's homepage.
Site homepage (ctnd).
A diagram showing the relationship between the various components in our project.
covidNet by Anirudh Kotamraju and Kailash Ranganathan - A Deep Learning Powered Coronavirus Visualization and Prediction Software
Inspiration
Coronavirus is undeniably the most major problem of current times, but it seems that quarantine and the effects it is having on the global market and on people’s lives are influencing a new wave of openings, and with it, an even stronger and more potent virus.
People are not adhering to social distancing as much, and while we understand their perspectives to want to quickly resume their normal lives, we wanted to deliver an objective and informative way to show people that coronavirus is more potent and spreading faster than ever.
To do this, we built covidNet, a realtime web app that uses up-to-date coronavirus data to display the growth of the virus in all US states and also use deep learning to give predictions and insights into how coronavirus will grow over the next 30 days using recurrent neural networks. This will be able to give a better insight into how coronavirus could grow over standard regression and curve-fitting models in place.
What it does
covidNet delivers a neat and clean UI straight to your device that gives visual data for all 50 US states on total cases and how they have grown since the start of the coronavirus outbreak. But the main attraction is the prediction curves, where we trained individual “recurrent neural network” models for each of the 50 states to analyze how the virus has grown over the past few months and continue the curve to predict the virus’s cases over the next 30 days, a lookahead from today. Quick highlights for predicted (total) cases tomorrow, in 3 days, and in one week are also visible for each of the states. The website is updated daily.
Each day, a Google Cloud Virtual Machine automatically starts up. It gets the new data for the day, and automatically trains each of the 50 models using the new Johns Hopkins data (not from scratch, but starting from the previous day’s trained models). It then uploads the new models’ predictions for the historical time and the next 30 days into a Github repository as well as the model files for the next day’s training. Whenever a user visits the website (hosted on Heroku), the predictions are taken from this Github repository. Thus, both our models and website are automatically always up to date with the newest trends in each state's fight against the pandemic.
With this project, we are able to give well organized and accurate predictions using state-of-the-art deep learning methodologies of what the virus could become in each state if further action is not taken. We hope that this will help present the true danger of the uncontrolled virus and encourage preventive action to be taken in the future.
How we built it
We used Dash and Plotly for our frontend, libraries especially relevant for visualizing data science results. With this, we are able to efficiently and effectively integrate our neural network prediction backend with a clean frontend all in Python with some CSS formatting.
The model updating happens on a Google Cloud Virtual Machine. It is configured with CRON to automatically start up at a certain time and run a startup bash procedure each day. This procedure begins training the models and pushing the csv and model files to our main github repository, where these results are integrated with our frontend. It features a streamlined python script that fetches data from Johns Hopkins, formats it and retrains 50 state models, and saves those to files as well as their historical and 30 day future predictions to a csv. The models are trained using 2 layer deep LSTM neural networks, with dropout rates of 0.2-0.3 implemented to prevent overfitting. The model files are saved so that on the next day, rather than starting training on the dataset and next day’s data from scratch, the training can load in the preexisting model and continue from there, making the model more accurate as time goes on.
The website is live and anyone can access it at
https://covid-net.herokuapp.com/
. Because our training is scheduled, the website and models are automatically updated daily without us having to do anything.
Challenges we ran into
Because LSTM’s are more complicated structurally (and time-dependent as opposed to normal ANNs) than normal feed-forward neural networks, our analysis of coronavirus time series from raw data was quite difficult. We spent a long time devising algorithms to convert the data from raw text (from the Johns Hopkins coronavirus dataset) to properly formatted and normalized tensors to run through our LSTM but were able to generalize this process and train a model given state data just by inputting the state name into our program. With this data our models devised, we were able to quickly create interactive graphs with it to display on our website.
Furthermore, one of the most important parts is that the whole program updates daily automatically, meaning that we don't have to manually change anything and the models will automatically take data from the dataset, continue training from the previous day's models, and fit to the new data while becoming more accurate. This was extremely hard, as we had to go from a python script that ran one model at a time to one that took data, formatted it, and trained and saved all models in an organized manner. Furthermore, integrating the frontend and backend using Github was also a challenge between configuring the GCP Virtual Machine and Heroku.
Accomplishments that we're proud of
We are proud that we were able to write the neural network, train 50 individual models on 50 individual datasets (one for each state), and deliver it in a functioning and visually pleasing UI in the timeframe of the Hackathon. We were able to functionally link the backend neural network Tensorflow model with the frontend Dash and Plotly web app and in the end, could deliver a useful and easy to use visualization of current coronavirus statistics for all 50 states and our deep learning predictions for future cases starting with the next 30 days. Because daily updates from a virtual machine have zero room for error (or the whole website comes crashing down), our process for automatic updates is robust, reliable, and organized well so that connections between backend and frontend are clear (through GitHub). We are also proud of the completely automated model and data update process, which updates the models using *
bash scripts on Google Cloud, then writes them to Github, and the Heroku app accesses those updated data files on Github and presents them to clients on a real time basis. *
What’s next for covidNet
Our application and neural network still have some refining to go through, even though it works quite well for all 50 states as a prediction device. We wish to make a bigger, deeper, and more powerful LSTM network to detect more subtleties and insights in the coronavirus data, and also bring in more variables, such as the openings of states, different social distancing orders, and other factors that may affect the spread of the virus. We already expanded on this project by going from only 37 states in a static website initially to a realtime, updated daily website with not only more accurate results but new data and extra training every single day. Perhaps with more computational power and a multivariate system, we will be able to not only predict coronavirus cases, but simulate different paths for the virus using different societal and community parameters, such as level of lockdown, average interaction among crowds, and others.
We hope you all stay safe and have fun :)
Built With
dash
github
google-cloud
heroku
numpy
pandas
plotly
python
scipy
tensorflow
Try it out
covid-net.herokuapp.com
github.com | covidNet | A Deep Learning Powered Coronavirus Visualization and Prediction Software | ['Hoponga (Kailash Ranganathan)', 'Anirudh Kotamraju'] | ['Second Place'] | ['dash', 'github', 'google-cloud', 'heroku', 'numpy', 'pandas', 'plotly', 'python', 'scipy', 'tensorflow'] | 76 |
10,341 | https://devpost.com/software/favorite-coding-language-survey | Inspiration
I would love to hear everyone's opinions on their favorite coding language!
What it does
It gathers information based on your selection of your favorite language
How I built it
I built it using HTML and CSS!
Challenges I ran into
Connecting the button
Accomplishments that I'm proud of
The whole survey
What I learned
Have alot of patience!
What's next for Favorite Coding Language Survey
Hopefully I can keep improving it and make it longer and better!
Built With
css
html
Try it out
codepen.io | Favorite Coding Language Survey | I created this survey to hear opinions on the favorite coding language of different people. | ['Isabella Acosta'] | [] | ['css', 'html'] | 77 |
10,341 | https://devpost.com/software/global-soft-support-ylwf41 | IBM Watson Assistant Chatbot
Inspiration
I saw a story about a female soldier who was brutally raped, and sexually harassed by her comrades. She could do nothing. No one payed attention to her story, and she suffered for months, after which, the story came out on Instagram. Why couldn't she seek support then? Where could she seek support? Nowhere. All these social media and entertainment sites are there for your entertainment. But when someone is in trouble, and needs help from the rest of the world, these apps are useless.
People all over the world have problems and situations they are in, that they cannot share with others in the fear of what their friends will think, what society will think about them. And most of the time, because they don't know where to go. The people are in need of advice, and just want someone to talk to them, and tell them what to do. That is because it is really hard to make tough, and beneficial life decisions when you are under constant abuse-both mentally and physically. I realized how much of a problem this was, decided to make a move.
What it does
Global Soft support is an online web app where anyone can anonymously describe their situation and troubles, and someone from any part of the world will answer them with a way to get out. You can also talk with the ChatBot! SO no one will track you, and you can get inputs on your situation from a person who has a way clear mind!
How I built it
We used MongoDB as my backend database. I use node.js as the backend script, and connected that with the middleware using express. I also applied the IBM Watson ChatBot Assistant in my project. I created this from scratch, and have it working on my site. have deployed everything using Heroku.
Challenges I ran into
I started off with an idea, clueless about which technologies I should be using, or if I would be able to use them or not. It took me 2 days to plan the project, and 1 day to code. But in the end, I did it!
Accomplishments that I'm proud of
I was able to make a full stack project from scratch(I did not use any GIT cloning :) ). Not only that, but I learned and we created at the same time.
What I learned
I learned how to use node.js and express to connect my backend(MongoDB Database to my front end)
What's next for Global Soft Support
I plan on reaching out to each corner of the world, and providing this website to everyone who is in need. I also plan to refine the site to be more user friendly.
Built With
amazon-web-services
dom
express.js
ibm-watson
mongodb
mongoose
node.js
purify
slugify
Try it out
github.com
global-soft-support.herokuapp.com | Global Soft Support | An online web app where anyone can anonymously describe their situation and troubles, and someone from any part of the world will answer them with a way to get out. You can also talk with the ChatBot! | ['Labdhi Jain'] | ['Amazon Gift Cards'] | ['amazon-web-services', 'dom', 'express.js', 'ibm-watson', 'mongodb', 'mongoose', 'node.js', 'purify', 'slugify'] | 78 |
10,341 | https://devpost.com/software/socialdistancer | Social Distancer
This app keeps people 6 feet away
This simple but useful App uses your iPhone’s camera to alert you when someone is within your six-foot safety zone.
Click on the App and your front camera opens as you point it at anyone nearby. If someone is within 6 feet, the box around the person turns red. If the person is more than 6 feet away (approximately 2 meters), the the box around the person turns green.
How to use
Hold phone horizontally while directed at people. If the box around a person is green, they are beyond 6 feet from you. If the box around a person is red, they are within 6 feet of you.
If there is no box when the camera is pointed at a person, than the camera does not see the person clear enough.
Works best when the target person is standing.
How Does it Work?
Social Distancer was created in Xcode and Android studio using Swift and Java. They both use the YOLO Object detection model to track people. When the camera sees a person, the app estimates the distance of the person based off of the size of the person in pixels.
Releases
Apple version can be demoed here:
https://ariwasch.applivery.io/social-distancer
Android version can be demoed here:
https://play.google.com/store/apps/details?id=org.microincorporated.socialdistancer
NOTE
Social Distancer was taken down from the app store after Apple introduced new policies to prevent the spread of false information of Covid-19. That means no social distancing or Covid-19 related apps are allowed to be published by individuals. If anyone who is reading this is part of a recognized institution (hospital, government agency, university) and would be willing to publish it, the developers of both the Apple and Android version would be willing to do so.
Additionally, we are willing to donate a majority of the ad revenue to Covid-19 relief efforts once both apps are published.
Contact us
For more information, email
ariwasch@gmail.com
or
lincolndoney@outlook.com
Prerequisites
You need an Android device and Android development environment with minimum API 21.
Android Studio 3.2 or later.
Built With
java
Try it out
github.com
play.google.com
microsyncinc.github.io
ariwasch.applivery.io
github.com | Social Distancer | This simple but useful App uses your phone’s camera to alert you when someone is within your six-foot safety zone. | ['Lincoln Doney', 'Ari Wasch'] | ['The Wolfram Award', 'First Place - Covid Track'] | ['java'] | 79 |
10,341 | https://devpost.com/software/bemyeye | app logo
Inspiration
Our eyes allow us to see the world. They help us carry out several tasks at ease, something we often overlook and take for granted. Visually impaired people struggle with tasks we consider to be very basic. For instance, shopping. The challenges they face are unimaginable . Globally the number of people of all ages visually impaired is estimated to be
285 million
, of whom
39 million
are blind. So this project is an initiative to help make their lives easier.
What it does
Mobile App
beMyEyes helps the visually impaired shop conveniently by :
Detecting and Identifying objects around
Narrating the type of object identified
Reading labels on products using OCR (Optical Character Recognition) and narrating it to the user
Connecting with a human assistant nearby to help the visually impaired user with shopping
It's compatible for both Android and iOS.
Website
The website enables volunteers to help visually impaired shoppers in their area by acquiring their information on the sign up page so they can be notified via text when a volunteer opportunity arises in their area.
How we built it
Mobile App.
Twilio
- Used for messaging between users. helpers and system.
google cloud vision
- used for ML object recognition
clarifai
- Used for identifying food
gcp OCR
- used for text identification
React-Native
- Used For building a cross platform app.
Expo-Speech
- Used for narration of results and providing instructions to the user
Adobe Illustrator
- Used for designing the logo, assets and UI for the app
mongodb
- Used for storing users helpers and matches data
Website
Maps JavaScript API
- Used For Embedded Interactive Google Maps and Auto-fill feature for the address slot in the form
Geocoding API
- Used For Embedded Interactive Google Maps and Auto-Fill feature for the address slot in the form
Semantics UI Library
- Used To Create Button on Join Page
Places API
- Used For Embedded Interactive Google Maps and Auto-Fill Feature for the address slot in the form
Figma
- Used to create prototype of website
Languages
- HTML, CSS, and Javascript were utilized to build the website.
*api deployment and testing : Sashido app was created and used for testing various API endpoints used in the system
Challenges we ran into
First of All , Our teammates are from different time zones So, It was a challenge to maintain real-time communication.
For some of us React Native, and image recognition and image captioning and working with API was the first experience. Still We managed to do it unitedly.
Accomplishments that we are proud of
Overcoming the above challenges were the Biggest accomplishments.
What we learned
Through this project we had the opportunity to learn React Native , Object Detection, OCR, Image Captioning, Text Generation, and text to voice conversion.
What's next for BeMyEye
For the project’s future, We think of integrating it with every shopping mall and market for better reach. So, that product can easily help the person in need .Also we can integrate it with sensors and spectral anagram for obstacle detection . Which will in turn help the visually impaired walk with minimal risk.
Built With
adobe-illustrator
css
expo.io
figma
gcp
geocoding-api
html5
javascript
maps-javascript-api
places-api
python
react-native
sashido
semantic-ui
twilio
Try it out
github.com
drive.google.com | BeMyEye | An additional set of eyes for the visually impaired | ['Ashish Kumar Panigrahy', 'Ebtesam Haque', 'Mualla Argin', 'Muntaser Syed'] | [] | ['adobe-illustrator', 'css', 'expo.io', 'figma', 'gcp', 'geocoding-api', 'html5', 'javascript', 'maps-javascript-api', 'places-api', 'python', 'react-native', 'sashido', 'semantic-ui', 'twilio'] | 80 |
10,341 | https://devpost.com/software/fridgeremindr | Auto generated grocery list based on items needed
Suggested recipes
air quality measurements showing a spike in particulate values (someone coughed or sneezed)
Essential groceries list
Expiry date recognition
Product identification
the air quality workshop which inspired us
attending the rust workshop for the learning and the bonus points
at this point we were wondering if we could build it cheaper and better
air quality workshop
the sps30 sensirion sensor up close
sensor basic hardware setup
Inspiration
Like it or not, grocery shopping is a major unavoidable chore. Especially in these circumstances, shopping can be a pain and we decided to automate the tediousness of checking expiry dates, whats in the fridge/pantry and also whether we should wear a mask indoors (sometimes we should, especially if there is company) the workshop on Saturday inspired us to build a cheaper and better quality air sensor which can even detect cough and sneeze droplets indoors
What it does
there are two main sets of features:
1: shopping list generation and expiry date detection. All you have to do is take pictures of what’s in your fridge and kitchen, FridgeRemindr takes care of the rest. The app detects the products present in the images using machine learning and generates a list. It lets you add essential items to a list along with their expiry dates. The app keeps track of the dates and generates your grocery shopping list for you. FridgeRemindr also generates a shopping list for you based on your cravings. All you have to do is name the dish you want to prepare. You could exploit this feature to help you prepare for a potluck, Thanksgiving dinner or any special occasion. FridgeRemindr compares the list of ingredients required with the items you have at home and generates the list for you.
2: active air quality monitor
the price and functionality of the purple air sensor was shockingly high, so we "borrowed" a sensirion sps30 sensor which is probably the most accurate retail available air quality sensor which is less than 45$ retail. paired with a DHT11 (less than 3$ retail) and a cheap microcontroller with wifi (esp32, less than 7$ retail) it is possible to build our sensor for a hardware price of under 55$. This setup senses particles from pm10 levels all the way down to pm0.5 levels. This is important because respiratory droplets, airborne pathogens and micro pollutants can be detected at this level of granularity (we actually tested if a cough or sneeze can be detected, and our sensor can do this: video here - ) our setup uses a dht11 for temperature and humidity but we can also use a better sensor like a bme280
.
basic video
https://youtu.be/QD7vP-gXwbU
hardware video 2:
https://youtu.be/iIwDxE88KfY
How we built it
hard work and perseverance and no sleep
Machine learning: used models from GCP cloud vision and clarifai
OCR - used google cloud and tesseract
Servers: used python flask and GCP functions
React-Native to build a cross platform app
Adobe Illustrator for designing the logo, assets, UI/UX
Hardware : sensirion sp30 particle sensor, dht11 temperature and humidity sensor, ARduino, raspberry-pi (didnt make the UI, ran out of time :( )
Ngrok tunnels everywhere
nodejs/express : push notifications server
Scientific references
.
https://www.sensirion.com/fileadmin/user_upload/customers/sensirion/Dokumente/9.6_Particulate_Matter/Datasheets/Sensirion_PM_Sensors_SPS30_Datasheet.pdf
https://www.ncbi.nlm.nih.gov/books/NBK143281/#:~:text=Published%20data%20have%20suggested%20that,the%20same%20number%20as%20talking
Challenges we ran into
coding for the sps30 was challenging (had to adapt some things directly from datasheet).
Accomplishments that we're proud of
the things all work.
What we learned
its hard work integrating everything
.
What's next for FridgeRemindr
.better integration of components
more robust hardware and casing
better notification system
Placing orders automatically for essential groceries
Built With
adobe-illustrator
arduino
clarifai
dht11
raspberry-pi
react-native
sps30
Try it out
github.com | FridgeRemindr | Automated grocery shopping | ['Ebtesam Haque', 'Muntaser Syed'] | [] | ['adobe-illustrator', 'arduino', 'clarifai', 'dht11', 'raspberry-pi', 'react-native', 'sps30'] | 81 |
10,341 | https://devpost.com/software/boardsafe | Boarding status
Book your seat
Choose your mode of transport
Choose your mode of transport
Inspiration
Mass transportation operators have been struggling immensely due to necessary social distancing measures. Many airlines have been struggling to steer away from bankruptcy. In order to cope, some companies have chosen to increase their fares.
This could be minimized by optimizing social distancing in order to safely increase occupancy.
What it does
Uses a modified version of
Steffen’s method
for boarding airplanes
Takes into consideration keeping families together, boarding groups/priority and disabled passengers
Maintains physical distancing between passengers algorithmically
Staggered boarding/deplaning process for optimal efficiency as well as physical distancing
How we built it
Experimenting with different libraries
Choosing React.js and regretting it
Hard work
Coffee
No sleep
Challenges we ran into
Animating the boarding status.
Assigning coordinates to each seat
Developing the algorithm was harder than we thought
Accomplishments that we're proud of
The algorithm works
What we learned
The current airplane boarding time can be reduced by half!
What's next for BoardSafe
Optimize social distancing in other forms of mass transport
Add a face mask detector at the door
Generate QR codes for passengers to use as boarding pass
Built With
adobe-illustrator
animejs
python
react
Try it out
github.com | BoardSafe | Optimized social distancing for mass transport | ['Ebtesam Haque', 'Muntaser Syed'] | ['Third Overall'] | ['adobe-illustrator', 'animejs', 'python', 'react'] | 82 |
10,341 | https://devpost.com/software/hiv-drug-prediction-model | Logo
Inspiration
Our inspiration is our professor who described the current world scenario of HIV infections and the population diagnosed with AIDs. The constant aim of developing something for social good was a constant source of motivation.
What it does
Our project is an HIV regulator that can in fact detect the HIV drugs from their molecular structure. It performs feature extraction by constructing graph structure representing the molecules and calculating 1D 2D and 3D descriptors for the molecules.
How I built it
We have used special libraries like Pytorch, Tensorflow, Rdkit, Torch, etc to build the model using proper datasets. All references have been provided within the documentation.
Challenges I ran into
We faced various issues like which classification algorithm or which classifier to be used for the prediction and after cross-validating various classifiers, coming up with a particular one was difficult as there hasn't been much work upon this earlier.
Accomplishments that I'm proud of
We were finally proud to have achieved a promising accuracy and better F-scores. We were able to work out the way we wanted the data to be processed and augmented.
What I learned
We had a great time learning about the various molecules and their structure. How we implemented graph structures upon 3D molecules was really a great thing I learned.
What's next for HIV drug prediction model
We will make this better to look upon by using a notebook like Jupyter Notebook or Colabs to give a clean format of all the files implemented together and work upon improvising the algorithm with CNN classifier along with Class Activation Maps.
Built With
python-package-index
pytorch
rdkit
tensorflow
wbp-systems-torch
Try it out
github.com | HIV Regulator | Perform feature extraction by constructing graph structure representing the molecules and calculating 1D 2D and 3D descriptors for the molecules.Our aim is to develop a model to detect the HIV drugs. | ['Abhik Chakraborty'] | [] | ['python-package-index', 'pytorch', 'rdkit', 'tensorflow', 'wbp-systems-torch'] | 83 |
10,341 | https://devpost.com/software/pong-flappy-b53ud6 | This is a picture of Pong!
This is a picture of the Creators page which shows our names and bios!
This is a picture of Flappy!
Inspiration
We were very puzzled at what to create for this hackathon. So we decided to think of some problems that we have right now. We said at the same time that the quarantine had made us so "bored" that we were about to go insane. From there, we were thinking of ways to interest other people and how to captivate others. That's when we thought of Pong!+Flappy!
What it does
The website we created features two games plus a quick bio of us. Pong is one of the games featured on the website and it has many cool features. If you didn't know already, Pong is a table tennis sports game featuring simple two-dimensional graphics. However, we added cool extra features to the game. Pong's extra features: 1. There is the option to play music in the background while the user is playing and keep in mind, you can skip around the music track AND adjust the volume. 2. There is an option of enabling confetti which is an animation that plays across the whole screen when a user wins. That way, it makes the winner feel much happier and wants to play again to get the same satisfaction :) 3. If the game is too easy for some people, we added an extra "fast mode" so users get some challenge! In "fast mode", the ball is much faster but the speed that the user can move the block is still the same. 4. Thinking of games, I knew that Fortnite and all those first-person shooter games had the option to change keybinds (controls to move). So we thought, why not let the users have the option what buttons to press, to move the user block. At the bottom of the screen, lays the 4 different keybinds for Person 1 and Person 2 to change when they want their block to move up and down. 5. Another feature we added was a "reset keybinds" where if a user tries to set a keybind as "∆" and it was an accident, they can reset keybinds and see what the recommended keybinds are. 6. There is a "game objective" button because we wanted it so that users can play up to an objective and not play forever or else no one will be the "winner". (Also, the confetti play when someone hits the objective that the user chooses). Instead of giving options on what the objective is, we asked the user to put in an objective number whenever they click the button "game objective". If the user puts something else besides a number, it says invalid response. 7. Also, the button "reset game" resets the score, ball, and game objective. 8. We also wanted to add a pause/resume button to let the user have extra control when they are trying to change their keybinds, game objective, music, or any other setting. 9. We also added options of different objects that the user could use instead of the standard ball. If you didn't already know, Flappy Bird is a game where the objective is to make the bird go through pipes without touching them. The more pipes the user goes through, the higher the score. Flappy's extra features: 1. There is a normal and fast mode to challenge users and make the game more interesting. 2. We blocked users from cheating by flying really high by making the user die if they try and go super high. 3. We have a glow behind the game screen. 4. We also added audio which is adjustable just like Pong! 5. We have a cool face animation next to the title "Flappy Bird". 5. For any electronic device beside a computer, touching/tapping is how you move the bird but for keyboard, we made it so that any key that is pressed can make the bird move. 6. We added options for the user to pick instead of just having a bird.
How I built it
We used repl.it to build everything that you can see on the website.
Challenges I ran into
One challenge we had was making the UI. There are a lot of features and we didn't want to make everything super cluttered. At the same time, we had to make it so that the user has options and can adjust their game according to their liking.
Accomplishments that I'm proud of
Definitely the custom keybinds. It was pretty hard capturing keycodes and then updating the text to reflect the changes that were made. Also, creating two games in two days completely with the added features was pretty tough.
What I learned
We both got much closer to each other and now are very close friends. Also, we both learned that we can make simple games turn into much more fun and complex game. We learned how to host audio, not on repl.it, learned more about HTML5 canvas, and how to have the mindset of always being creative and adding new features to the game. Lastly, we learned that hackathons like Hack the Cloud are an amazing opportunity to bond and collaborate with people who have the same interests as you!
What's next for Pong!+Flappy!
Pong!:
If we had extra time, we would have created a solo mode where it would be the user vs a robot! Maybe even a multiplayer setting where you could play with people from all over the world! Also, the ability to drop and drag any music the user wants, and the ability to drop and drag whatever object they wanted instead of selecting a limited amount of options!
Flappy!:
If we had extra time, we would add coins between the green poles so whenever the bird goes through they collect coins and we could create a shop where there would be different options of skins that could be bought by coins! Also, just like Pong, the ability to drop and drag any music the user wants and the ability to drop and drag whatever object they wanted instead of selecting a limited amount of options! Maybe even.... having multiple people playing with you?
Built With
css
html
html5
javascript
Try it out
pong.jasonantwiappah.repl.co | Pong!+Flappy! | Two web games completely made from scratch with an extra added twists of our own! We hope you enjoy! | ['Jason Antwi-Appah', 'Winston Iskandar'] | [] | ['css', 'html', 'html5', 'javascript'] | 84 |
10,341 | https://devpost.com/software/heart-o-k | probability of heart disease in the individual.
patient entering the information to check for heart disease.
Information of the patient that is being entered.
When recommending medicines, the view will be something of this kind.
login page
sign up page
home page from where the patient can jump directly to report/check/logout.
What it does My project provides a simple ui where you can check for probability of heart disease and get recommendations for medicines and drugs correspondingly.
How I built it
I built a simple prediction model using best out ml algorithms available like glm, gbm,svr, etc. After that I prepared my own data of medicines by scraping data from medlife, etc and give recommendations using collaborative filtering.
Challenges I ran into
I face difficulty while building medicines data set. Also, results were not that accurate in the past, so i had to work a lot.
Accomplishments that I'm proud of
The website that i designed provides a very simple ui that anyone is able to operate. Results are promising.
What's next for HEART-O-K
I would like to extend this project for another diseases like thyroid, etc.
Built With
css
google-web-speech-api
html
javascript
parse
r
rshiny
server | HEART-O-K | Predicting heart disease in an individual and getting recommendations for medications and drugs. | ['Deepshi Sharma'] | [] | ['css', 'google-web-speech-api', 'html', 'javascript', 'parse', 'r', 'rshiny', 'server'] | 85 |
10,341 | 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'] | 86 |
10,341 | https://devpost.com/software/ai-voice-assistant | Inspiration
The inspiration was always to learn new technology.
What it does
It is a voice assistant powered by wit.ai. The users can use a voice interface to ask the assistant very basic things like time and date to information about anything, play songs, personalized jokes, browser automation, COVID related data etc
How I built it
The main languages I used was javaScript and python. The UI was done in electron js and the backend with wit.ai integration was done with python3. I used a library called Eel to connect my python code to js .
Challenges I ran into
The challenges I ran into was lack of time, so I could not add all the features that Il wished to include.
Accomplishments that I'm proud of
In spite of the lack of time and resources, I managed to complete the project
What I learned
I got to learn wit.ai a very powerful tool for NLP related projects.
What's next for AI-Voice assistant
The next features that I like to include are complete home automation using my assistant
Built With
eel
electron
javascript
python
wit.ai
Try it out
github.com | AI-Voice assistant | This is a personal voice assistant built with Wit.ai platform with a voice interface. The users can ask, information about anything, to play songs, to send an email, computer hardware status etc. | ['Abhinav Tharamel Baiju'] | [] | ['eel', 'electron', 'javascript', 'python', 'wit.ai'] | 87 |
10,341 | https://devpost.com/software/wecare-5l9dgi | Home Screen of app, which allows you to report your symptoms, check the status of your circle, and get daily personalized tips.
Map Screen of app, which allows you to see hotspots around you and your Care Circle.
Care Circle screen of app, which allows you to health conditions of your loved ones.
Web interface, which can be used to update the symptoms. It is synced with the app.
New logo.
Update with a key.
Hotspots for countries.
Options from the start.
Questions about your health.
Hot spots.
App design
As the outbreak of COVID-19 continues to spread throughout the entire world, more stringent containment measures from social distancing to city closure are being put into place, greatly stressing people we care about. To address the outbreak, there have been many ad hoc solutions for symptom tracking (e.g.,
UK app
), contact tracing (e.g.,
PPEP-PT
), and environmental risk dashboards (
covidmap
). However, these fragmented solutions may lead to false risk communication to citizens, while violating the privacy, adding extra layers of pressure to authorities and public health, and are not effective to follow the conditions of our cared ones. Unless being mandatory, we did not observe the large-scale adoption of these technologies by the crowd. Until now, there is no privacy-preserving platform in the world to 1) let us follow the health conditions of our cared ones, 2) use a statistically rigorous live hotspots mapping to visualize current potential risks around localities based on available and important factors (environment, contacts, and symptoms) so the community can stay safer while resuming their normal life, and 3) collect accurate information for policymakers to better plan their limited resources.
Such a unified solution would help many families who are not able to see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. These urgent needs would remain for many months given that the quarantine conditions may be in place for the upcoming months, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and COVID-19 potential reappearance next year at a smaller scale (like seasonal flu). There is still uncertain information about immunity after being infected and recovered from COVID-19. Therefore, it is of paramount importance to address them using an easy-to-use and privacy-preserving solution that helps individuals, governments, and public health authorities.
WeCare Solution
WeCare is a cross-platform app that enables you to track the health status of your loved ones. Individuals can add their family members and friends to a Care Circle and track their health status and get personalized daily updates on best prevention practices. In particular, individuals can opt-in to fill a simple questionnaire, supervised by our epidemiologist team member, about their symptoms, comorbidities, and demographic information. The app then tracks their location and informs them of potential hotspots for them and for vulnerable populations over a live map, built using opt-in reports of individuals. Moreover, symptoms of individuals will be tracked frequently to enable sending a notification to the Care Circle and health authorities once the conditions get more severe. We have also designed a citizen point, where individuals get badges based on their contributions to solving pandemic by daily checkup, staying healthy, avoiding highly risky zones, protecting vulnerable groups, and sharing their anonymous data.
WeCare includes a contact tracing module that follows the guidelines of Decentralized Pan-European Privacy-Preserving Proximity Tracing
(PEPP-PT)
. It is an international collaboration of top European universities and research institutes to ensure the safety and privacy of individuals.
What we have done during the weekend
Have been in contact with other channels in Brazil and Chile.
We have updated the pitch (extended), app-design and backend connection of the app this week. New contacts with Chile and Singapore. We have also made some translation work with the app. Shared more on social media about the project and also connected to more people on slack and LinkedIn. We have also modified the concept of Care Circle and how to add/remove individuals. Now, the app is very easy-to-use with minimal input (less than a minute per day) from the user. We are proud of the achievements of our team, given the very limited time and all the challenges.
Challenges we ran into
The Hackathon brought together plenty of people of different expertise and skills. There were challenges that we faced that were very unique, as we faced a variety of communication platforms on top of open-source development tools.
Online Slack workspaces and Zoom meetings and webinars presented challenges in forms of inactive team members, cross-communications, and information bombardment in several separate threads and channels in Slack and online meetings of strangers that are coordinated across different time zones. In developing the website and app for user input data, our next challenge was in preserving the privacy of user information.
In the development of a live hotspot map, our biggest challenge here was to ensure we do not misrepresent risk and prediction into our live mapping models.
Also for the testing of the iOS version, we ran to the new restriction of App Store for COVID-related apps, which should be backed up by some health authorities or governmental entities.
The solution’s impact on the crisis
We believe that WeCare would help many families who can see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. The ability to check up on their Care Circle and the hotspots around them substantially reduces the stress level and enables a much more effective and safer re-opening of the communities. Also, individuals can have a better understanding of the COVID-19 situation in their local neighbourhood, which is of paramount importance but not available today.
The live hotspot map enables many people of at-risk groups to have their daily walk and exercise, which are essential to improve their immunity system, yet sadly almost impossible today in many countries.
The concept of Care Circle motivates many people to invite a few others to monitor their symptoms on a daily basis (incentivized also through badges and notifications) and take more effective prevention practices.
Thereby, WeCare enables everyone to make important contributions toward addressing the crisis.
Moreover, data sharing would enable a better visual mapping model for public assessment, but also better data collection for the public health authorities and policymakers to make more informed decisions.
The necessities to continue the project
We plan to continue the project and fully develop the app. However, to realize the vision of WeCare we need the followings:
Public support: a partnership with authorities and potentially being a part of government services to be able to deploy it on AppStore. It also makes WeCare more legitimate. This would increase the level of reporting and therefore having a better overview and control of the crisis.
Social acceptance: though being confirmed using a small customer survey, we need more people to use the WeCare app and share their data, to build a better live risk map. We would also appreciate more fine-grained data from the health authorities, including the number of infected cases in small city zones and municipalities.
Resources: So far, we are voluntarily (and happily) paying for the costs of the servers. Given that all the services of the app and website would be free, we may need some support to run the services in the long-run.
The value of your solution(s) after the crisis
The quarantine conditions and strict isolation policies may still be in place for upcoming months and year, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and possible COVID-19 reappearance next year at a smaller scale (like seasonal flu).
Therefore, we believe that WeCare is a sustainable solution and remains very valuable after the current COVID-19 crisis.
The URL to the prototype
We believe in open science and open-source developments. You can find all the codes and documentation (so far) at our
Website
.
Github repo
.
Pitch:
https://youtu.be/7fMrVqxoPKY
Pitch extended version:
https://youtu.be/Vo0gs3WlptU
Other channels.
https://www.facebook.com/wecareteamsweden
https://www.instagram.com/wecare_team
https://www.linkedin.com/company/42699280
https://youtu.be/_4wAGCkwInw
(new app demo 2020-05)
Interview:
https://www.ingenjoren.se/2020/04/29/de-jobbar-pa-fritiden-med-en-svensk-smittspridnings-app
Built With
node.js
python
react
vue.js
Try it out
www.covidmap.se
github.com | WeCare | WeCare is a privacy-preserving app & page that keeps you & your family safer. You can track the health status of your cared ones & use a live hotspot map to start your normal life while staying safer. | ['Alex Zinenko', 'Sina Molavipour', 'Ania Johansson', 'Hossein S. Ghadikolaei', 'Christian M', 'Seunghoon HAN', 'Tomasz Przybyłek', 'Mohamed Hany', 'Alireza Mehrsina'] | ['1st Place Overall Winners', '2nd Place'] | ['node.js', 'python', 'react', 'vue.js'] | 88 |
10,341 | https://devpost.com/software/funnybunny-e7u98y | FunnyBunny
Funny
Wise
Inspiration
We wanted to see if we could implement and create a bot that was actually funny and make the user laugh! Plus, with the pandemic, we wanted to create a unique way for people to disconnect and relax and smile without needing to leave the house.
What it does
We present you with a funny chatbot who has been trained on speech from the fan favorites of television: The Office, Gordon Ramsay, and Friends. Yes, the bot can definitely tell you a joke, but just like all the true comics, its humor flows out effortlessly during a conversation. And don’t forget to ask about the weather! Don’t say I didn’t tell you it’s funny AND helpful!
Personality: funny with a side of sass
Hobbies: keeping you company and helping you out
Cute
A fun conversation with FunnyBunny
How we built it
We used:
Gordon Ramsay
Chandler Bing
The Office cast
Chuck Norris
Dad jokes
React Native
DialogFlow
Amazon Alexa
Google Cloud
Adobe Illustrator
SpaCy for POS tagging and linking, word association and NLTK for sentiment.
To determine conversation flow, we utilized Google Cloud’s DialogFlow and designed a conversation flow, creating custom intents and entities. With each user input, the app pings the DialogFlow API to get the correct response. Additionally, we created an Amazon Alexa skill that has the same functionalities as our app, so the user can have the same great experience using Amazon Alexa.
The backend was deployed on Google cloud platform as serverless cloud functions. These functions had a python 3.7 runtime with 128 MB ram. The segregated nature of the endpoints meant that some user config data was stored in a mongodb instance which was looked up upon invocation.
Challenges we ran into
Initially, we created the Alexa skill and saw that Google offered an easy import tool which sounds too good to be true, and it was - that tool no longer works. So, we spent a lot of time reading and understanding many of the Google Cloud Products in order to successfully manually transfer the dialog model. Interestingly enough, you can code in python for AWS Lambda but not for Google’s Cloud Functions, so we needed to find a workaround for the lack of Python compatibility of Google Cloud Functions.
Accomplishments that we're proud of
We're really proud that our product is actually working! Jokes aside, we learned about integrating different parts together from the application to the cloud and the NLP engine.
What we learned
We learnt how to use stuff that makes it work.FunnyBunny has a good sense of humor!
What's next for FunnyBunny
We wanna move it move it
Built With
react-native
Try it out
github.com | FunnyBunny | Bunny with a sense of humor! | ['Ebtesam Haque', 'Muntaser Syed', 'Sarah Zhou'] | [] | ['react-native'] | 89 |
10,341 | https://devpost.com/software/remote-elderly-home-care-via-privacy-preserving-surveillance-9mrdgx | Privacy preserving person face detection at home
Plug and Play AI device discovery
Home Page
Person detection indoors
Person detection outdoors
Inspiration
COVID19 isolated at home many of us, including our elderly parents and grandparents. Not being able to check on them regularly elevates the risks that they are exposed to such as falls, gas leaks, flooding, fire and others.
What it does
Ambianic.ai is an end-to-end Open Source Ambient Intelligence project that removes the stigma associated with surveillance systems by implementing privacy preserving algorithms in three critical layers:
Peer-to-Peer Remote access
Local device AI inference and training
Local data storage
Ambianic.ai observes a target environment and alerts users for events of interest. Data us only available to homeowners and their family. User data is never sent to any third party cloud servers.
Here is a blog post that goes into the reasons why we started this project:
https://blog.ambianic.ai/2020/02/05/pnp.html
And here is a technical deep dive article published in WebRTCHacks. It clarifies that it is absolutely possible to build a privacy preserving surveillance system, despite popular cloud vendors making us believe that all user data belongs safely on their cloud servers:
https://webrtchacks.com/private-home-surveillance-with-the-webrtc-datachannel/
How we built it
Ambianic.ai has 3 main components:
Ambianic.ai Edge: a Python application designed to run on an IoT Edge device such as a Raspberry Pi or a NUC. It attaches to video cameras and other sensors to gather input. It then runs inference pipelines using AI models that detect events of interest such as objects, people and other triggers.
Ambianic.ai UI: A Progressive Web App written in Javascript using Vue.js and other front end frameworks to deliver an intuitive timeline of events to the end user.
Ambianic.ai PnP: A plug-and-play framework that allows Ambianic UI and Ambianic Edge to discover each other seamlessly and communicate over secure peer-to-peer protocol using WebRTC APIs.
Challenges we ran into
Challenges include selecting high performance, high accuracy and low latency AI models to detect events of interest on resource constraint edge devices.
Another challenge is taking into account user local data to fine tune AI models. Pre-trained models can perform reasonably well, but they can be improved with privacy preserving federated learning on unique new local data.
Accomplishments that we're proud of
Ambianic.ai has been in public Beta for several weeks helping a number of users in their daily lives. Some users report success in keeping an eye on their elderly family members:
https://twitter.com/mchapman671/status/1230931722650423299
What we learned
Although the project sets ambitious goals, there seem to be sufficient enabling Open Source frameworks and community momentum to drive the ongoing success.
What's next for Remote Elderly Home Care via Privacy Preserving Surveillance
We need to work on these major areas:
Recruit volunteers in the home care community to test the system and provide feedback
Select more models to address open use cases such as fall detection, gas leaks and others
Work on implementing Federated Learning infrastructure to fine tune initial pre-trained models.
Built With
javascript
pwa
python
raspberry-pi
tensorflow
webrtc
Try it out
docs.ambianic.ai | Remote Elderly Home Care via Privacy Preserving Surveillance | COVID19 isolated at home many of us, including our elderly family members. Left unattended they are prone to risks such as falls, gas leaks, flooding, fire and others. | ['Björn Kristensson Alfsson', 'Yana Vasileva', 'Ivelin Ivanov'] | ['Best EUvsVirus Continuation', 'Best Home Care Project', 'Best Platform'] | ['javascript', 'pwa', 'python', 'raspberry-pi', 'tensorflow', 'webrtc'] | 90 |
10,345 | https://devpost.com/software/vid-ai | Inspiration
Video Content consumption is growing on mobile and advertisers are spending huge dollar on video advertising. 50% of these videos are consumed on mobile. Focus on short format video has also increased as the average human span attention is less than 8 sec. Also there is in an interesting insight about video consumption, 98% of time Phones are used in portrait mode while consuming videos. Our video content cloud SDK gives access to Short format vertical and horizontal videos.Our Android native video player embedded in SDK supports VAST 4.0, VAST 3.0 and VAST 2.0 Inline Linear Ads.
Get Started
Integrating the VID.AI Video Ads SDK into an app is the first step toward displaying ads and earning revenue. Once that's done, you can choose an ad format (such as Video in feed or Interstisial video) and get a detailed set of steps for implementing it.
Requirements
Use Android Studio 2.0 or higher
Target Android API level 16 or higher
Built With
java
maven
Try it out
rep.tyroo.com | VID.AI | A cloud based payments and video service integration app with AI | ['Rahul Singhal'] | ['First Prize'] | ['java', 'maven'] | 0 |
10,345 | https://devpost.com/software/redcusx-dronu0 | Inspiration
My inspiration is my parents and that section of society who want to enjoy the benefits of fast and rising technology. Our current project resolves few problems that commonly people face, namely- building websites from handmade drawing, job dashboards, issues faced by the blind and deaf customers, offline object detections and transactions [offline e-shopping] and providing traffic management solutions. Today we have products that allow faster deployment, scalability, and security. Our main aim was to bridge the gap between fast technology and common people. I saw my friends say if I could an application to serve the society. I saw my mom saying "I wish I could shop even when offline". Nearly millions of dreams remain uncherished. This has motivated me to build this application and convert the so-called "If" to "yes we can". Nothing is impossible in today's world using tech stacks like Kubernetes, Openshift, Fuse projects which are so easy to use. My inspiration is Red Hat and their community of developers who build such amazing products and in fact, Red Hat studio code was my dream project a year back.
What it does
Our product is based on customer requirements. As per their requirements, we provide services like just draw and get the code, maintain job details and application to design the house, Voice services, and services for physically handicapped.
What's next for Redcusx
We have a lot to work upon RedcusX. We need to add many such small but interesting free services. Our project upon automation of website building we need to implement Tensorflow.js so that we can develop code based upon real-time object detection. We are still working on our product Trafene. We are thinking to convert CusX into a platform for developers to submit their work on applications and they will be paid for that. For any innovative idea by any common person upon making a better customer experience, they will be paid and developers may work upon such ideas to build creative products. This will be a continuous process of creating a new world where people love to work without any hassle.
Built With
ar
google-web-speech-api
java
mavenlink
python
restful-web-services-bible | Redcusx | A new platform to improve upon the customer experience | ['Abhik Chakraborty'] | ['Second Prize'] | ['ar', 'google-web-speech-api', 'java', 'mavenlink', 'python', 'restful-web-services-bible'] | 1 |
10,345 | https://devpost.com/software/bestcloud-find-best-cloud-services | Inspiration
People face a lot of confusion choosing the best cloud provider when it comes to select anyone of it at a cheaper cost keeping in mind all the parameters that are required. Due to this reason, I have created this Cloud Recommender which will display you the affordable one only.
What it does
It finds the best cloud service with respect to various parameters. ☁
Parameters
Name
Description
Storage Amount
Number of Gigabytes
Data Transfer Out
Number of data transferred out to the region
Read Requests
Number of GET Requests
Write Requests
Number of POST Requests
Region Name
Location of the data center
Temperature
Frequency of accessing the data
How I built it
Technology Stack
Bootstrap5 🎨
CostStorage's API
Demo
Social Media
Follow me on
Twitter
✔
Built With
bootstrap
cloudstorage-api
html
javascript
Try it out
bestcloud.surge.sh
github.com | BestCloud - Find best cloud services | Find the best cloud service with respect to various parameters | ['Sumit Banik'] | [] | ['bootstrap', 'cloudstorage-api', 'html', 'javascript'] | 2 |
10,345 | https://devpost.com/software/easy-tables | The application
Inspiration
I often use dynamodb tables for my applications, however the editor in AWS looks old-fashioned and is hard to use. So, I decided to make a way to collaborate on and edit DynamoDB tables with simplicity!
What it does
After you create a dynamodb table, simply specify to api that connects to the dynamodb table and the columns you want to use in the code (specifics are on github). Then, you and others can collaborate on, edit, create, delete, and find items on the dynamodb table easily.
To delete or edit an item, click the item in the table
To create an item, click create at the top
To find an item, specify the a key of the item and the first few letters of the value and only those items would be displayed in the table
Any edits you or another person makes can be found when you reload the page
How I built it
The front end is built with react and redux, and I used create-react-app to do so. AWS API gateway is used to connect with the backend, which uses DynamoDB, Lambda, and S3. That was built with serverless. Since the application is serverless, it is very reliable, fast, and easy to package, so collaboration would be easy.
Challenges I ran into
Getting the values from the dynamodb table and iterating over them to display them in a table was difficult and took some time.
Accomplishments that I'm proud of
I used API Gateway to connect front end and back end to make a serverless project!
What I learned
I learned how to modify dynamodb tables using code
What's next for Easy Tables
I plan to add more functionality like cognito and imago hosting, so that my project will be used by others and possibly companies.
Built With
apigateway
dynamodb
lambda
node.js
react
redux
s3
serverless
Try it out
github.com | Simple Tables | A simple way to edit, interact with, and collaborate on DynamoDB tables. | ['ram potham'] | [] | ['apigateway', 'dynamodb', 'lambda', 'node.js', 'react', 'redux', 's3', 'serverless'] | 3 |
10,345 | https://devpost.com/software/voyageur-q04b1h | Inspiration
We had won the grand prize at an APAC-level hackathon and he got a chance to go to a startup conference in Barcelona this summer. But due to the pandemic, it was canceled. Now, Bhavya is not sure if he’ll go even if the conference is next year. We realized this would be the case for many travelers, both leisure and business. One of the major problems would be making travelers gain the confidence to travel again.
We decided to do something to encourage people to travel, by assuring them of safety.
Our solution solves these problems:-
Hygiene & Health
Hack the very definition of travel in ways that address the health concerns long after the COVID-19 slowdown has passed. These inventions must demonstrate how the well-being of travelers and businesses is preserved or improved during travel rather than put at risk.
Sustainability & Relief
With pre-pandemic travel practices as your starting point, and new business models and social/environmental impacts as your guide, invent new responsible, socially impactful products and services that drive exceptional travel experiences and economic growth. Also, with public health and employment concerns at the forefront now, demonstrate how your invention measurably enhances economic conditions in regional and local destinations around the world.
What it does
We have created software services for hotels, airports, parks, restaurants, museums, theatres, and other enclosed private tourist spots. Our system will automatically detect whether people are following social distancing and whether they are wearing masks or not, from CCTV footage. The owners of the place will be alerted if someone is not following the rules.
These places can advertise that they’re using an automated system to ensure safety, and this will attract more tourists.
The other facet of our solution is an Android app for travelers/tourists. Users can pick a destination and a date of interest. We will show them the updates of that area, and give the estimated number of cases. This estimation is based on a predictive ML model.
This will help users make an informed decision and they can postpone their trip well in advance, without losing out money on cancellation charges. This will also help air travel companies and hotels, who have to bear losses if a person cancels their stay.
How we built it
We have taken a sample recording of the CCTV camera footage. An image processing model detects and classifies various bounding boxes based on the distance between people in the video. Also, we have the Mask detection algorithm which was built using CNN and it checks whether people are wearing a mask or not and creates a bounding box around the face. So the viewer knows the number of people violating the norms.
These models were built in Python.
The website for private owners (of the hotel, market, tourist spot) was built using React, Firebase, and Node. The mobile app for users (tourists) was built using the Android Studio and Firebase.
Challenges we ran into
One challenge was Data privacy. For that, we will ensure that the output of our machine learning model that will run on the CCTV frames will only number: that is the number of the red bounding boxes and the number of the green bounding boxes. This will be stored and updated on the cloud database dynamically. These stats will be made available to the websites of the private tourist places. From this, the private tourist authorities will get an idea about the number of people maintaining and following the social distancing norms.
Accomplishments that we're proud of
We are proud of the fact that our project will help many travelers, both leisure and business in the aftermath of this pandemic. We will be providing one of the major strengths to travelers that is gaining confidence to travel again. We are really happy to be part of the change that will boost & encourage people to travel safely.
Technology Used
We have used Machine learning to detect if people are following COVID19 norms- social distancing and wearing masks. We have used the YOLO model to detect people. Once that task is achieved we have calculated the euclidean distance between the bounding boxes(output of the ML model). We check if the distance has been above a threshold that we have defined. If so, we attribute such a group of people with a red bounding box. For mask detection, we have made a custom CNN model wherein we have annotated the mask image and trained the convolutional neural network for the mask image. The model detects the presence of masks in the frame and draws a bounding box around it.
For COVID19 trend prediction, we have used data of a place named Mumbai in India. We have used Recurrent neural networks(RNN) for such prediction because of the fact it can remember past trends and predict future trends on the basis of past knowledge.
For the website, React, Node, and Firebase were used. For mobile apps, Android Studio, Google SDK, Covid19 API, and Firebase were used.
What's next for Voyageur
The next plan would be to host our entire application on the cloud. The ML models and the backend will be deployed on the cloud. In phase 1, we would like to try out this solution locally. We will tie-up with local hotel chains and tourist spots in Mumbai and devise a basic billing plan to start earning revenue. We will also release our app for tourists on the play store. After these iterations and learning from the results, we would like to partner with more places and or a company like Trivago which can in turn sell these services to its partners.
Built With
android-studio
machine-learning
Try it out
github.com | Voyageur | Make people confident to travel again | ['Vedant Kumar'] | [] | ['android-studio', 'machine-learning'] | 4 |
10,345 | https://devpost.com/software/pandoconnect | PandoConnect
A platform created to share the experience of those Covid19 survivors. In such a time when we browse about this virus and only get to see how it is affecting us badly every day, this platform will help to boost up the mental strength of people all over the globe. Over here anyone who is potentially a Covid19 patient or has recovered from it can help people get aware of the virus by sharing their experience and positive thoughts. People who might not be a patient but are someway connected to them can also post over here, this will help people remain connected to each other globally. If you are neither a patient nor a survivor nor even a close acquaintance to them, don't worry you can also come here and view these blogs. These blogs can any day spread positivity that we can share in these times of crisis.
When all we have right now is search and get distressed about the situation around us, this platform will help you fight back by seeing how people have globally fought back this invisible enemy. This platform which is meant for connecting and sharing the experience of Covid19 patients can give you hints about how you can stay safe and sound during this difficult time. It will help you remain cautious about the surroundings and take proper measures to combat this virus.
A Sentiment Score will be given to every post using the Real-time Machine Learning Model which will help the Reader of the blogs to see which story got which emotions and how much.
Demo
Click here for demo
or you can also check the links given below
Inspiration
The world is now unanimously fighting an invisible enemy, an enemy that cannot be overpowered with any weapon but by collectively staying away from each other. As of today, the number of active cases globally stands somewhere near 3.5 million and if we consider an average of 2 family members for each active patient then the total is about 10 million. These are the minimum count of people who is going through mental stress right now.
Features
• Sentiment Analysis.
• Capabilities to Connect users all over the globe for one cause that is fighting COVID 19.
• Capabilities to Sharing motivating stories.
• Built with Ionic and ReactJs.
• Deployed in Firebase.
• Database Firestore by Google Cloud Platform and it is realtime.
• Google Cloud Storage for Image Upload
• Responsive Design
• Progressive Web Application
• Hybrid Application
How I built it
It is built using Ionic & ReactJs. Firebase with Google Cloud is used for Database, Cloud Storage, and Deployment.
Challenges I ran into
I faced a few challenges in making the upload image functionality in the blog submit as this was my first time with GCP.
Accomplishments that I'm proud of
I have completed most of the application in 2 weeks.
What I learned
This is the First time I have used Ionic. So, It was a great learning experience.
What's next for PandoConnect
• Adding Sentiment Analysis using Machine Learning Models to give a score to blogs.
• Login with Email and Password apart from Google login.
• Enhancement of User Interactiaction.
• Mobile application as it is built on a hybrid framework. ie. Ionic.
• Reaching out to more Survivors to share their stories.
Built With
css
firebase
html
ionic
javascript
react
typescript
Try it out
github.com
pandoconnect-c9991.web.app | PandoConnect | This platform is created to share the experience of Covid 19 survivors. This platform will help to boost up the mental strength of people all over the globe. | ['Sourav Dey'] | ['The Wolfram Award'] | ['css', 'firebase', 'html', 'ionic', 'javascript', 'react', 'typescript'] | 5 |
10,345 | https://devpost.com/software/smartbusiness-vctwua | Inspiration
Cloud is IasS ( Done ) , PaaS ( Not adequate extensions ) , SaaS ( Limitation of APIs and closed for purpose )
How about evolution of PaaS by "Plugins". Plug-In Architecture can be of the following types.
e.g (1) ELK based Logging Plugin
(2) JIRA based PMO Plugin
(3) Prometheus based Monitoring Plugin etc.
Cloud Native -CNFC has so many software. Each could be plugin to start with Kubernetes Operator and make it Kubernetes-Native ( Cloud-Native ) and since it is plugin it wouldn't be bulky and light-weight. Cloud-Operators can sell Plugins in Marketplace.
But wait there is KubeCtl Plugin. Also there is "krew"... So what's new.
Coming back to "Cattles vs Pets" story. Application Platform is still.... how do we change that. We now have kubernetes of kubernetes but do we have Kubectl of Kubectl :) Let me make it simple.
Application Platform is heterogeneous. How do we solve it by Computer science first principle --> Everything is solvable by indirection - Configurator of Configurator....
Let me talk VR Plugin.
Theme is Cloud VR/AR and DevOps. Let us put our thoughts for this usecase.
(*) Mobile ( Client ) request Cloud Platform for VR App. [ May be playstore to search and request ]
(*) Cloud Platform give ability for device authenticated to be "Worker Nodes". Devices like Mobile can be authenticated from telco etc for authenticity. Worker nodes to cloud platform should be dynamically added and removed. Kubectl commands ensures client worker node is utilised only for Client VR image.
(*) Cloud Platform registers the client device as "worker node" and adds to the cluster. Master nodes downloads the VR-Client Image with respective kubectl-commands to client. Fetching of VR-Image from Registry is dynamism we are looking forward to... e.g. Mobile has asked XYZ VR game ; we need to search and send the right Client image from registry. Things what happened from API to GraphQL which is super charged API should happen. e.g Give me VR game which is like XYZ and runs based on my device. Platform based on personalisation rule and device characteristics sends to the client right image with kubectl commands to register.
(*) Mobile has Sandbox to run Kubectl commands from server. [ Remember Java Sandbox ]. Bad Server security challenge taken care of.
(*) Mobile is now dynamic worker node. It is all one nice happy cluster.
(*) Mobile VR Client in Sandbox called for server VR image and VR experience is great.
(*) VR is over. Client request to de-register itself.
(*) Platform depending whether it is paid or free ; bills appropriately to Mobile bill.
SideNote : We can have Linkedin of VR/DevOps guys alone - Call it "DO_Link" . ( Invitation based registration ) . Recommendation based on the help provided on "StackOverflow" of the portal. Peer Recognition , Cloud/DevOps talks, Pull Requests etc making it a vibrant community.
What it does
It is Collaborative platform for Kubernetes based Cloud where plugins are installed and hence custom Platform can be made. It is Platform-making-Platform. Work-Done ( Volunteer and Paid ) and Recommendation is on Block chain.
How we built it
Operator which assembles Kubernetes Operators.
Challenges we ran into
Accomplishments that we're proud of
Idea.. and Hope "Platform can be assembled"
What we learned
Think BIG
What's next for SmartBusiness
Implement :) We already have Garderner by SAP ( Kubernetes of Kubernetes)
Built With
node.js
react
solidity | SmartBusiness | K888 | ['deepak khandelwal', 'Chandresh Turakhia', 'Jagadish K', 'Vasanth Reddy'] | [] | ['node.js', 'react', 'solidity'] | 6 |
10,345 | https://devpost.com/software/mood-match | Logo
Sample conversation
Inspiration
Many times, it is very difficult to pick a song that is perfect for your current mood. Especially during such an unprecedented time in our world, it is hard for people to understand how they feel, let alone understand how to feel better. A plethora of research studies have proven that music is truly one of the best ways to brighten someone’s day and MoodMatch aims at doing just that. This issue of not being able to understand one’s true emotions and grasp what is needed to acquire a more positive mindset inspired me to create MoodMatch.
What it does
MoodMatch is a Facebook Messenger ChatBot that recommends songs based on a user’s current mood. MoodMatch understands the user’s current emotions by asking several personalized questions and using novel sentimental analysis algorithms to deliver several songs that will cheer up the mood of the user.
How I built it
Before this project, I was very new to the ideas of creating a project. This project introduced me to the end-to-end programming pipeline. I started by first mapping out what I had to do:
Obtain a list of songs, artists, and lyrics of the songs
Perform sentimental analysis on the songs to understand what kinds of feelings are exhibited by the song
Create a messenger bot
Program the messenger bot to ask the user questions
Process the results (sentimental analysis on the chosen choices)
Recommend songs with similar sentiment levels or perhaps higher sentiment levels to cheer one up
I followed this process thoroughly and used the Microsoft Azure Cognitive Science API to perform sentimental analysis. I also used various APIs including Spotify, Genius Lyrics, and various others.
Originally, I had meant for MoodMatch to pop up a Messenger Webview and encourage users to fill out a form that would then allow for the processing of data, however, Facebook’s innovative Quick Replies module on Messenger allowed me to make MoodMatch more interactive and personalized for users.
Furthermore, all of the data regarding songs and the various components associated with it are stored using AWS S3, making this application a perfect model of cloud-based computing. Through this project and several past instances, I understood the growing power of cloud-based applications in our world and how leveraging the cloud through applications such as AWS and Azure will undoubtedly ameliorate your app.
Challenges I ran into
As I was very new to the end-to-end programming process, I ran into many challenges including not being able to understand what was wrong. My first challenge in this journey of completing MoodMatch was deploying my messenger bot on a Heroku server. Many times, I received an Error 400 or Error 500 stating that the /GET request cannot be found. However, once I got over this hump by fixing a few lines in my code, I was faced with several other tough mountains:
Obtaining results from the HTML form and using ExpressJS to deliver POST requests
Returning a list of songs and executing my algorithm on an ASYNC function
Transitioning from a bland messenger webview to more interactive Quick Replies
I often asked friends or even posted on StackOverflow to get some of my questions answered and get over these challenges. This project truly wouldn’t have been possible without others who helped me get over these challenges.
Accomplishments that I'm proud of
Creating a bot was not something I could've imagined me doing a few months ago, but now I have fully learned one example of the end-to-end programming pipeline. Getting over the aforementioned challenges and not giving up throughout the process has not only given me more technical knowledge, but it has impacted me mentally as I am more confident in my coding ability after this project.
What I learned
I fully learned the end to end programming pipeline of sorts. In particular, I learned the ins and outs of the various APIs I worked with and understanding how to deploy/manage server-based applications like a messenger chatbot.
What's next for MoodMatch
A lot is in store for MoodMatch, ranging from automating the song updates as well as adding more factors that may influence someone's choice of song. I plan on having an autorefresh of sorts for the list of songs already scraped off the web right now so that users will continuously get different songs. Perhaps even employing an account scenario in which users are never recommended the same song on multiple occasions is also one thing I plan to work on. Lastly, a lot of factors go into one’s feelings and current emotions, which definitely cannot be grasped by the current 2 questions asked my MoodMatch. I plan on adding more of these questions and even an open-ended question of sorts, in which users can type in their response, and emotional analysis will be performed on their inputs. In fact, a few of these are already in the works so be on the lookout for upcoming updates ;)
Built With
billboard
facebook
genius
html
javascript
node.js
python
spotify
Try it out
www.messenger.com | MoodMatch | Ever feel down, but don't know how to cheer up? Ever partying, trying to have fun but not knowing what song to play? Fear no more, MoodMatch is here, giving you the right song at the right time. | ['Viren Khandal'] | ['Track Winner: Entertainment and Silly'] | ['billboard', 'facebook', 'genius', 'html', 'javascript', 'node.js', 'python', 'spotify'] | 7 |
10,345 | https://devpost.com/software/find-a-peaceful-protest-fi9ka2 | Inspiration
When I watched the news, I noticed how many protests around the world support different communities and movements. However, I also noticed many protests had violence, which often was not related to the movement itself. Violence is a reason many people who want to support their movement don’t attend these protests. For this hackathon, I decided to build something to help people connect and find peaceful protests.
What it does
Find a Peaceful Protest is an interactive map with user-generated content. It allows users to add new protests and find existing ones. It also has a review system where users can add their own account of the protest and images of the protest.
To reduce the amount of fake protests and reviews, Find A Peaceful Protest has a smart system where it calculates your reliability. The more reliable you are, the greater the impact is of your new protest or review.
Additionally, a color-coded map navigation system makes it easy to see which protests are right for you. Markers on the map are color-coded according to how peaceful the protest is rated, and the opacity of markers are set according to how reliable it is.
How I built it
For the map, I used Leaflet.js for the user interface, OpenStreetMap for the map content, and ESRI for geocoding and reverse geocoding. For the backend, I used Firebase Realtime Database to store data and Firebase Storage for image storage. For the general structure of the website, I used HTML/CSS and JavaScript, as well as W3.CSS. I used Firebase Hosting to host my site.
Challenges I ran into
I was not familiar with the Leaflet.js library when starting the project, so it took some time to understand and learn it. Additionally, I had some problems with getting an image URL from Firebase Storage, but eventually figured it out after reading the documentation.
Accomplishments that I'm proud of
I am proud of figuring out how to implement the Leaflet.js map without prior experience in using the library.
What I learned
I learned a lot about Leaflet.js, as well as Geocoding and accessing geolocation in the browser.
What's next for Find A Peaceful Protest
I plan to implement an account system for Find A Peaceful Protest to further increase reliability of data and repeated reviews from the same person.
Built With
esri
firebase
html5
leaflet.js
openstreetmap
Try it out
github.com
find-a-peaceful-protest.web.app | Find A Peaceful Protest | Not attending protests because of violence? Find a Peaceful Protest today. | ['Benjamin Man'] | [] | ['esri', 'firebase', 'html5', 'leaflet.js', 'openstreetmap'] | 8 |
10,345 | https://devpost.com/software/nikhil_cloud_star | AWS Cloud Services
Inspiration : The Services Offered By Cloud Computing
What it does : It creates the cloud server
How I built it using AWS
Challenges I ran into to utilise aws services efficiently
Accomplishments that I'm proud of o utilise aws services efficiently
What I learned AWS Subscription
What's next for Nikhil_Cloud_Star
Built With
amazon-web-services | Nikhil_Cloud_Star | Cloud Services in AWS | ['Nikhil Pandey'] | [] | ['amazon-web-services'] | 9 |
10,345 | https://devpost.com/software/yourcloud | messeging screensort
Inspiration
Though I am a beginner, I am very passionate about messenger bot, AI, Deep learning, NLP. These helps me to begin these journey.
What it does
This is a messaging bot used to provide cloud service to each facebook user effectively. Here, User upload his/her files along with some input tags. Later he can find files effectively with this tag and some sentiment analysis. This bot can be used in self to self messaging in facebook and It will help user finding his file easily.
How we built it
This bot is built with chatfuel, some api and plugins. The bot is still in developing stage and It can be improved more.
Challenges we ran into
Many drawbacks we faced to develop that bot. Sometimes It didn't provide exact file by analysis. But after some effort, It starts working.
Accomplishments that we're proud of
I'm really satisfied with the amount of code I could churn out in a short amount of time. I am also proud by participating a big hackathon like facebook.
What we learned
We have gained a vast knowledge working in this project. we have learned how to make an interactive messenger bot.
What's next for YourCloud
Extend the functionality of this bot. Developing some existing work that still exist.
Built With
chatfuel
natural-language-processing
Try it out
m.me | YourCloud | It will be used to provide cloud service to each facebook user effectively. Here, User upload his/her files along with some input tags. Later he can find files effectively with this tag. | ['Avi Pal', 'Sajid Hasan', 'Tanmay Biswas'] | [] | ['chatfuel', 'natural-language-processing'] | 10 |
10,345 | https://devpost.com/software/smartcloud | Description
This is an improved platform to display metrics for cloud services. Having used some before, these platforms become bulky and hard to navigate easily. As such, I used this opportunity to improve the current AWS CloudWatch dashboard. Before, the top and side bars were extremely cluttered, especially creating a problem as they are not feasible for intensive use.
I converted many of the above options to dropdowns from the icons, which allows the top bar to collapse and become far more intuitive. Then, I combined several of the options in the side bar to create a more frictionless approach. I also gave the main dashboard area, with relevant graphs, a "mosaic" look to improve the UX.
About
I used Figma to wireframe this, which proved invaluable as Figma is a great platform for design. The main site is implemented with the regular HTML/CSS/JavaScript.
Built With
html
Try it out
github.com | smartcloud | smart cloud is an improved platform for cloud services | ['Sohini Kar'] | [] | ['html'] | 11 |
10,345 | https://devpost.com/software/ascendant-challenge | Ascendant Challenge is a Dreaming City’s activity that players can complete every week to get gear. The challenge location keeps rotating every week while changing with the level of the curse and may be disturbing for new players.
The planet is so big, and finding certain locations may be difficult for the new players. Ascendant Challenges are not known by most new light players.
DESTINY-2 – ASCENDANT-CHALLENGE-LOCATION-THIS-WEEK – APRIL-28-MAY-4-2020
Dreaming City has three different curse cycles that are Weak, Medium, and Strong. We can use the cursing type for locating Petra Venj, she is the vendor who will give you the Ascendant Challenge.
Her locations are The Strand, Divalian Mists and Rehasilvia for Weak Curse, Medium Curse, and Strong Curse respectively. Recently
sony also reveals the PlayStation 5 Worldwide Release Date.
Ascendant Challenge is an activity that you unlock when you reach Dreaming City and are tied to the Ascendant Plane. Every week players will get a single portal at random locations that act as the door to the Ascendant Plane. The level of the curse determines the location of the Ascendant Challenge every week.
There are few set locations Ascendant Challenge This Week and the rotation happens between these locations only. That is:
Bay of Drowned Wishes
Gardens of Esila
Spine of Keres
Harbinger’s Seclude
Chamber of Starlight
Aphelion’s Rest
destiny-2-Ascendant-Challenge-This-Week
Where are the Ascendant Challenge This Week?
Players especially new ones are always confused about the location for the Ascendant Challenge whenever there’s a weekly reset. Let’s dive into Week’s Ascendant Challenge.
Built With
php
Try it out
omggamer.com | Ascendant Challenge | Ascendant Challenge | ['andrewmacmillan1'] | [] | ['php'] | 12 |
10,346 | https://devpost.com/software/noline-4pteni | app screenshot 3 - line joining screen
app screenshot 2 - line management login
app screenshot 1 - main menu
Mid work selfie
Some bugs
The first day
web screenshot 1 - line manager screen
app screenshot 4 - user view while in line
web screenshot 2 - line view, (you will show this to users to join the line, or you can also print the qr code :D)
app screenshot 5 - the line manger screen, which the manager will use to advance and monitor the line
web screenshot 3 - the main screen on desktop
Inspiration
We came up with the idea while waiting in line in recent times, we all noticed practicing social distancing while still preserving our place in the line can be extremely difficult, on one hand you don't want to lose your place in line by staying to far, but due to recent time crowding with a lot of people can be very dangerous for your health.
So we thought, why do we all have to crowd up in here? Technology can allow us to organize a line without actually being present, that way we can both stay safe and stop wasting our time waiting in lines.
What it does
noline is a web app that allows users to create and manage queues of people for any purpose, you can easily create a new line and get an easy screen which contains a qr to join the line, and a range of ways to join it.
from the user side, you can join the line easily, and leave your phone number so you will be notified when your line will arrive, while monitoring how much time you have until its your turn :D
How we built it
We used the flutter framework to build the project, since flutter just launched an option to use their technology to build web apps, and we thought it would be an awesome learning experience! for the server side we used firestore and firebase for the database that manages the clients, lines, and sms notification service. and for actually sending the sms messages automatically, we used a nodejs server which uses the Twillio platform (right now in trial mode :D), and will allow users to leave their phone number and get an sms message when their turn is coming soon, and they should get near the line.
Challenges we ran into
We wanted to make the app as accessible as possible on one hand, and also allow people that are not used to messing with complicated technology to join it easily. which created a big challenge.
In addition we wanted to allow line creators and managers create and manage the line in seconds, and with no need for additional equipment other then their phone / tablet / pc.
Accomplishments that we are proud of
Setting up a custom QR code for each line which will be auto generated was an extremely difficult challenge, also working for 2 days intensively as a team was crazy fun :D
Setting up the nodejs server which sends SMS message automatically was also a great challenge we managed to overcome, and are extremely proud of finishing.
What We learned
We each learned a lot about new programming languages (some of us didn't use flutter/dart before and for sure nodejs :D), usage of complicated frameworks, and setup of servers that will run automatically with our products on them was an amazing learning experience. Also working as a big team (5 people) was very intensive and we had to use git intensively to keep one another in tact, which can get hard while working fast on a project.
What's next for noline
Our first goal is to get noline on more platform other then the web, and upload an app to the google play and IOS stores for easier access for users who can download those apps.
We also want to get our SMS server connected with a premium twillio account which costs more than we could afford for now.
And finally it would be great to finish up so more nice touches on the app, improve security with password for each line manager, allow them to go back on the line in cased they missed people, and allow them to reset the line easily.
We are crazy excited for this project and want to continue working on it and get it out there after this hackathon :D
on a personal note we want to thank you guys for making the last 2 days great for us! it was an awesome experience :D
Raz, Yotam, Liad, Koren, And Harel
Built With
dart
express.js
firebase
firestore
flutter
heroku
node.js
qr
twilio
Try it out
noline-dbc7f.web.app
github.com
github.com | noline | noline is an awesome web app that allows you to manage and join queues for any purpose online and without actually being present in the queue! we hope it will help humanity practice social distancing | ['Cohen Liad', 'Harel Finaly', 'harryhannum Hannum', 'Koren Minchev', 'Raz Gino'] | ['1st place'] | ['dart', 'express.js', 'firebase', 'firestore', 'flutter', 'heroku', 'node.js', 'qr', 'twilio'] | 0 |
10,346 | https://devpost.com/software/speech-assist-k9vwyi | Speech to text
Sign language to text
Inspiration
We were inspired by the fact that there are over 466 million people in the world with disabling hearing loss and globally the number of people of all ages visually impaired is estimated to be over 285 million.
(WHO, 2018 & 2010, respectively) Yet, despite this pandemic creating numerous additional barriers for people with disabilities, there have not been many accessible, convenient, or affordable solutions.
Most people who are deaf and hearing-impaired depend on the ability to read lips to converse with others, and a facial covering that impedes communication can increase frustration and affect their mental health.
When the volume of speech is reduced, the listener must concentrate harder to understand and follow the communication. Couple this reduction in volume with the inability to lip-read, and it can make it very frustrating for hard-of-hearing and deaf individuals, as well as the general population.
What it does
Our app
Speech Assist
helps people by transcribing speech into text on their screen in real-time. With masks being mandatory in many countries, its difficult for people with hearing impairments to interpret others. Our app provides real-time speech transcription of speech to text, text to speech, and video to sign language format. We also provide a resource and community help page.
The voice & speech recognition market will be worth $26.8 Billion by 2025 with speech recognition commanding the largest share due to increasing consumer demand, confidence, and usage. Over 466 million people have disabling hearing loss and over 285 million have a visual impairment. The speech to text API market size is 1.3 billion.
This app meets consumers increasing demand due to most events moving online. Industries that will require it include healthcare, e-learning, and media & entertainment to optimize operations. Speech-to-text solutions offer faster transcription, low costs, and high accuracy.
We could potentially sell access to the software like the API, and a Subscription for users to use the app, and ensure we can provide discounts for non-profits and support individuals if they cannot afford it, etc., This app has the potential to improve the lives of millions of people by Creating accessible platforms and safe spaces for people. We are leveraging growing technologies like AI, Blockchain, and Machine Learning to innovate our world. Voice and Speech recognition has numerous applications, including automotive, healthcare, education, hospitality, government, and public services, manufacturing/enterprise, retail, and e-commerce. Thus, the impact is infinite.
How we built it
Ethereum Web3.js, Truffle, Ganache, Solidity, HTML/CSS, Flutter, Dart, TensorflowLite, TeachableMachine
Challenges we ran into
Because our group consisted of members in the UK, India, Australia, and Canada, it was quite difficult to manage the time difference and continue the work through the midnight hours. Also, a lot of time was spent figuring out how to use the teachable machine and integrating the ML model in Flutter. However, we combatted this by staying in touch through the channels and keeping everyone in the know on what was happening and meeting virtually. In addition, Ideation was difficult as we had numerous ideas, and bringing together several ideas and possibilities down into a single app definitely took time. We went through various ideas and how we could execute them. In addition, finding the React component not working properly caused additional challenges to overcome and the integration was a bit messy.
Accomplishments that we're proud of
We are really proud to have accomplished the work that we had in the strict timeframe. Being able to learn from one another and communicate on a consistent basis was quite an accomplishment since we are all in different time zones.
What we learned
This app integrated principles including machine-learning, blockchain, and AI. Thus, it really was a learning curve and we learned new languages and frameworks. We learned a lot about the statistics related to people with disabilities as well as the progress and growth of the voice and speech recognition market. We also learned and developed time management and communication skills. It was a great experience to work with a group of inspiring women from across the world (for us, our group consisted of members in the UK, India, Australia, and Canada, and being able to manage the large time difference has proved that we are not only resilient but that barriers do not define us).
What's next for Speech Assist
The options and applicability of Speech Assist are endless, and we believe that this app will help numerous people globally. We created this app because we want to improve the lives of millions of people. We want to continue to create accessible platforms and safe spaces for people to support one another and improve communication across the community.
We would love to dive deeper and continue to leverage growing technologies like AI, Blockchain, and Machine Learning to innovate our society and advance our world. (Voice and Speech recognition has numerous applications, including automotive, healthcare, BFSI, education, hospitality, government, and public services, manufacturing/enterprise, retail and e-commerce, legal, consumer electronics, and military and defense), and technology type (artificial intelligence, and non-artificial intelligence) The options are endless for the different applications and subsets we can build with this app and structure.
Built With
css3
dart
ethereum
flutter
html5
solidity
tensorflow
web3
Try it out
github.com | Speech Assist | Aids interpretation for the visually/hearing impaired, especially while wearing masks. Transcribes speech to text, text to speech & video to sign language. Provides resources and community support. | ['Grace Gong', 'Akhila F', 'Akanksha Singh'] | ['2nd place'] | ['css3', 'dart', 'ethereum', 'flutter', 'html5', 'solidity', 'tensorflow', 'web3'] | 1 |
10,346 | https://devpost.com/software/addhyan-gqdepo | ..
Built With
bootstrap
css3
html5 | Add | ! | [] | ['3rd place'] | ['bootstrap', 'css3', 'html5'] | 2 |
10,346 | https://devpost.com/software/mespero-impact-tech-for-resilience-and-mental-health | GIF
Goals
In these two days of Wonder Women Tech's Hacks 4 Humanity, the MESPERO project had two primary goals
1. To move from app idea to prototype mockup
:
Specifically, the idea for this app originated early in the COVID crisis, as we witnessed friends, colleagues and clients experiencing significant mental injury. So, we conducted an
informal, exploratory survey on preferences in mental health apps
in June and, in these two days of Wonder Women Tech's hackathon, were finally able to use those research findings to build the prototype mockup.
2. To build from 'crowdsourcing lived experience' idea to proof of concept
:
One of MESPERO's major innovations is its focus on
culturally-sensitive iteration
empowering local populations to share their lessons learned from lived experience. Equally important is the project's focus on supporting people to tell their own stories and share their own wisdom within the context of
diversity and inclusion.
In short, the goal is to support specific target groups to create and
scale their unique narrative of healing.
As such, the second part of MESPERO's participation in this hackathon was a
virtual workshop for five women with some form of lived experience around resilience, emotional wellbeing or mental health.
The participants were introduced to the basics of virtual learning and supported in digitally defining their preferred narrative.
For the Wonder Women Tech Hack pilot workshop, we selected five women reflecting diverse demographics:
Italian nurse, 30s, dealing with COVID patients
and who is now experiencing insomnia
US military psychiatric nurse, 40s, serving abroad
and concerned that some of her new cohorts have a different view of how to conduct mental health intake
Japanese HR head, 50s,
whose company is dealing with a sharp spike in burnout cases
Syrian woman, 30s, of a refugee background
who had her preexisting PTSD triggered by the lockdown
Austrian woman, 20s,
who is becoming increasingly despondent in her job search
Heather gave these women a short virtual workshop on Sunday and worked individually with them on Monday to create their preferred digital narratives.
Inspiration
The Global Issue
:
The World Health Organization estimates that one in four people will have a mental-health disorder during her/his lifetime with countless others at risk due to personal, societal and environmental factors. The vast majority will not have sufficient access to mental-health support.
Meanwhile, mental health issues among the general population globally have worsened dramatically under Covid. 2.7 billion people, or more than four out of five workers in the global workforce, have been affected by lockdowns and stay-at-home measures. The rise in mental health challenges has already impacted the labor force and is expected to continue long-term.
And for an additional hundreds of millions of people living at the poverty line or in societies in which discussing mental health is taboo, the negative impact of this pandemic is arguably much more severe.
Yet at present, there is no cost-effective and integrated solution for promoting emotional wellness while preventing and treating mental health issues on a mass scale - let alone one which is culturally-sensitive and empowering of local populations to tell their own stories.
The Personal Challenge
:
As a psychotherapist, Heather has spent much of the pandemic supporting others with emotional and mental health issues related to the lockdown.
As an organizational development consultant, she has worked with many HR managers now facing heightened levels of workplace burnout, depression, anxiety and substance abuse - all within the context of major budget cuts.
As a youth mentor, she has seen the devastating impact that the pandemic's disruption has had on adolescent depression, anxiety, ADHD, and general quality of life.
As mental health advocates, many of us connected to MESPERO have witnessed how the lockdown has exacerbated preexisting conditions such as PTSD related to war or domestic violence in various populations.
And in all of these circumstances, we have discovered that there is a significant lack of resources available for these individuals, let alone on a
culturally-sensitive and inclusive basis.
So, as
human rights activists focused on Impact Tech,
we decided to create a project contributing to a creative, innovative, and sustainable new approach for Social Good. That's how MESPERO was born.
What it does
MESPERO aims to promote resilience and emotional wellness while mitigating mental injury (from COVID 19 and other sources) for multiple target groups. Emphasis is on building mental fitness while expanding preventive choices.
Additional focus is on adapting to unique and disadvantaged target areas
(ranging from refugee camps in Jordan to hospitals in Harlem to barrios in Bogotá) through culturally-sensitive iteration.
The
humanitarian impact of decreasing stigmatization around mental-health issues and enhancing quality of life globally
is in scope. A further goal is
mitigating the negative societal impact of untreated mental-health issues
such as increased risk of violent offense, conduct disorders, substance abuse, and extremism.
This innovation will be carried out through culturally-sensitive iteration empowering local populations to share their lessons learned from lived experience.
We are also developing
youth-empowerment and mentoring programs
to improve mental-health literacy and reduce stigmatization.
How it was built
In these past few days, Heather built the mockup with proto.io and on the basis of extensive research conducted a few months ago, as described above. The workshops and related digital interactions deployed Articulate 360 and Raptivity.
While building this prototype mockup and doing the related workshops were carried out during the past two days, however, it must be said that MESPERO is a team effort that has existed for some months. Psychologists, HR professionals, academics and organizational development experts are among the volunteer consultants who believe in this project.
The five women mentioned above also volunteered their time and provided valuable feedback in being among the first cohort to take the workshop.
Foremost among those who have provided valuable insight every step of the way of MESPERO's development, however, are the women of
SDG 5 Thrive
(alphabetically:
Rania Ali, Doaa Al Zamel, Nour Barakeh, Suad Mohamed
). These inspiring young women have already contributed greatly to the promotion of humanitarian causes, the scaling of mental health awareness and healing, and the pursuit of greater Social Good.
Challenges run into
No major challenges. Lack of sleep and the necessity to make do with limited financial resources, but as MESPERO has so far been a volunteer project, that is normal ;-)
Accomplishments to be proud of
We are proud of everyone connected to MESPERO and look forward to our next steps!
But rather than pride, the driving force behind MESPERO is the understanding that millions – if not billions – of people right now are not being equitably served regarding emotional wellbeing and mental health.
MESPERO can and will make a difference. We will reach those populations and empower them to share their own wisdom around healing.
What was learned
During these past few days, we got great feedback on tweaking the workshop for different target groups, in this case specifically for: US military nurse, COVID healthcare professional, multinational HR head, person of a refugee background, young job seeker.
We learned a lot about transposing research to app design when making the prototype.
One note re. AI: It is clear that many of those connected to Wonder Women Tech are connected to the field of AI. It is also clear that chat bots and related technology are widely used in mental health apps.
However, in general, it must be acknowledged that AI systems are only as good as the data put into them. In addition, numerous mental health target groups are hesitant to use AI or chat bots due to (often valid) privacy concerns.
As such, MESPERO will not incorporate AI or chat bots at this time. That might come later with specific target groups, but for now, we will focus on enabling groups to develop and share their narratives instead.
What's next for MESPERO: Impact Tech for Resilience and Mental Health
To get funding to build the app and to scale the 'crowdsourcing lived experience' approach far and wide!
Built With
articulate-online
heartandsoul
proto.io
rise360
storyline360 | MESPERO: Impact Tech for Resilience and Mental Health | MESPERO digital self-care promotes emotional wellness while mitigating mental injury including for those disadvantaged. We crowdsource solutions by harnessing lessons learned from lived experience. | ['Heather Wokusch'] | ['Honorable mention #1'] | ['articulate-online', 'heartandsoul', 'proto.io', 'rise360', 'storyline360'] | 3 |
10,346 | https://devpost.com/software/i-can-see | Proposed Solution
Inspiration
Technology can be of assistance in incredible ways. Please, check the illustrations in the video.
There are several apps for people with visual impairment. They can read text, recognize objects and even count money (cash). However, this is not enough. What about letting a blind person receive a meaningful description of the scene in front of them? What if we return them the possibility to see through the ears. Current state-of-the-art methods could make this happen. In this project we just try to make it real.
What it does
By using a wearable camera, visual information is captured and processed in order to generate a description of what appears in the image. This description is told to the blind person so he/she could know what is happening in front of them.
Of course, it is not perfect and has mistakes, but
How I built it
Using existing research and implementing it on tensorflow. It required to train for long and of course a lot of data!
Challenges I ran into
Training time is long for the timing of a Hackathon. Training further would provide better results.
Battery usage and memory constraints due to limitations of wearable devices
Accomplishments that I'm proud of
Use technology to try to help people in need
What I learned
Technology already exists: let's use it!
Current research is amazing and advances quickly. Let's bring it to reality!
Research is under constant improvement and there are mistakes, but for sure the current state is better than not having anything like that at all!
What's next for I can see
Bring this to people by getting a funding!
Keep improving and keep updating this assistance following updated advances in science.
Built With
gpu
python
smartglasses
tensorflow
Try it out
sheilacaceres.com | Eyemazing | Make technology be the eyes of people with visual impairments. | ['Sheila Caceres'] | ['Honorable mention #2'] | ['gpu', 'python', 'smartglasses', 'tensorflow'] | 4 |
10,346 | https://devpost.com/software/vestige | Login Page
Supermarket page
Dishes
Supermarket products
Restaurant page
Inspiration
Various restaurants and supermarkets, waste tons of food, and expired products. People don't buy items that are about to expire and these are usually sold out at a cheap rate and eventually gone to waste. So why not give these to people those who actually need it at a cheaper rate, of course telling them the product would expire soon. Restaurants have buffets and events and tons of food are cooked for the same. These technically aren't leftovers but these are definitely going to waste, so why not give this out for free or sell it at a cheaper rate. This would definitely bring a smile on a family's face.
What it does
We have a web app and a mobile application, each extending each other's features. The mobile app uses your location and finds the nearest store in your location and provides you details of their about to expire products and restaurants that have extra food and are willing to sell it for a lower rate. The web application focuses on the society where people that can buy and afford these things, can give it to the poor for free as a donation.
How I built it
The mobile app was made on Flutter, Firebase, and Google Maps API SDK. The web app was designed with Pug, Flask, and Node.Js for the backend.
Challenges I ran into
A couple of integrations and CI/CD pipelining failures, which was later fixed.
Accomplishments that I'm proud of
Teamwork and coming up with a sudden project and finishing it in no time was devious but we did it.
What I learned
Use of new technology and time management.
What's next for Vestige
ML and AI integration for better prediction and analysis of hotels and supermarkets.
Built With
dart
flask
flutter
node.js
pug
Try it out
github.com | Vestige | An app that helps the needy by providing them with excessive foods that are cooked in a restaurant and also the cheap sale of soon to be expiring goods to help the needy and people who can't afford. | ['Ipshita Joshi'] | ['Honorable mention #3 - based off of Voting from Public'] | ['dart', 'flask', 'flutter', 'node.js', 'pug'] | 5 |
10,346 | https://devpost.com/software/alert-alligator | Inspiration
Wildfires in oregon
What it does
Alerts users of poor air quality and natural disasters
How we built it
Entirely on heroku
Flask frontend
Postures sql database
Redis Queue for alerts
Mailgun for emailing
Python for glue
Challenges we ran into
Didn't know heroku
Accomplishments that we're proud of
Actually works for air quality
What we learned
What's next for Alert Alligator
Built With
flask
heroku
python
Try it out
alert-alligator.herokuapp.com | Alert Alligator | Alerts users of air quality any natural disasters in their area. | ['Mikayla Friend', 'zachary trudo', 'Sheyla Trudo'] | [] | ['flask', 'heroku', 'python'] | 6 |
10,346 | https://devpost.com/software/beyoutiful-app | Inspiration
We were inspired by our own experiences surrounding our own struggles with society's perception of body image. Being young girls ourselves growing up in the digital age, we wanted to help find a solution or something to relieve the stress.
What it does
This app is a way to combat the social issues which arise when constantly being surrounded by "perfect people". It alleviates pressure by being a constant reminder to the user to look after themselves and love their bodies.
How I built it
We started with our idea of an inclusive, welcoming environment and decided what we would like if we wanted an app to get away from social media.
We built it on a webpage with a mobile app format in mind, using html, css, javascript.
Challenges I ran into
Our team are amateur at coding. Without a strong foundation, we were still able to produce a website. There were definitely problems with the navigation bar and photos aligning which couldn't be resolved in time however we are going to work on the website for longer. With time, we can smoothen the creases. Our team are very amateur but were enticed by the challenge.
Accomplishments that I'm proud of
We enjoyed learning html and css very much and this project was definitely motivational in our learning progress. Furthermore, we have both never worked as a team on a project like this. We worked very well together, constantly checking up on each other and helping find solutions.
What I learned
We learned the basics of html, how to style a webpage and how to incorporate an idea into code (which we found to be the hardest!). We also pushed ourselves and included image maps and lists from user inputs.
What's next for beYOUtiful app
The 2 days felt very short and we want to continue improving the design and features on the app. We are young girls inspired by women in STEM and are hoping to pursue this in our future.
Built With
css
html5
javascript | beYOUtiful app | App for female body confidence :) | ['Karen Li'] | [] | ['css', 'html5', 'javascript'] | 7 |
10,346 | https://devpost.com/software/breast-cancer-awareness-and-detection | GIF
Our App Prototype
Our App HomePage
Features of our App
Blog Page
Join the Cause
Find Support
Breast Cancer Awareness
Inspiration
In a lifetime, 1 in 8 women in the World develops breast cancer, as reported by the National Breast Cancer Foundation. Although breast cancer is the most common cancer among women in the world, increased visibility, early detection/screening, and improved care options have helped to reduce death rates in the past 30 years. It's our priority to raise awareness for Breast Cancer and detect breast cancer at an early stage in life hence we are in the need to develop such a solution.
What it does?
Help breast cancer patients and carriers find the knowledge that is accurate and trustworthy with ease.
The solution to monitor side effects of specific cancer treatments in Breast Cancer.
The solution to monitor side effects of specific cancer treatments in Breast Cancer by the government.
The solution to detect Breast Cancer at an early stage in life.
How we built it?
We have created a web application using PHP, Perl, and javascript that has numerous facts, features, functionalities to raise awareness for Breast cancer. We have also made an AI-based model which will be based on a different extracted feature from an X-ray predicts whether the tumor is malignant or benign.
Challenges we ran into
The idea itself is tricky as very few people think of such a sensitive concept.
Also, Understanding the UCL data set for the prediction of breast cancer is bit complex.
Accomplishments that we're proud of
Thinking of an idea that is new to the society and is for the social good for our Women.
Implementing our idea into a WebApp Prototype Model.
Creating awareness among people especially women of all ages.
Detecting the Breast Cancer at an early stage in women using our AI Model Dataset Analysis.
What we learned?
The idea itself was really challenging for us.
We learned the proper way to implement our idea into something from where anyone in the society can benifit.
We learned the Art of Solution-Building and integrating SOciety related problems into Technological Solutions.
Through the challenges, we learned a lot of WebApp Designing.
The Languages used were in itself very challenging.
Dealing, Cleaning, and Preprocessing of Data Collected.
What's next for Breast Cancer Awareness and Detection?
We are ready with our model. In the long run, we need to make an automated image processor for the extraction of features and implementing them on the web. Taking this a step further, we will also be implementing the same for Men.
Pink for Women, Blue for Men. Yes !! Men Get it Too.
Built With
javascript
machine-learning
perl
php
python
Try it out
github.com | Breast Cancer Awareness and Detection || WebApp + AI Model | There can be life after breast cancer. The prerequisite is early detection. | ['Amit Patel', 'Anushka Upadhyaya'] | [] | ['javascript', 'machine-learning', 'perl', 'php', 'python'] | 8 |
10,346 | https://devpost.com/software/sociobox | Chatbot & landing page
login
signup
home
onboarding 1
onboarding 2
forum
creatNew
post
Inspiration
In the age of information overload, we believe that individuals who want to stay informed need a better way to access quality information about relevant social issues because it’s difficult to know where to find trustworthy, easy-to-read, science-based information that efficiently provides you with a comprehensive understanding of the issue.
User Interview Results
What it does
Sociobox captures the best resources and packages them together in order to deliver an educational experience that’s both enlightening and enjoyable. It includes a variety of mediums for all learners: videos, audiobooks, articles, virtual events, etc. as well as ideas for action steps that users can take to further the cause, and a community platform so they can discuss their thoughts with other users.
Each month, the focus of the box changes. One month it may be focused on genetic engineering, sustainable consumerism the next, and human trafficking after that. This nudges users out of their comfort zone as they're motivated to expand their horizons by diving deep into an issue that they may not otherwise become very familiar with. To make learning more effective, users are encouraged to participate in conversations with each other. Looking at the same resources gives them a shared language so it's easier to talk about complicated problems.
Features
Sign up with a name, email, and password
Login with email and password
View the social issue of the month on the home page
Access a curated list of resources related to the topic (video/podcast/articles)
Play a video
Read article
Listen to podcast
Save pages to revisit them
Join the community forum
How we built it
Low fidelity wireframe using balsamiq
High fidelity wireframe using Figma
Front-end development using React, Redux
Back-end development using Node.js, Express.js and mongodb
Chatbot using Dialogflow and Google cloud
Challenges we ran into
We ran into some git problems and merge conflicts, but we were able to resolve them with effective communication and stack overflow. We had a hard time finding reliable sources of information, APIs such as BBC API are available to staff only. Other APIs have a limit of free API calls. Due to time constraints, we weren't able to make use of all api endpoints created on the backend. 5 minutes before the deadline and after deployment, we found out that one of the APIs only works on localhost (developer plan).
Accomplishments that we're proud of
We have completed the whole
UI design
for the app (including stretch goals), a fully functional
chatbot
and completed the
front-end
and
back-end
development of the app (main features). Our app can be accessed
HERE
What we learned
We learned how to use Figma for UI design, react for front-end development and using the new beta feature of Dialogflow for chatbot. We learned to use Redux for state management and create associations/references between forum, discussion, and message database models on the backend and add/delete/update tables in MongoDB.
What's next for Sociobox
New features
Customizable feed
Users can choose the update frequency (daily/weekly/monthly), prioritize issues (local/national/global issues), select the media that appears (article/podcast/video), and the length of the video/podcast.
Friends & private chat
User can add other users as friends and chat in private
Fundraising
Add an option to allow users to donate to a particular cause/organization involved in a particular social issue - or - provide enough value that users feel comfortable paying a monthly subscription fee that will be donated to the issue of the month.
Rewards Program
Keep users engaged by rewarding them for completing the list of resources each month and being active in the community.
Built With
balsamiq
css
dialogflow
express.js
figma
google-cloud
html
javascript
mongodb
node.js
react
Try it out
github.com
github.com
www.figma.com
bot.dialogflow.com
sociobox.s3-website.us-east-2.amazonaws.com | Sociobox | Your FREE Social Good Subscription Box | ['Ava Chan', 'Darren Zhang', 'mat many', 'Chelsea Polak', 'dina tahoun'] | [] | ['balsamiq', 'css', 'dialogflow', 'express.js', 'figma', 'google-cloud', 'html', 'javascript', 'mongodb', 'node.js', 'react'] | 9 |
10,346 | https://devpost.com/software/capsulize-3701vw | Inspiration
Our workplace struggled to adjust to the new reality with the threat of the pandemic looming over both wellbeing and productivity. Dividing the workplace into shifts and sealed off capsules proved an immensely complex task considering how many workplace dependencies exist in our environment. Furthermore, many employees were affected by frequent shifts of public transport availability, which meant they had to find other ways of commuting to and from work.
Those difficulties led us to believe there is a need for a service capable of handling large and complex employee data sets and provide an optimal division that would allow the workplace to maintain its productivity while protecting its employees.
What it does
Capsulize divides the workplace employees into shifts (each working in different hours), capsules (groups of employees sealed off from the rest of the company), and workspaces (based on each employee's preference). Capsulize also provides a carpool plan based on the employees' home location and mode of transportation.
How we built it
We implemented the core algorithm in python, and integrated it into a flask server. The client side forms are just good old html + css.
The algorithm
The algorithm is designed to run in several stages.
The first stage assigns employees into shifts. It does it by mapping every "shift dependency" (i.e. an employee stating he cannot be productive without a coworker available in the same shift) and binding dependent workers to the same shifts. Each worker is assigned to his workspace (load balancing is done at a later stage to ensure room occupancies don't overflow).
The second stage assigns workspaces to capsules. This mapping is performed in a way similar to how to first stage maps "shift dependencies", but in this case we map workspaces based on their occupying employees' "capsule dependencies" (i.e. the cowerkers the employee has to have physical contant with).
The third and final stage groups employees working in the same shift into carpools. It calculates travel distances between employees and prioritizes employees with fewer carpool options to maximize the car capacity utilization.
What's next for Capsulize?
Workspace and capsule load balancing features are currently missing.
A better ui design, probably with a rich client framework.
Built With
css3
flask
html5
javascript
python
Try it out
github.com | Capsulize | Capsulize divides company employees into shifts and capsules in order to mitigate the spread and effects of pandemics such as COVID-19. | ['Almog Kradshtein', 'Maor Haim', 'Michael Shustin', 'Or Zamir'] | [] | ['css3', 'flask', 'html5', 'javascript', 'python'] | 10 |
10,346 | https://devpost.com/software/complimentz | Block page
Send Compliments Page
Sign Up Page
Menu + Today's Compliment Page
Front Page
Inspiration
My mobile app aims to help people with low self-esteem and make someone's day better.
What it does
My app allows you to receive a compliment every time you open the app. The compliments come from other users (who are likely friends) as well as a pool of pre-loaded compliments (just in case you don't have any friends ;__;). You can also block users who are bothering you. The last functionality that was supposed to be implemented was sharing a compliment you liked through facebook, but I didn't get around to that. All in all, this is a fun app designed to help people with low self esteem and make someone's day better.
How I built it
I built this app on android studio (java). I got some of the art I used in the app through google (free for commercial use images) and I made some of the images myself via Photoshop. I used an SQL database to store compliments, blocked users, and accounts. If I had gotten around to it, the facbook connection would have been done through the facebook SDK (
https://developers.facebook.com/docs/sharing/android
).
Challenges I ran into
Doing this myself in 24 hours was a challenge. I also ran into a lot of bugs with the SQL database insertions. This is also my first time using popups for an android app, so that was something I had to learn quickly. Some of my code still doesn't look optimal, but it is working, and I plan to clean it up later.
Accomplishments that I'm proud of
Doing this myself in 24 hours and learning popups when university has already started.
What I learned
I learned how to make popups appear for android apps. I also learned a bit about how to make an app compatible with various screen sizes (like for phones vs tablets).
What's next for Complimentz
Compatibility with various screen sizes, facebook integration, bug fixes for blocked users, better graphics for showing the current compliment, perhaps some sort of internet scouring system that looks for new compliments and adds them to a general pool every day. Finally, publication.
Built With
android-studio
java
Try it out
github.com | Complimentz | Funny compliments to brighten your day. | ['areeja132000 Ali'] | [] | ['android-studio', 'java'] | 11 |
10,346 | https://devpost.com/software/quaranteam-orgqb3 | WelcomePage
Some Information about COVID-19
Login
Covid19 Stats
Salute to the heroes
Movie
BookRecommendations
Games by us
BlogPage
Events
Inspiration
INSPIRATION
We are facing a global health crisis unlike any in the 75-year history of the United Nations — one that is killing people, spreading human suffering, and upending people’s lives. But this is much more than a health crisis. It is a human, economic and social crisis. After extensive research work, we have come across various problems that are being faced by every section of the society.
-People without access to running water, refugees, migrants, or displaced persons also stand to suffer disproportionately both from the pandemic and its aftermath – whether due to limited movement, fewer employment opportunities, etc.
-Older persons are not just struggling with greater health risks but are also likely to be less capable of supporting themselves in isolation, thus they become very easy targets of mental health disorders like anxiety and depression.
Cancellation or postponement of large-scale sports and tournaments, closure of the hotels, restaurants and religious places, closure of places for entertainment such as movie and play theatres, sports clubs, gymnasiums, swimming pools etc has had a massive effect, whether it be in terms of employment or lack of resources for entertainment.
Postponement of examinations has left students in a state of uncertainity, and they’re falling into the cycle of overthinking and hampering their mental health.
-Even doctors, who are already struggling and risking their lives to help the world heal, are facing so many issues. Lack of proper equipment like PPE has forced them to resort to measures like using raincoats and helmets as a safety precaution.
QuarantTeam has come up with a solution to provide a common platform where all these problems can be addressed, heard and solved efficiently!
What it does
1) A platform to appreciate the frontline warriors who solve the problems of millions, who have risked their lives for us without any second thought. They need our much needed appreciation and applause.
2) Encourages community building by updating about the details of the virtual events that are being held, so that there can be collaborations between NGO's and various organisations while staying at their own place of comfort.
3) A section where we have books that can be read online and also a movie recommendation system. And the fun part is, we have super cool games, both one player and two player, to kill boredom while quarantined at home.
4)For anyone who needs to vent out their pent up feelings, we have the blog section where you can write and read other blogs as well
5) A platform where anyone who needs help or has a particular need to be catered, can submit his/her requirement and those who can volunteer to help can contact them to fulfill their needs!
Unique Features
Honoring and appreciating the efforts of all the people on the front-line providing us all the services and help in this pandemic.
One player and multiplayer games which are self made using unity can be played on our website.
We provide real time COVID stats which helps a person recognize the red , orange and green zones in the location
Movie recommendation system which displays movies based on ones choices and preferences.
How we built it
FRONTEND
: HTML5, CSS3, Bootstrap4, JavaScript,JQuery
BACKEND
: Firebase
OTHER SOFTWARES
: Unity
EDITORS
: Visual Studio Code, Sublime Text , Visual Studio
Challenges we ran into
We were initially focusing on building on AR games but they can’t be used on website and hence, we made 3D games using Unity.
In READMORE function used in blog section , our page was loading before the JavaScript was executed. We tackled it by using Local Storage.
We were also having problem with Read Now ! Button in books recommendation but we were finally able to solve the problem.
Accomplishments that we're proud of
We were able to web-host unity games which was quite a task!
We were able to complete a fully working website in 27 hours.
Being newbies the pressure was real but the experience of building was amazing.
What we learned
Team Spirit
Time Management
Team Work
Working on real world problems
Competitiveness
Being Optimistic
Achieving a lot of Confidence
What's next for QuaranTeam
No project can be perfect there is always scope of improvement with time ;)
--> We could also add a personal chat feature for people to communicate better.
--> Last but not the least, during this time mental health is something we need to emphasize on and we would want to dedicate a whole section of this website to mental health where people can check their mental health score through a questionnaire and if it we are not satisfied with the result we could recommend them a psychologist or a counsellor for the same.
Built With
aos
bootstrap
c#
css3
firebase
git
github
html5
javascript
unity
Try it out
github.com
deekshitav.github.io | QuaranTeam | Surviving the Pandemic like a Hero!! | ['DEEKSHITA VERMA', 'Cheshtha Agarwal', 'Shrankhla Srivastava', 'Shivangi Goel', 'Aastha Jain'] | [] | ['aos', 'bootstrap', 'c#', 'css3', 'firebase', 'git', 'github', 'html5', 'javascript', 'unity'] | 12 |
10,346 | https://devpost.com/software/lazarus-bmuzxd | Inspiration
1.All proximity trackers applications of today like Aarogya Setu of India or BlueTrace of Singapore demand that each of its users have a BLE enabled smartphone(for example an operating system of KitKat or greater for Android users) and the technique is effective only when large chunks of the population are using this smartphone application. But that cannot be the case for countries/regions with large populations and considerable proportions of low income groups. As a result, a lot many people are left untraced and their contacts with an infected person can be determined only by on-field investigation relying on people’s memories. Also regular app users cannot reap full benefits of it when so many people around are untraced.
2.Moreover, such BLE proximity trackers are region specific, restricting contact tracing for an individual within borders, which can prove to be fatal for international flyers.
3.If a person tests positive for Covid19 he/she must be interviewed by healthcare workers to trace contacts which may have been missed by tracking techniques. But reproducing all interactions accurately from memory is not possible and also healthcare workers have to repeatedly come in close contact with patients. None of the trackers provide any solution in such a case.
4.None of the prevalent applications support accessibility for any kind of people with disabilities.
5.Covid19 contact tracing apps have no utility outside the domain of pandemic control.
What it does
Lazarus app allows multiple users to register on a single smartphone. After sign-in, each user can open up the dedicated interface for his/her account and use all app features including BLE tracker, such that all actions taken, data generated and stored are in accordance to this particular user.
Now suppose user B starts up BLE tracker on his/her interface and leaves. The others cannot record their contacts when they go outside. For this we have a ‘SIGN-IN’ feature to record contact with someone without a smartphone or not registered at all. The smartphone carrying app-user (say user D) can ask for the phone number of the person with no smartphone or account (say person E). D enters this number on its app interface and the interaction between E and D is immediately recorded.
But individuals are not much likely to exchange phone numbers to record contact with every person they meet as the number of dedicated smartphone app users will always be much less than that of shared app users or that of non-registered individuals. To solve this, we have introduced a special type of account called ‘Desk’. Places of close human gatherings like receptions, customer help desks, shops, classrooms, doctor’s clinics can be registered as Desk user in the app by the person-in-charge. This desk operator can keep recording attendances for anybody entering this space with the same Sign-in method mentioned above.
This Desk account feature also generates readymade data regarding which places behaved as hotspots, without actually tracking down location of each infectious human-to-human transmission. The Desk user can also use BLE proximity tracker just like individual accounts.
Apart from Sign-in method, QR exchange feature is also available where one user can scan QRs displayed by other users (individuals or “Desk” users) and record contacts.
All the above interaction recording methods (BLE tracker, SIGN-IN feature, QR exchange feature) use an algorithm that generates unique time stamped code for each interaction (individual to individual and desk to individual) that is stored in the account data of the users involved. If an individual falls sick or a desk turns out to be hotspot, all associated past interactions can be easily traced back and the involved users be warned.
To overcome the difficulty in reproducing interaction history from memory, an in-app “Enter Daily Log” option is provided where the user can wilfully enter his daily whereabouts just like maintaining a diary. All the log entries are then filtered by Microsoft Azure’s natural language understanding LUIS model, to extract key information like location, time and person or number of persons interacted with, which is then stored with date stamp.
How I built it
Microsoft Azure AD B2C--for user authentication
Azure Functions--for recording human-to-human interactions without BLE, using phoneNo(SIGN-IN feature)
Azure LUIS--for analysis of text input in "Daily Log" feature
Microsoft Healthcare Bot--for symptom checking
Google Cloud Firestore--to store interaction data temporarily for the user without a smartphone(person E in above example) in SIGN-IN feature
Challenges I ran into
Being from a core engineering background, developing a mobile application was not easy. Barring basic programming, algorithm and data structure, database management knowledge, everything else about app development and using cloud resources had to be learnt from scratch. Since I wanted an application that was available on both Android and iOS, I chose Flutter environment for my development process. Though programming and UI design on Flutter were easy to understand, but since Flutter is a fairly new platform, not all required features were available in readymade libraries and integration of Microsoft Azure's cloud services especially required reading a lot of documentation. Use of Bluetooth Low Energy on Flutter also required effort. YouTube videos and open-source Github repos helped a lot.
Accomplishments that I'm proud of
Figuring out cloud services was daunting but it helped in the app's features tremendously and I would like to develop more solutions for social good using cloud services with the right mentorship and support. I learned to push myself through scheduled tasks in order to complete the project. As the project involves a lot of activities happening simultaneously, there was no shortcut for any feature. But I feel happy about myself that I could patiently read through sample codes and documentation an learnt entire concepts in depth, so much so that now I am confident enough to be able to make something for any use case.
What I learned
In the development process I learnt a lot about the futuristic developer friendly cloud services available out there. REST APIs, GET, POST methods were extremely important for the project. My interest in learning Machine Learning technologies for higher studies was also boosted while trying to employ AI/ML for user utilities. I also understood the importance of UI design and enhancement of user-experience for a utility to be effective, whatever be the feature involved. A developer needs to put himself/herself in the target user's shoes, which, in my case, is every human being on this planet.
What's next for Lazarus
With human voice support and Machine Learning, the above Daily Log feature can monitor physical and mental health of user all year round and provide personalized guidance for health issues, even beyond the current pandemic. The app, thus never loses its purpose. Voice support and multi-user support can also make use of the app easier for people with visual or other physical disabilities, that make smartphone use difficult.
We also intend to implement a social media platform which will take up the health issues the users are facing (as evaluated in Daily Log feature) and post them anonymously for other users to view and users who have been verified as medical practitioners can offer suggestions. The suggestions relevant to a user will show up in his/her feed with the qualifications of the practitioner offering the suggestion. Thus the user receives honest medical advice which is not always guaranteed in paid visits where the doctor’s or hospitals’ vested interests can allow for misguidance and foul play.
Built With
azure
dart
flutter
google-cloud
luis
Try it out
github.com | Lazarus | Mobile application for contact tracing even without BLE eliminating need for one phone per user. The user can also speak to the app, while it filters health data and guides user accordingly. | ['Kazi Masudur Rahaman'] | [] | ['azure', 'dart', 'flutter', 'google-cloud', 'luis'] | 13 |
10,346 | https://devpost.com/software/mentr-me | Inspiration
To help others during this covid crises
Built With
bootstrap
css
flask
html5 | Mentorship | Mentorship | ['Anagha Sivadas', 'Gayathri Venu'] | [] | ['bootstrap', 'css', 'flask', 'html5'] | 14 |
10,346 | https://devpost.com/software/remo-remote-interview-assist-eolbui | Inspiration
Work from home has become the new normal, how would interview from home sound ? REMO aims at providing an intergrated platform for facilitating the conduction of online interviews. That is where we took inspiration from.
Built With
css
html
javascript | Interview | make interviews easy | ['Namya LG'] | [] | ['css', 'html', 'javascript'] | 15 |
10,346 | https://devpost.com/software/talklang | Inspiration
I love watching KPOP, Always been a huge Fan (Army) of them, but as they speak Korean I always have to wait for the English subtitles and also the real meaning somehow gets lost in the translation so I felt if there can be a way to talk to native Korean speakers and learn their language through a video call from the ease of my home.
What it does
TalkLang is a global language learning app (Android and iOS) that connects students and teachers for 1-on-1 online language lessons. At TalkLang, we believe that human interaction and cultural sharing are the best way to become fluent in a foreign language. Just go through the list of teachers, check their profiles and if you like their profile you can book a meeting with them.
How I built it
It is built using Flutter and Agora. Expressive UI is a very important part of an app it can turn potential visitors to buyers as it facilitates interactions between the user and you're application, so we choose Flutter which not only gives you the freedom to make beautiful UI but also helps you cater to both Android and iOS markets while keeping developers happy with its features like HOT Reload.
Agora was our primary choice while we thought of integrating video calls, it's super easy and fast to integrate with the app.
Challenges I ran into
One of the major challenges was integrating live transcription, which broke at the last moment so couldn't include that feature in the current apk but will surely be there in our future versions
Accomplishments that I'm proud of
It has a beautiful UI starting from the bottom navigation bar, the app looks awesome and more importantly, we have made it keeping all mobile sizes in mind.
What I learned
I learned a lot about making apps that can work seamlessly on different devices of varying screen sizes and also a lot about Agora and Flutter
What's next for TalkLang
Planning to launch on play and apple store.
Built With
agora
flutter
Try it out
github.com | TalkLang | An online education and training platform designed to teach various languages with the help of video sessions. | ['Harsh Agarwal'] | [] | ['agora', 'flutter'] | 16 |
10,346 | https://devpost.com/software/here-for-you-ducsx3 | Inspiration
Mental health is much more important than physical health always, When i started thinking of a idea for topic social good i came across many but one thing that i believed and was fascinated by was helping or changing individual's situation and by making it better sure the whole society will be filled in with goodness. As there is a proved "A small drop of water can make up a mighty ocean".
What it does
The Alexa skill takes in answers for five questions from the user and checks for the user's mental health by analyzing the answers and informs them whether they need to take medication for their mental health or not.
How I built it
The skill was made with javascript in amazon developer console making it compatible to answer whatever the user speaks.
Challenges I ran into
Skill-building was comparatively much easier compared to the ideation phase I went through. Apart from that result calculation part and Utterance conflicts in the Alexa developer console seemed to a little heck of problems.
Accomplishments that I'm proud of
I am so happy to make this skill which will bring goodness to society and individuals by helping with their mental health and making it easier for them as voice-based rather than pen and paper.
What's next for Here-For-You
The skill will be made enabled to have different types of mental test for different mental problems like a stress test, dementia test, etc. We will also improve to give mental cure related advice.
Built With
amazon-alexa
javascript
Try it out
github.com | Here-For-You | Mentally healthy is as equal as being 100x physically healthy | [] | [] | ['amazon-alexa', 'javascript'] | 17 |
10,346 | https://devpost.com/software/c-care-17qgih | Inspiration
During this current COVID 19 pandemic, I see health workers and doctors are curing the patients, the police are controlling the crowd movement and even bus drivers are helping people to get back home. As a future engineer, I felt like my contribution is none, this is what motivated me 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 statement
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? Also in this COVID-19 people, morale is down, we have to boost people's moral otherwise we can't win this fight against COVID-19. The size our product is huge and if it gets successful it will create a measurable positive impact in India.
Solution in brief
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. 2nd important feature is the NEWS feed, our app has a news feed system where users will find only the +ve news that is being ignored by the TV and social media, that +ve news will create a placebo effect among the user making them optimistic and mentally strong.
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
We’re proud to have completed our project in the period of HACKS4HUMANITY. Additionally, we’re proud of how we’ve dealt with time pressure and worked cohesively as a team to actualize our start-up goals, which we believe would have a genuinely positive impact on saving many lives once implemented properly.
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 any 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
geofencing
google-maps
java
sqlite
Try it out
github.com | C care | An app that keeps you protected physically and psychologically from COVID - 19 | ['Anup Paikaray', 'Arnab Paikaray'] | [] | ['android-studio', 'geofencing', 'google-maps', 'java', 'sqlite'] | 18 |
10,346 | https://devpost.com/software/virago_code-029c78 | Drawer section of features
PCOS diagnosis
PCOS diagnosis
Health Insights
Health Insights
PCOS Health Assistant
PCOS Health Assistant
Social Impact!
Inspiration
PCOS(Polycystic Ovary Syndrome) is a hormonal & metabolic disorder affecting
1 out of every 5 women
of reproductive age (16-40) in India and 116 million women worldwide. It's listed among the
most common diseases you haven't heard of
due to the
social stigma
associated with it.
Education and awareness about PCOS cure
is a crucial problem to be solved along with
no reach to the right expertise and support for PCOS, also the misconceptions that follow in PCOS
.
One of our team members, who herself went through PCOS
and reversed it successfully stands as an advocate for PCOS Education. Through our
social health-tech initiative
PCOS Virago we aim to
educate women with PCOS, emotionally and morally support scared/helpless teenagers & women with PCOS, diagnosis for PCOS & help with mental health issues for women with PCOS
. There isn't any application/service which caters to the need of women with PCOS and hence in this hackathon, we started developing the
first-ever app for women with PCOS
. We believe through this we will be able to support women with PCOS, give them access to PCOS related services,
use technology to leverage innovative features, change people's lives, and create a social impact!
What it does
We listed the common problems faced by women with PCOS and came up with 8 innovative features to how technology can help women with PCOS!
It's an all in one app which helps women to perform a basic PCOS diagnosis (detects whether you have PCOS), know the type of PCOS (advanced quiz based on the dataset), enroll themselves in the PCOS Lifestyle Programs with the PCOS health experts team, join support groups like PCOS Virago Community for emotional and moral support for mental health issues with PCOS, track daily lifestyle & fitness changes. It also includes features like health insights (blogs, podcasts, videos, courses) for PCOS & fertility education, period tracker and ovulation calendar as well as a PCOS Chatbot for assisting with basic info.
How we built it
Once the user registers on our app, we lead her to the
4-item questionnaire
for use in the diagnosis of PCOS; the questionnaire yielded a sensitivity of 85% and a specificity of 85% on multivariate logistic regression and a sensitivity of 77% and a specificity of 94% developed by referring to
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1949220/
.
It later asks for
advanced user details
which will help in finding the type of PCOS the user is suffering from (stress-induced, obese PCOS, thyroid PCOS, etc) using
https://www.kaggle.com/prasoonkottarathil/polycystic-ovary-syndrome-pcos?select=PCOS_data_without_infertility.xlsx
dataset.
The app includes a
PCOS health assistant
for educating users about the basic info and misconceptions of PCOS wherein we trained the chatbot using Dialogflow and integrated it with Flutter.
We prepared a
community chat group
using Flutter and Cloud Firestore for supporting women with PCOS
The
health insights
sections include access to resources like blogs, podcasts, and videos for PCOS education wherein we linked it to the blogs present on the PCOS Virago website written by PCOS health experts
We plan to implement the
period tracker and ovulation
calendar using API's, fitness tools using fitness API like Google Fit, and an interface to connect to PCOS experts and reversal programs.
Challenges we ran into
Implementing the questionnaire to give the most accurate results for the PCOS diagnosis quiz, obtaining a good dataset for the type of PCOS quiz. But we are glad we could make through them (lost a few hours of sleep though!)
Accomplishments that we're proud of
We could implement the PCOS diagnosis quiz finally! We also found the dataset and analyzed it to develop a type of PCOS quiz later on. We finished 4 out of the 8 features planned in the last 2 days, which itself was a milestone given that we working on something that doesn't exist and we had to do everything from scratch - that too remotely!
What we learned
Logic implementation for the PCOS diagnosis quiz, analyzing the dataset for the type of PCOS quiz, integrating Dialogflow, language model, and training it with PCOS data, flutter state management. Also, that passion and hard work can solve problems for the world!
What's next for Virago_Code
Implementing the remaining 4 features( although the logic and technology stack has been thought well over by us) and making it scalable enough for users to access this wonderful app.
Built With
android-studio
cloud-firestore
dart
dialogflow
firebase-auth
flutter-sdk
python
Try it out
github.com
pcosvirago.in
docs.google.com
drive.google.com
www.instagram.com | PCOS Health, PCOS Awareness & PCOS Support | First-ever all in one app for women diagnosed with Polycystic Ovary Syndrome (PCOS) | ['Anushka Bhave', 'Sakshi Oswal'] | [] | ['android-studio', 'cloud-firestore', 'dart', 'dialogflow', 'firebase-auth', 'flutter-sdk', 'python'] | 19 |
10,346 | https://devpost.com/software/store-of-tomorrow | Built With
html5 | ***** | ***** | ['Tripti Saloni', 'Eksha Singh', 'Anusha Nigam'] | [] | ['html5'] | 20 |
10,346 | https://devpost.com/software/self-tutor-53ohcm | Inspiration
Help people with no access to education, educate themselves.
What it does
Identifies the objects shown to it, counts the number of objects and spells them out. This helps the illiterate person learn how to count, identify and learn the alphabet through spellings.
Displays a series of images of alphabets on screen and asks the person to identify it. Also tells whether the identification is correct or not.
Speaks an alphabet for the user to write it on the paper, captures the image of the alphabet and checks whether it matches with the asked alphabet or not.
Helps the person to read a book by taking in the image of the captured page of the book and reading it aloud.
How I built it
The front end was entirely made using pySimpleGUI. YOLO was used as object detection system. Pyttsx3 was used for text to audio and google sound API was used for audio to text.
Challenges I ran into
This was my first time working with pysimplegui. Designing multiple windows through master slave architecture was a challenge. Apart from that getting speech to text conversion API work was also a tough task as the application crashed everytime it was used but the issue was solved at the end.
Accomplishments that I'm proud of
I am proud of bringing my idea to life in a given period of time and experimenting with new technologies.
What's next for Self Tutor
Support for other languages can be added Other interactive teaching methodologies can be added.
Built With
google-speach-api
pillow
pysimplegui
pytesseract
python
pytssx
Try it out
github.com | Self tutor | Groups of illiterate people who have no access to educators can educate themselves using Self tutor. It helps them to read and write and use the resources provided to them. | [] | [] | ['google-speach-api', 'pillow', 'pysimplegui', 'pytesseract', 'python', 'pytssx'] | 21 |
10,346 | https://devpost.com/software/fundit-nqtog9 | Login
Business Description
Highlights
Payments
fundIt
A platform that democratizes access to capital for small businesses via crowdfunding
Inspiration
Startups founders don't have those connections or profits to get funding and especially in a year full of uncertainties many big investors are scared to invest in small businesses. And not all startups makes million dollars in their beginning years.
Meanwhile, most people are not as rich but want to invest. So we want to build a platform that benefits color businesses (because majority of them are quite small) and Investors both. Startups put their video pitches to help make investor a decision on the startup and investor can make an appointment with the business to know about their future goals before investing.
What it does
fundIt is a an app for small businesses to get crowdfunding by retail investors for equity.
Users can login and authenticate their credentials via Apple/Google/Email
Startups can post data such as PDFs, Images, and Text to supplement their crowdfunding campaign and help investors to make investment decisions
Investors can browse all campaigns via a Tab view
The most unique feature of this platform is the highlighted businesses of the month. Underrepresentation and discrimination is a huge problem in business investments so we want to represent those businesses by having a separate page for them.
Investors can schedule a virtual meeting with the representative of startup that will help investor know about the future plans of the business
Investors can pay as little as $10 for a share in the startup’s equity offered in the crowdfunding campaign
Investors can view their past investments & their total investments on a profile view
Startups can checkout the funds raised from the crowdsourced campaign via Apple/Google Pay to Apple/Google Wallets in a virtual FundIt card
How I built it
Flutter: Dynamic Mobile Applications that runs both on Android and iOS.
Firebase: For authentication
Square: Payment Processing
SQL: For storing the Business and Investor Information
UiPath: For automating the process for investors displaying startups according to their search history
Potential Users
Retail investors - who will be investing in the companies that are listed on our platform
Startups - they sign up for crowdfunding in exchange for equity.
Challenges I ran into
Payment Processing using Square
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
sqaure
Try it out
github.com | fundIt | A platform that democratizes access to capital for small businesses via crowdfunding | ['Sulbha Aggarwal', 'Rishav Raj Jain', 'Rupakshi Aggarwal'] | [] | ['dart', 'firebase', 'flutter', 'sqaure'] | 22 |
10,346 | https://devpost.com/software/sahaaya-making-web-accessible-to-everyone | Inspiration
The inspiration came from my friend who was dyslexic and that's why it was hard for him to read text on browser
What it does
Sahaaya is browser extension that changes the appearence of the entire web based on your design customizations and preferences. It’s especially helpful for people with dyslexia, because it comes built-in with an option that adjusts the color-contrast ratio and typography. We provide a huge variety of color contrast schemes with different font styles so that every user can adapt to his/her preferences.
How I built it
I build this app using chrome APIs to manipulate web pages to change their color contrast and typography according to the preferences
Challenges I ran into
The greatest challanges I faced in this project to manipulate DOM of external websites that too using a chrome extension
Accomplishments that I'm proud of
I was able to make this project in such a short time(4 days) and I am really proud of what I have accomplished in such a short time
What I learned
I really mastered DOM manipulation after using it so extensively in this project and got a really in depth understanding of how Chrome extensions and APIs work
What's next for Sahaaya - Making web accessible to everyone
I want to add Text to speech feature in this extension to also include auditory challenged people
Built With
chrome
css3
html5
javascript
webstore
Try it out
github.com | Sahaaya - Making web accessible to everyone | Sahaaya is a chrome extension that helps people with visual and learning disorder read on the web. | ['Shivansh Yadav'] | [] | ['chrome', 'css3', 'html5', 'javascript', 'webstore'] | 23 |
10,346 | https://devpost.com/software/greenar-ar3kg0 | Inspiration
How often do we realize that we have so much empty space around us which belongs to nature and that we can help revive our mother earth but a small step- Planting more trees and making the earth a little more greener? However, growing a tree is a long process and thus visualizing the final result of it excites us! GreenAR is all about this!
What it does
GreenAR lets you visualize Virtual plants and trees in your Garden/Backyard or elsewhere, you can plant up to 25 trees and 25 plants (5 of each type) at different positions. Thus you can visualize the final results of planting a tree and that certainly excites any nature lover. If you do not have enough space for a large tree, you can visualize smaller pots and plants as well.
How I built it
It started with collecting as well as creating some 3D models. All these 3D Models are extremely low poly and use materials instead of textures so that more and more options could be provided. The UI starts with basic Instructions for User, followed by a canvas option for Plants or trees All this using Object Tap. The first issue was that the plant to grow wherever the user drags the arrow to and stop following it after that. Achieved this using patch editor to initially keep the visibility of all 3d models of plants and trees off and follow the drag. Once the button of the plant/tree is pressed, its visibility is turned on, its size is increased from 0,0,0 to 1,1,1 to give a feel of growing and most importantly its screen drag patch is disabled to it stays wherever planted.
A similar patch is created for each and every plant/tree. Thus it enables the user to visualize multiple trees at different positions. This supports up to 25 trees and 25 plants ( 5 of each type) and still not much heavy on the device due to low size. All the trees will have some facts and figures written about them on a separate canvas. Here is a look at the patch's arrangement. Credit for 3d models
Challenges I ran into
1.Couldn't Find a way to dynamically instantiate copies of plants 2.Planting a tree and then stop its drag
Decreasing the size of the lens within limits to improve lens engagement
Accomplishments that I'm proud of
My first experience with the Patch editor which I feared for a few months is over, and it is awesome! I am pretty sure I have got a ton of ideas to implement this summer vacation.
What I learned
It was a great experience to learn to implement logics and calculations using patches and improved my 3D modeling skills. While building this lens in the last two weeks I came across a lot of small and big issues that will definitely help me in my future projects on SparkAR.
What's next for GreenAR World
It was a great experience to learn to implement logics and calculations using patches and improved my 3D modeling skills. While building this lens in the last two weeks I came across a lot of small and big issues that will definitely help me in my future projects on SparkAR.
Built With
blender
photoshop
sparkar
Try it out
github.com | GreenAR | One small step to GreenAR world | [] | [] | ['blender', 'photoshop', 'sparkar'] | 24 |
10,346 | https://devpost.com/software/my-therapist-app | The LOGO
Ever since the world entered the pandemic year, it is not unknown, that the mental and emotional health of humans all around the globe has taken a toll.
More and more people are coming out confessing that they are depressed or emotionally stressed out.
How mental illnesses and emotional imbalances are recieved and treated varies dratically from one society to another.
Whereas posh societies have easy and quick access to help, in forms of psychologist and psychotherapists, the middle class and the lower class continues to suffer. In middle and lower class societies, there is still a taboo and stigma attached to mental and emotional illness. People do not acknowledge this illness, let alone seek treatment. In such conditions, would it not be revolutionary to have a platform that would
enable anyone, anywhere suffering mental, emotional challenges and wanting help to connect to psychologists through just a click on their mobile phones?
My Therapist App is designed to be a single platform for people to choose from a range of available psychologists and therapists and book online and/or offline sessions through just a click!
The aim behind My Therapist App is to make therapy and psychological aid easily accessible to people suffering from anxiety, stress and depression.
The app is built with Flutter App framework.
We aim to use 'AI for detection of depressions in people using their social media posts' techniques and help people who are unaware of their possible mental or emotional imbalance. We want to include 'gift a session' facility in our app so that people can gift psychotherapy sessions to their needy friends and family and help them.
Built With
dart
firebase
flutter
Try it out
github.com
youtu.be | My Therapist App | My Therapist App is designed to be a single platform for people to choose from a range of available psychologists and therapists and book online and/or offline sessions through just a click. | ['Mahe Iram Khan', 'Musheer Ahmad'] | [] | ['dart', 'firebase', 'flutter'] | 25 |
10,346 | https://devpost.com/software/aadhaar | .
Built With
html | . | . | [] | [] | ['html'] | 26 |
10,346 | https://devpost.com/software/voice-shop-voice-enabled-shopping-assistant | Inspiration
The day to day process of navigating to websites and then adding products to the cart is time-consuming. So We thought of making a voice-enabled shopping assistant which can search and add products to the cart just with a voice command.
What it does
It can search and add products to the cart just with a voice command. It is also capable of performing a day-to-day activity such as playing music, opening applications, etc
How I built it
We have built it in python using the selenium library and performing web automation
Challenges I ran into
Web automation was really tough
Accomplishments that I'm proud of
The final product which performs on voice command is an accomplishment.
What I learned
I have learned many new skills like web automation, python libraries, etc
What's next for Voice Shop - Voice-enabled Shopping Assistant
Built With
python
selenium
Try it out
github.com | Voice Shop - Voice-enabled Shopping Assistant | A daily use voice enabled shopping assistant | ['Esha Goel', 'Vidhi Garg'] | ['Best Voice Project'] | ['python', 'selenium'] | 27 |
10,346 | https://devpost.com/software/byeciggy | Launch Screen
Intro Screen
Detail retrieval.
Program selection.
Progress.
Inspiration
An individual's ability to contribute to social good comes from a place of availability of secondary resources to spare. While it might be financially clenching for majority people to donate for a cause, it is easier to loosen up a fraction of their needless expenses on a daily basis, slowly. This experience can be gratifying and a step towards improved quality of life. This idea births from the common practice at retail stores where small donations are collected from shoppers for a noble cause.
What it does
User can input his/her approximate details of daily tobacco consumption.
User choose how much of your current tobacco consumption should be converted into savings.
Everytime the user has a craving to smoke, he/she can either decide to smoke or save that money for a cause (social/personal)
How I built it
I have learning Swift for a couple of weeks now. I came across this Hackathon and decided to build an application.
I used XCode as the IDE to develop and simulate the Swift code for iOS application. I used Canva for generating icons and images for the UI/UX.
Challenges I ran into
Since I am not a designer by experience, I struggled with the UX. Additionally, this application needs to be partnered with an online-wallet so as to enable immediate money transactions.
Accomplishments that I'm proud of
I am very happy with the idea itself and I can see major directions of growth for this application that can be put to use for both personal and social causes.
What's next for ByeCiggy
In the current time of rising health issues and worldwide shortage of resources, ByeCiggy can bring all charitable organizations at your fingertip and let you feel kind while you feel healthy. Partnering with banks, wallets and charity centers, ByeCiggy can revolutionize societal health at micro-level leading to grand results.
Built With
swift
uikit
Try it out
github.com | ByeCiggy | Helps you convert your tobacco indulgence into goodwill. | ['Shruti Biswal'] | [] | ['swift', 'uikit'] | 28 |
10,346 | https://devpost.com/software/q-minds | Activity Pinwheel
Home Page
Past Accomplishments
Inspiration
A lot of my friends and family members struggled with being productive during the quarantine days. They got tired of doing the same thing everyday: scrolling and sleeping. This was not only making them bored but was affecting their mental health negatively. I decided to build something easy-to-use where they can find fun activities and connect with others in the same boat!
What it does
Q-Minds gives the user suggestions for what to do during the day. Completing one small task per day makes the users feel productive and energized. The 'star' reward system and posts from friends help keep people motivated.
The short term effects: Entertainment, Sanity in quarantine, Active Mind.
The long term benefits: Healthier habits, Will to stay active and and productive, new skills acquired.
How I built it
I used an HTML template from html5Up and then changed it to the design I wanted. I had some HTML/CSS knowledge, so I was able to make the changes. I didn't know JS so I tried to look up ideas for building a pinwheel in JS and found some helpful resources.
Challenges I ran into
I had some issues with margins and positioning of my wheel and the text associated with it. I was having trouble with the video length so I decided to use a text-to-language tool to make the pitch more concise and clear.
Accomplishments that I'm proud of
This is my first hackathon without a team. I am glad that I have enough confidence now to design and develop a product all on my own. Also, this is my first virtual hack and I feel prepared to participate in more. The thing I am most proud of is that I made something related to mental health, a topic that often gets neglected in technology.
What's next for Q-Minds
I will develop a log in and sign in platform. There will also be communities and friends groups for folks to stay motivated. Some sort of ML methods to suggest tasks that users will enjoy based on their previous completed tasks will be great.
Built With
css3
html5
javascript
visual-studio
Try it out
github.com | Q-Minds | 'Q-Minds' helps people in quarantine improve their mental health by engaging in interesting activities daily. | ['Noor Fatima'] | [] | ['css3', 'html5', 'javascript', 'visual-studio'] | 29 |
10,346 | https://devpost.com/software/covid19-care | Inspiration
coming soon...
What it does
How we built it
Challenges we ran into
Accomplishments that we're proud of
What we learned
What's next forC-care
Built With
html | C-Care | Waste care | [] | [] | ['html'] | 30 |
10,346 | https://devpost.com/software/justicecoin-w5ym9z | Monero Ledger
Built With
sol | Veracoin | Monero Ledger | ['Pratyush Mallick', 'MyLinh Murphree'] | ['Best Overall Hack'] | ['sol'] | 31 |
10,347 | https://devpost.com/software/threat-detection-automation-in-it-ot-converged-networks | Lab setup
Workplan Full view
Inspiration
We see more and more IT-OT converged networks, as manufacturing and critical infrastructure organizations try to achieve their digital transformation goals. These converged networks increase the attack surface by exposing the OT environment to always connected internet accessible networks against the traditional well controlled (sometimes separated by an air gap) OT network boundaries. Over the last few years we have seen some targeted attacks intentionally using the IT environment as a pivot point to enter OT networks to achieve their objective but most of the time incidents are generated by threats built to target IT environments, unintentionally impacting OT networks. There are fundamental differences between handling an IT security alert vs OT security alert, where IT world focuses on confidentiality/Integrity while OT world’s main focus being availability. Although there are lot of differences between IT & OT worlds in many ways such as CIA priority and protocols used, more and more fusion SOCs are being built to monitor these converged networks for threats and compliance.
What it does
Primary challenge is to correlate the alerts generated by both IT and OT point security products, identify the malwares that could have moved across IT-OT boundary impacting the critical OT assets and contain them preventing further damage to the organization in a structured manner. Secondary challenge being optimizing the analyst efforts spent on manually gathering, enriching indicators and evidence.
How I built it
We built a virtual lab to replicate the IT OT environment completed with
Firewalls : Palo Alto Firewall, Fortigate Firewall
IPS/IDS : Firepower (IT), Nozumi (OT)
Servers : Active Directory, MS Exchange
Log Server : Splunk
SOAR : XSOAR
Targets : IT PC, Human Machine Interface PC, simulated PLC
After studying the clients existing threat detection process, we reengineered the process to include additional log/alert sources that could add value. We managed to streamline and automate the enrichment, event driven threat hunting, containment and notification.
Challenges I ran into
This was our first attempt to build a playbook using a SOAR technology, let alone XSOAR. We learnt new things everytime when we run into a problem whether its an integration issue, playbook input output issue, transforming splunk raw logs or mapping them to XSOAR as jason value pairs. However at the end of the process we are highly satisfied knowing we have grasped lot of knowledge, tips and tricks and thought process required to design and build future automation & orchestration projects.
Accomplishments that I'm proud of
Complete IT-OT lab setup, Having a solution to over achieve client's MTTD & MTTR expectations. Most of all completing the 1st XSOAR playbook and it's ALIVE!!!
What I learned
Thought process was the most important one, is there a better way, have someone already found a way to do this more efficiently, how much of a unique solution is required to solve my problem, can I use existing automations and playbooks to optimize my playbook. other than XSOAR engineering tasks, I've also learnt great deal about Nozumi, splunk, JSON
What's next for Threat Detection Automation in IT OT converged Networks
Built With
xsoar
Try it out
github.com | Threat Detection Automation in IT OT converged Networks | Automating and optimizing an existing threat detection process in an IT OT converged network | ['Weranga Kumaradasa'] | ['Best Security Playbook'] | ['xsoar'] | 0 |
10,347 | https://devpost.com/software/slashnext-playbook | SlashNext Cloud reports the URL to be malicious and the playbook determines it to be targeting the HMRC brand
Automate Online Brand Protection to Take Down More Malicious Brand Content in Less Time
Attempts to fraudulently use or impersonate a brand is an extensive and severe problem for brands. Most brands have abuse inboxes for the public to report suspicious communications. This is a complex and manual operation for global brands that require brand protection teams to sort through thousands of malicious and benign emails daily, gather forensics evidence, and send take-down requests to the domain or other organizations hosting the malicious content.
This playbook fully automates the process of reviewing the emails sent by customers and the public to online brand abuse inboxes. It detects brand impersonators and malicious URLs using deep inspection of website content and packages everything required to request a take-down (IOCs, forensics, and screenshots) into an email sent to the abuse department to simply forward to the domain registrar.
This playbook leverages SlashNext’s threat detection technology that uses mature machine learning (computer vision, NLP, and OCR) and virtual browsers to dynamically inspect page and server behavior with 99.07% accuracy. This speeds-up the process of taking down malicious sites targeting your organization right now and in the past. With this playbook, teams will save hundreds of hours spent per week managing corporate brand abuse inboxes.
Playbook’s main steps
Extract URL from the reported email
Take snapshot of the email
Request real-time scan through SlashNext SEER Cloud (to be analyzed by a virtual browser)
Download URL Scan Report including website screenshot, HTML and rendered text
Log evidence
Perform a deep inspection of the HTML to find If Phishing URL is targeting the Brand
Forensic Analysis says Yes
Get domain Whois information
Prepare complete evidence to be shared with hosting providers and domains registrars (includes URLs, phishing email and website screenshots)
Dispatch a take-down email to concerned abuse department
Close incident
Built With
api
playbook
Try it out
github.com | SlashNext Online Brand Protection Detect & Respond Playbook | Fully automates the online brand abuse inboxes to detects brand impersonators & malicious URLs using deep inspection & packages required for take down proof (IOCs, forensics, & screenshots) | ["Lisa O'Reilly"] | ['Runner Up Security Playbook'] | ['api', 'playbook'] | 1 |
10,347 | https://devpost.com/software/securehealth | Inspiration
Currently, I work in the medical device industry creating products that make medical imaging capabilities available to everyone. The medical landscape is changing. And where healthcare can happen will transition from point of care to point of care everywhere. With devices like mobile phones and smart watches and portable imaging devices. That means an attack surface that will increase exponentially. SecureHealth is a POC to protect health networks from compromise that could bring down an entire network of health services with fatal consequences.
What it does
Devices provisioned and controlled through SecureHealth can be monitored through the XSOAR SecureHealth integration, possibly using PAN's AppID technology. When anomolous activity is detected the system creates an incident using Google Chronicle to automatically prepare related information that allows the analyst to escalate the situation and allow SecureHealth to automatically unprovision the device and protect the rest of the network.
How I built it
The integration is built with python connecting to SecureHealth services (some simulated for lack of PAN hardware).
Challenges I ran into
Access to PAN hardware
Accomplishments that I'm proud of
What I learned
What's next for SecureHealth
Onboard the first devices
Built With
mobile
node.js
python | SecureHealth | Next Generation Security Management for the Next Generation of Everywhere Health Devices | ['seth piezas'] | ['Best Palo Alto Networks Product Integration Playbook'] | ['mobile', 'node.js', 'python'] | 2 |
10,347 | https://devpost.com/software/aws-ec2-prisma-and-xdr | Reduce non-compliance with Prisma, EC2 and XDR combination
what does not work
the AWS EC2 - remove security group command - seems like even when the "security group" is provided, it tries to work on all security groups (not just the security group provided). I am trying to work on a custom integration which can solve this problem
Built With
xsoar | AWS EC2 - Prisma and XDR | Reduce non-compliance with Prisma, EC2 and XDR combination | ['Manoj Verma'] | ['Runner Up Palo Alto Networks Product Integration Playbook'] | ['xsoar'] | 3 |
10,347 | https://devpost.com/software/serge-s-placeholder-submission | When I was introduced to the Demisto playbook editor the first thing had to say was WOW, Demisto has made security automation as easy as Visio. The second thing I had to say was, damn I wish I had this for Ansible!
IT Operations has always had scripting and point solutions for specific use cases, but low-code platforms for IT Operations that tied together significant portians of the IT Infrastructure are non-existent. Innovations in IT automation have brought us fantastic tools to our warchests like Ansible, Terraform, and Chef, but these aren't necessarily making things easier for general purpose system administrators. They all require non-insignificant investments of time and study before yielding value. It's not surprising that products like ServiceNow that are bridging the gap are extremely popular.
One of the automation tools that I'm intimately familiar with is Ansible. Ansible has a mild barrier to entry and a steep learning curve to mastery, as their playbooks are written entirely in a declarative markup language with YAML, and has limited ability to perform if/then/else logic. It's meant to be declarative of desired end state with the modules determining how to get there. There is no graphical interface, or easy drag/drop workflow engine like we do in XSOAR. Many first time users see Ansible playbook development akin to programming and quickly give up. Similarly those that don't often struggle to have Ansible interact with regular users, as it doesn't have anything remotely like XSOAR's friendly user interface, data collection or reporting capabilities. It is a tool for automation engineers.
My submission is not just a XSOAR playbook, but in fact a set additional integrations that supercharge XSOAR using Ansible modules. This opens up the possibilities for many more use cases in XSOAR by filling in the gaps required for IT infrastructure operations. I like the Desolvable Host Agents in XSOAR, but they don't compare to the power of Ansible's Modules and their agentless functionality. The integrations I have written my be powered by Ansible and run on the XSOAR server itself, but are first class citizens within XSOAR with high quality command documentation, argument options, context outputs, and importantly performance and scaling. If you didn't look under the covers of the Python code, you would not know that you are using the Ansible engine at all. There is no markup or scripting to be found, and credential management for access to systems by these integrations is done with the native XSOAR platform. I have seamlessly woven the two together, giving you the power and integration breadth of Ansible within XSOAR without any addition servers or components outside of the XSOAR engine itself. You easily use my added commands just the same as any other XSOAR integration.
The gaps I have filled cover the following areas:
Windows and Linux host management
Cisco Routing and Switching
Certificate and DNS management
Control over Kubernetes
VMware vSphere Virtualisation
Improved Azure Integration
Hetzner Cloud
Alibaba Cloud
In total I have added 13 integrations and over 500 commands.
I have provided a demonstration playbook that shows the usage of the Windows host integrations in conjunction with the rich existing XSOAR functionality, in ways that would not be possible by using only XSOAR, or Ansible on it's own.
This playbook follow the SOAR philosophy of enabling an non-subject matter expert to execute a complicated procedure with protective guardrails to ensure their success.
Please note the integrations require my Ansible-Runner container to function. My PR is still in the process of being accepted:
https://github.com/demisto/dockerfiles/pull/2772
In lieu of this container image being available you can generate the required image using the following XSOAR command:
/docker_image_create name=ansible-runner dependencies=ansible-runner,paramiko,ansible==2.9.12,psutil,ssh_agent_setup,pywinrm>=0.2.2,requests-ntlm,hcloud>=1.0.0,pyvmomi,openshift>=0.6,pyyaml>=3.11,azure-mgmt-compute,azure-mgmt-storage,azure-mgmt-resource,azure-mgmt-network,dnspython,footmark>=1.1.16 packages=gcc,linux-libc-dev,libc6-dev,sshpass,openssh-client
Built With
ansible
containers
python | 1+1 = 3 Supercharging XSOAR with Ansible | XSOAR is the perfect No Code platform for IT Operations... | ['Serge Bakharev'] | ['Best Business Use Case Playbook', 'Customer Choice'] | ['ansible', 'containers', 'python'] | 4 |
10,347 | https://devpost.com/software/temp-account-management-for-external-parties | Playbook Overview
Inspiration
Account management for external parties has been one of the the most headache tasks in my daily work. There are always vendors that would like connecting our environments for setting up stuffs, and setting up these accounts take a lot of time and effort because of the high amount of such request.
What it does
The playbook reads CSV file containing list of temp accounts' Username and Account Effective Period, then schedule related tasks on XSOAR.
How I built it
Mainly using ParseCSV and OOTB AD Integration with little python script to glue things together
Challenges I ran into
Schedule task on XSOAR requires cron job to be created, that the time format on cron may not be understandable by non-technical team.
Accomplishments that I'm proud of
Created a little python script that convert "normal" time format to cron job, and glue the pieces together to build a small but effective playbook that actually solves the issue we encountered.
What I learned
How to automate tasks and handle information flow effectively.
What's next for Temp Account Management for External Parties
Enhance the playbook with better error handling and more file format support.
Built With
python
Try it out
github.com | Temp Account Management for External Parties | Scheduled account creation and deletion on Active Directory using CSV files | ['Apple Li'] | ['Runner Up Business Use Case Playbook'] | ['python'] | 5 |
10,347 | https://devpost.com/software/aws-security-hub-starter-pack | Starter Pack
Inspiration
Take a cloud native app with autoscalling groups and automatically remediate a compromised instance.
What it does
Classifies Security Hub Incidents and maps the fields to an xSOAR instance. Handles instances in an autoscalling group and fetches processes from Systems Manager. Removes compromised instances and has the autoscalling group create new ones.
Built With
ec2
guardduty
lambda
python
securityhub
Try it out
github.com | AWS Security Hub | Starter Pack | Get up and running faster with this AWS Starter pack. Contains Classifiers and Mappers to get you going. Also contains example playbooks to run through your security incidents from GuardDuty | ['Daniel Prince'] | ['Sponsor Prize AWS - Security Hub'] | ['ec2', 'guardduty', 'lambda', 'python', 'securityhub'] | 6 |
10,347 | https://devpost.com/software/aws-compromised-instance-forensics | AWS EC2 Compromise Response
Inspiration
Many SOC's are strapped for well qualified analysts and there is an ever increasing number of detections to respond to and resolve. In my case we were onboarding new AWS responsibilities and to make up for the lack of analysts and AWS experience this playbook was created to streamline the process of responding to Guard Duty alerts by eliminating the initial mitigation as well as the set for the forensic process.
What it does
This playbook is triggered by Guard Duty alerts on network activity. It then moves to block the offending traffic and create a snapshot of the volume which can be converted and attached to a forensic workstation via an EC2 Launch Template.
How I built it
First I started with an issue, namely EC2 instances contacting hosts they shouldn't. I then drafted a playbook on paper that was workable and met our basic needs. Then I worked to transfer it to XSOAR.
Challenges I ran into
XSOAR doesn't have all the EC2 commands available yet to really make this playbook pop in my opinion. In production we ended up modifying the built-in EC2 integration to fit our needs a little more specifically and I expect most clients would probably do the same to some degree or another. As this is outside the scope of this contest I ended up working around these issues and creating a playbook that works well on it's own and meets the basic need of the automation while allowing for room to expand and customize it as necessary.
Accomplishments that I'm proud of
Taking the time out of a busy schedule to better learn the XSOAR platform and apply my AWS knowledge.
What I learned
I had never used the EC2 integration prior to this so I learned the commands which were available and how best to use them as well as how to extend the built-in integrations with custom commands.
What's next for AWS Compromised Instance Forensics
Next is to trial the custom version I have written for our production environment and hopefully get it into mainstream use along side our other playbooks.
Built With
amazon-ec2
amazon-web-services
ec2
xsoar | AWS EC2 Compromise Response | The purpose of this playbook is to define an automated response to Guard Duty alerts indicating malicious traffic either inbound or outbound to an AWS EC2 instance. | ['Thomas Burnette'] | ['Sponsor Prize AWS - Security Hub Runner Up'] | ['amazon-ec2', 'amazon-web-services', 'ec2', 'xsoar'] | 7 |
10,347 | https://devpost.com/software/https-www-youtube-com-watch-v-7k2gm23k03g | Can you detect malicious activities that took place a year ago? How fast?
Built With
python
xsoar | Chronicle threat hunting | Can you detect malicious activities that took place a year ago? How fast? | ['Manoj Verma'] | ['Sponsor Prize Google Chronicle'] | ['python', 'xsoar'] | 8 |
10,347 | https://devpost.com/software/incident-response-pack | Automating CyberOps - one playbook at a time!
Inspiration
The cybersecurity challenge and the opportunity to develop a playbook to solve the problem and be part of the success.
What it does
Helps the incident response teams to automate repetitive tasks of indicator extraction, enrichment , conditional checks and automated response actions based on the results.
How I built it
I used XSOAR hackathon instance and the API integrations
Challenges I ran into
Access to RiskIQ Passivetotal API
Accomplishments that I'm proud of
Successful run of the Playbook :)
What I learned
How to use XSOAR to automate repetitive tasks
What's next for Incident Response Pack
A lot of enhancements that I wasn't able to accomplish during the hackathon duration. I will follow up.
Built With
googlechronicle
ibmqradar
playbook
python
riskiqpassivetotal
scripts
sendemail
xsoar
Try it out
github.com | Incident Response Pack | This Incident Response Playbook can be used by the SOC teams, who need to extract and enrich domain information, perform reputation checks and take response actions based on the results | ['Arpitha Srinivas'] | ['Sponsor Prize Google Chronicle - Runner Up'] | ['googlechronicle', 'ibmqradar', 'playbook', 'python', 'riskiqpassivetotal', 'scripts', 'sendemail', 'xsoar'] | 9 |
10,347 | https://devpost.com/software/make-it-easy | Attacker buys stolen domain names to fool 'domain age' based intelligence, can you still catch them?
A combination of Sixgill, RIskIQ and other tools to build confidence into the investigation.
Built With
python
xsoar | Sixgill stolen domain investigation | Attacker buys stolen domain names to fool 'domain age' based intelligence, can you still catch them? | ['Manoj Verma', 'Upasana Singh', 'Mala Verma'] | ['Sponsor Prize Sixgill'] | ['python', 'xsoar'] | 10 |
10,347 | https://devpost.com/software/sixgill-xsoar-content-pack | Inspiration
The cybersecurity challenge and the opportunity to develop a playbook to solve the problem and be part of the success.
What it does
This XSOAR playbook is configured to run as a time triggered job that periodically adds bad indicators from Sixgill Darkfeed to SIEM blocklist. The playbook further adds a tag to each indicator that is successfully added to the blocklist. Using this tag one can easily identify and filter the indicators that are added to the blocklist.
How I built it
I used XSOAR hackathon instance, XSOAR built in automations and the API integrations
Challenges I ran into
To fetch indicators from Sixgill darkfeed
Accomplishments that I'm proud of
I was able to successfully create and run the Playbook job!!
What I learned
How to use XSOAR playbook , automations, apis to automate repetitive tasks and flows.
What's next for Sixgill XSOAR Content Pack
I will enhance contributions as well as continue to submit more content in future.
Built With
api
playbook
python
pythonscript
sixgill
sixgilldarkfeed
threatintelfeed
threatintelmangement
xsoar
Try it out
github.com | Sixgill XSOAR Content Pack | This XSOAR playbook is configured to run as a time triggered job that periodically adds bad indicators from Sixgill Darkfeed to SIEM blocklist. | ['Arpitha Srinivas'] | ['Sponsor Prize Sixgill - Runner Up'] | ['api', 'playbook', 'python', 'pythonscript', 'sixgill', 'sixgilldarkfeed', 'threatintelfeed', 'threatintelmangement', 'xsoar'] | 11 |
10,347 | https://devpost.com/software/cyber-squatting-detection-with-xsoar | Can we detect cyber squatting and phishing domains to protect our employees and customers with help of XSOAR and freeware tools?
there are many companies which provide cyber squatting detection and brand reputation service. the idea is to create something similar with XSOAR and freeware tools.
The playbook can run as a job. Analyst need to provide few domain names of interest (like org name, primary customers, etc.). which their employees and customer generally visit and provide/store sensitive data. The playbook generates similar names and checks if any website really exists with the name. The domain names are created using algorithms like Levenshtein distance similarity, TLD replacement, typo sensitivity, adding/removing dots and dashes.
next step is to find if that website is genuine or a phishing website. It can be done with help of website content similarity comparison, image comparison, whois searches, domain age history, indicator comparison, and so on.
To help the analyst, machine learning based comparison of website content should be developed.
Based on analysis, result should be stored in a list so that next time analyst need not to investigate a genuine domain which has similar name.
Built With
osint-tools
python
xsoar | Cyber Squatting detection with XSOAR | Can we detect cyber squatting and phishing domains to protect our employees and customers with help of XSOAR and freeware tools? | ['Manoj Verma'] | ['Sponsor Prize RiskIQ'] | ['osint-tools', 'python', 'xsoar'] | 12 |
10,347 | https://devpost.com/software/a-63zxn9 | This playbook utilizes the RiskIQ Passive Total data feeds to investigate suspicious domains.
Built With
python | RiskIQ threat hunting | Whois and passive DNS can be really powerful | ['Manoj Verma', 'Mala Verma', 'Upasana Singh'] | ['Sponsor Prize RiskIQ - Runner Up'] | ['python'] | 13 |
10,347 | https://devpost.com/software/windows-forensics-using-powershell-remoting | Inspiration
DFIR open source tools.
What it does
Allows to capture multiple types of forensic data from a windows hosts without having to install any type of agent. Using native capabilities in Windows such as Winrm, Powershell, Netsh and more.
Once the data is captured it is moved into XSOAR and is parsed and analyzed by multiple tools such as XSOAR PcapMiner, Regipy (A Python library to analyze registry), and many more.
How I built it
Created a Powershell integration that allows to open a remote session to a host. Multiple Python tools such as convert ETL to PCAP, Regipy which is user to parse data and Volatility to parse memory dumps.
Challenges I ran into
Creating a Docker image to support PS remoting without SSH
Developing a new OOTB Powershell integration.
Covering the most critical aspects to focus on within a short time limit.
Accomplishments that I'm proud of
Creating a complete suite of tools for various forensic aspects for acquiring data, retrieving and analyzing.
What I learned
How to implement an agent less DFIR tool suite And best practices for which data to capture. Working with Powershell integrations.
What's next for Windows Forensics Using Powershell Remoting
Improving security to use HTTPS for winrm, provide more commands and playbooks to gather and parse more data. and create a polling mechanisms for Powershell.
Built With
powershell
python
Try it out
github.com | Windows Forensics Using Powershell Remoting | This pack enables you to grab critical forensic evidence from your windows hosts and all of this without having to install any agent and respond in realtime. | ['Dean Arbel', 'EliorKedar', 'erezh31', 'David Baumstien'] | ['Staff Winners'] | ['powershell', 'python'] | 14 |
10,347 | https://devpost.com/software/tidy | Inspiration
It all started from a real-life event that was truly painful for us - the newly recruited developers that had to go a long journey to prepare our workspace and install all necessary software/configurations etc.
What it does
Tidy's integration handles endpoints environment installation from A to Z - and can be customized to fit any role.
What I learned
First and foremost - teamwork. This journey taught us to plan, set goals and to work accordingly. Throughout the process we learned to navigate around the obstacles and make things happen!
What's next for Tidy
A lot more! Tidy can be extended to hold more executions and to allow diverse usages across all departments. Plus, we can build an interactive UI and provide Tidy as a maintained service such that it will also be responsible for repairing broken versions etc.
Built With
ansible
github
goenv
homebrew
nodenv
pyenv
python
zsh | Tidy | Tidy integration handle endpoints environment installation. | ['Gal Rabin', 'Eli Sharf', 'hod Alpert', 'Bar Levy'] | ['Staff Winners'] | ['ansible', 'github', 'goenv', 'homebrew', 'nodenv', 'pyenv', 'python', 'zsh'] | 15 |
10,347 | https://devpost.com/software/sase-content-pack | Use the dashboard to track tenants, metrics and license information
Prisma Access Tenant Provisioning, Automated.
Response playbook for threats detected from Prisma Access customers
Single view of Threat Enrichment, indicators and the original log
Inspiration
Prisma Access customers, especially Service Providers, have to do significant manual work when creating new tenants and remote networks. We decided to join together and build an XSOAR playbook to automate this process. We also believe that XSOAR can automate not only alert response playbooks but also service management and provisioning playbooks. This XSOAR use case resonates with Network Security teams and shows the power of our products working together. We believe that XSOAR can help drive not only process efficiency but also drive more business for the company and our MSSP partners by identifying opportunities.
What it does
Playbook 1 - Prisma Access Multi-Tenant Creation
Automates the provisioning of Prisma Access tenants including remote networks and mobile users.
Integrates with ServiceNow to fetch order information and handle the request.
Service Management Dashboard
Queries and presents live information on Prisma Access service status in an easy to consume dashboard
Shows Prisma Access license information including remaining users and bandwidth in available license and currently provisioned users and bandwidth for each tenant.
Playbook 2 - Prisma Access Threat Response
Automates threat enrichment using Autofocus and PassiveTotal and enhances NGFW security profile threats detected by the Prisma Access firewall by fetching the threat logs from Cortex Data Lake.
Generates sales leads for the XDR/MDR team by escalating customers with recurring infections and threats detected on the network by the Prisma Access NGFW.
How we built it
We started collaborating on the main playbook, relying on Lookman's expertise with Service Providers and Prisma Access to identify the business logic required and built it into XSOAR.
We added more automation to retrieve the service IPs from the Prisma Access SSH integration so we can reduce manual handoffs within the process.
We discussed relevant data and metrics and divided some work to populate this data into our dashboard
We generated some logs through CDL and built a threat enrichment and response playbook to respond to it by changing the policy on the firewall.
Challenges we ran into
Prisma Access Cloud Plugin API limitations.
Testing environment for Prisma Access MultiTenant is difficult to get.
Finding the matching APIs for the Panorama UI actions we needed to automate.
Limited documentation for Prisma Access Cloud Plugin SSH commands.
Accomplishments that we're proud of
Real customer value to Service Providers and Enterprise customers (we already have SEs asking to use it for their customers).
Tested in a real customer environment.
Use case is applicable for Enterprise (non-multitenant) customers as well as Service Providers.
Enhances Service Provider offering of Prisma Access by reducing time-to-market for all parties (Palo Alto Networks, the Service Provider customer and the end customer).
Expanding XSOAR from SOC into a new use case family of Service Management Automation and the NetOps audience.
Automating end-to-end order to delivery process for service providers.
Automating the querying of Service IPs for the remote connection and providing details to the customer.
Our dashboard which shows service metrics as well as license information and tenant information.
What we learned
How to collaborate on new XSOAR use cases
How to use cool XSOAR features
How customers provision new tenants on Prisma Access
Prisma Access and Panorama API capabilities
How to contribute through the new marketplace UI
What's next for SASE Content Pack
Get feedback from customers and the content team to enhance the pack and offer it in the Marketplace.
Create an Enterprise playbook to help a large customer automate the creation of >1000 Remote Networks.
Collaborate with Prisma Access PMs to leverage more APIs and metrics and suggest useful API enhancements.
Deploy the SASE to MDR escalation flow (in our Threat Response Playbook) with customers to help them add XDR to existing SASE customers.
Add more service status and metrics to the dashboard.
Migrate the SSH-based Panorama gpcs plugin action to the new REST API once the Prisma Access v2 integration gets released.
Built With
autofocus
cortexdatalake
pan-os
panorama
passivetotal
prismaaccess
servicenow
Try it out
github.com | SASE Automation with Prisma Access | Enable Service Providers and Enterprise customers to provision, manage and secure their SASE customers. | ['Lior Kolnik', 'Lookman Kurusumuthu', 'Megha Bindal', 'Matthew Kwong'] | ['Staff Winners'] | ['autofocus', 'cortexdatalake', 'pan-os', 'panorama', 'passivetotal', 'prismaaccess', 'servicenow'] | 16 |
10,347 | https://devpost.com/software/detecting-brand-abuse-using-ct-logs-and-logo-detection | Find matching certificates and create incident of type BrandAbuse
Automatic playbook for type BrandAbuse to create screenshot and match/detect logos
Inspiration
Customer facing companies are often targetted by phishing campaigns using similar domains/pages. Using a very simplistic aproach we can detect malicious phishing campaigns being planned at the moment they're being created.
What it does
Monitor certificate issuers and download any public and newly issued certificates
Initial matching of domains (using the certificate's common_name) with custom regular expressions to find similar company names
Create a screenshot of the potential phishing domain using a custom Google Cloud function with Puppeteer (also present in Git repo)
Detect any logos on the screenshot using the CloudVision API (and provide the related company)
Increase the severity if the logo detection matches with your own company name
What it contains
A custom integration to interact with Transparency log providers
Script to decode Base64 and save output as a file
Custom IncidentTypes definition
Set of playbooks to:
Monitor transparency logs and create a new incident as custom type BrandAbuse (this playbook should be run as a periodic job in XSOAR)
Automatically enrich custom type BrandAbuse to create a screenshot using a custom GCloud function and detect the logos using GCloud Vision API
Several unit tests
Custom code for a Google Cloud function to create screenshots with Puppeteer (
https://github.com/d3vzer0/xsoar-hackathon-pack
)
Custom demisto docker image containing the Python libraries to decode the certificates (
https://github.com/d3vzer0/xsoar-certificate-transparency
)
How I built it
Using the demistosdk and a lot of Python Code, custom containers and Google Cloud Functions
Challenges I ran into
First time developing custom integrations and using the SDK so it took a lot of effort to getting everything set up. The public cloud instance wasn't performing that well so I used a local development deployment instead.
What I learned
Getting to know XSOAR's inside out :)
What's next for Detecting brand abuse using CT logs and logo detection
Finetuning and deduplication, adding more enrichment.
Built With
cloud
docker
google
python
xsoar
Try it out
github.com
github.com | Detecting brand abuse using CT logs and logo detection | This submission monitors newly issued certificates from CT logs for potential phishing campaigns hosted on external (but visually similar) domains using word matching and logo recognition. | ['Joey Dreijer'] | [] | ['cloud', 'docker', 'google', 'python', 'xsoar'] | 17 |
10,347 | https://devpost.com/software/phishing-investigation-response-using-xsoar-and-slashnext | Inspiration
Phishing being the number one attack vector.
What it does
Responds to a phishing alert. Ingests phishing email and extracts and enriches indicators using Slashnext integration and performs conditional checks and takes response actions.
How I built it
xsoar Slashnext integration
Challenges I ran into
Instance configuration
Accomplishments that I'm proud of
Content pack
What I learned
Phishing response can be standardized
What's next for Phishing investigation response using xsoar and slashnext
Minor enhancements
Built With
api
integration
xsoar
Try it out
github.com | Phishing investigation response using xsoar and Slashnext | https://www.youtube.com/watch?v=G0bQiATtEyM | ['Pramukh Ganeshamurthy'] | [] | ['api', 'integration', 'xsoar'] | 18 |
10,347 | https://devpost.com/software/k8s-policy-as-code-for-cn-series | Overview
Inspiration
The inspiration for this project stems from the need to bridge the gap between DevOps and SecOps, as it pertains to firewall policy. Although the Panorama Kubernetes plugin solves the problem of dynamically synching pod-to-ip mappings, we were missing a mechanism that enables firewall policy to be defined once and automatically synched with Panorama.
What it does
A custom Kubernetes integration allows XSOAR to listen for Network Policy changes via the watch API. A change detected via the watch API triggers an XSOAR playbook that automatically converts Network Policy into Panorama policy.
Future support for using XSOAR to detect and quarantine pods associated with malicious activity.
How I built it
The Kubernetes integration was built using the Kubernetes Python SDK. The playbook itself performs the on-the-fly conversion of NP into SP and the XSOAR Panorama integration pushes the results to Panorama.
Challenges I ran into
Mapping k8s NP to SP
Creating a NP annotations/label convention/mapping sufficient for declaring NGFW features and objects, e.g. App-ID, security profiles, etc.
Reconciling the fundamental differences in how firewall policy is interpreted and enforced in k8s vs CN-Series.
Accomplishments that I'm proud of
Seeing a working prototype.
What I learned
Policy as code and other attempts to reduce the number of times firewall policy must be written is a critical piece of the DevSecOps story.
What's next for K8s Policy as Code for CN-Series
World domination
Built With
kubernetes
panos
python | K8s Policy as Code for CN-Series | A DevSecOps playbook that automates the synching of Kubernetes Network Policy with CN-Series Security Policy. | ['Steven Serrata', 'Lior Kolnik', 'Gunjan Patel', 'Megha Punjani', 'Sudeep Padiyar'] | [] | ['kubernetes', 'panos', 'python'] | 19 |
10,347 | https://devpost.com/software/insider-threat-data-exfiltration-response-with-xsoar | Inspiration
Solving the Insider threat challenge
What it does
Use Cortex XSOAR and Code42 integration to identify potential data exfiltration activity from insider threats while speeding investigation and response by providing fast access to file events and metadata across physical and cloud environments.
How I built it
XSOAR Code42 integration
Challenges I ran into
NA
Accomplishments that I'm proud of
Successful run of playbook
What I learned
Solving problems
What's next for Insider threat data exfiltration response with XSOAR
Several enhancements
Built With
api
code42
playbook
xsoar
Try it out
github.com | Insider threat data exfiltration response with XSOAR | Identify data exfiltration activity from insider threats while speeding investigation and response by providing fast access to file events and metadata across physical and cloud environments. | ['Pramukh Ganeshamurthy'] | [] | ['api', 'code42', 'playbook', 'xsoar'] | 20 |
10,347 | https://devpost.com/software/slashnext-automate-ir-abuse-inbox-management | Abuse Inbox management playbook is automatically triggered when admin move the suspicious email to the investigation folder
Automate Phishing IR and Threat Hunting for Abuse Inbox Management
This playbook fully automates the identification and remediation of emails sent to abuse inboxes by leveraging SlashNext’s patented behavioral phishing detection technology that uses millions of virtual browsers to detect unknown threats, return definitive verdicts, and forensics evidence of malicious phishing emails, at scale. Dramatically reduce the time and effort involved in researching suspicious URLs across digital sources with accurate, fully automated, and definitive URL analysis on demand. Abuse inbox management is often a manual and complex operation. With this playbook, teams can reduce up to 80% of the hours spent per week managing abuse inboxes, which also provides detection and remediation for Microsoft Office 365 and similar secure email gateways.
Playbook’s main steps
Extract URLs from the reported email
Request real-time scans through SlashNext SEERTM Cloud (to be analyzed by a virtual browser)
Download URL scan reports from SlashNext SEER Cloud including site screenshot, HTML and rendered text)
Take email snapshot
Log evidence for analyst (host reputation and complete forensics)
Review the incident
Close the investigation
Built With
api
ir
playbook
security
threat-hunting
Try it out
github.com | SlashNext Automate IR Abuse Inbox Management | Dramatically reduce the time and effort involved in researching suspicious URLs across digital sources with accurate, fully automated, and definitive URL analysis on demand. | ["Lisa O'Reilly"] | [] | ['api', 'ir', 'playbook', 'security', 'threat-hunting'] | 21 |
10,347 | https://devpost.com/software/identity-threats-incident-response-with-xsoar-and-silverfort | Inspiration
Solving problems in identity threats space
What it does
Blocking Identity-Based Threats with Silverfort and Palo Alto Networks Cortex XSOAR
How I built it
XSOAR Silverfort integration
Challenges I ran into
Integration configuration
Accomplishments that I'm proud of
Successful development of the playbook
What I learned
Level of flexibility offered by XSOAR and the various use cases that can be easily implemented
What's next for Identity Threats Incident Response with XSOAR and Silverfort
Enhancements with widgets, dashboards, layouts and reports
Built With
api
automations
integtration
playbook
xsoar
Try it out
github.com | Identity Threats Incident Response with XSOAR and Silverfort | Blocking Identity-Based Threats with Silverfort and Palo Alto Networks Cortex XSOAR | ['Pramukh Ganeshamurthy'] | [] | ['api', 'automations', 'integtration', 'playbook', 'xsoar'] | 22 |
10,347 | https://devpost.com/software/test-pjikyq | Inspiration
The passion to solve problems in OT cybersecurity space
What it does
allows organizations to efficiently and effectively analyze, prioritize, and remediate potential threats in operational technology (OT) environments, lowering the risk to business-critical facilities and processes.
How I built it
Using XSOAR integrations and playbooks
Challenges I ran into
-NA-
Accomplishments that I'm proud of
Successful run of playbook
What I learned
Solving problems
What's next for test
Enhancements with dashboards and reports
Built With
api
integrations
playbook
python
xsoar
Try it out
github.com
github.com | Ransomware Response Pack | Efficiently and effectively analyze, prioritize, and remediate potential threats in operational technology (OT) environments, lowering the risk to business-critical facilities and processes. | ['Pramukh Ganeshamurthy'] | [] | ['api', 'integrations', 'playbook', 'python', 'xsoar'] | 23 |
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