A project for HackBeanPot 2024 that incorporates full-stack development, machine learning, model training, and UI/UX to deliver a cohesive product.
- Introduction
- Requirements and Installation
- Data Visualization
- Project Structure
- Future Improvements
- Developers
Under the Weather is a web application designed to forecast infectious disease outbreaks in your area based on their inputed state. The application uses machine learning and data visualization to display possible outbreaks of either hepatitis, measles, pertussis, rubella, and smallpox in any or all of the 50 U.S. states.
Flask and Docker are required.
Data analysis performed using Pandas, Numpy libraries, as well as visualization with Plotly (as seen below).
Frontend: HTML, CSS, TypeScript, React
Database: MySQL
Backend: Python, PyTorch framework for NN
- Data Collection: Identify additional infectious diseases (COVID-19, influenza, RSV) which are relevant to users and geographic region. Collect reliable data from public health organizations, research institutions, and government agencies.
- Real-Time Data: Incorporate real-time data with feedback from users (user location and possible infectious disease) to provide most up-to-date predictions.
- Provide users with qualitative descriptions of predictions ("low risk", "medium risk", "high risk"), as well as suggestions for actions (wear a mask, avoid large group events, quarantine, etc).
- Mobile Optimization: Optimize application for mobile devices in order to improve accessibility.
- Harish Varadarajan
- GitHub Profile: https://github.com/superhvarn
- Aarav Shyamkumar
- GitHub Profile: https://github.com/AShyamkumar19
- Ethan Moskowitz
- GitHub Profile: https://github.com/EthanMoskowitz
- Alan Zhang
- GitHub Profile: https://github.com/alanZhang0813
- Ella Chee
- GitHub Profile: https://github.com/ellachee4
- Jaden Zhou
- GitHub Profile: https://github.com/JadenZHub