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Under the Weather

A project for HackBeanPot 2024 that incorporates full-stack development, machine learning, model training, and UI/UX to deliver a cohesive product.

Table of Contents

  1. Introduction
  2. Requirements and Installation
  3. Data Visualization
  4. Project Structure
  5. Future Improvements
  6. Developers

Introduction

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.

Requirements and Installation

Flask and Docker are required.

Data Visualization

Data analysis performed using Pandas, Numpy libraries, as well as visualization with Plotly (as seen below). Screenshot 2024-02-24 at 10 46 34 PM

Project Structure

Frontend: HTML, CSS, TypeScript, React

Database: MySQL

Backend: Python, PyTorch framework for NN

Future Improvements

  1. 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.
  2. Real-Time Data: Incorporate real-time data with feedback from users (user location and possible infectious disease) to provide most up-to-date predictions.
  3. 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).
  4. Mobile Optimization: Optimize application for mobile devices in order to improve accessibility.

Developers