FireWatch 🔥

SAP Challenge Winner 🏆- ConUHacks 2025

Challenge: Create a platform to optimize the deployment of firefighting resources.

• Part 1: Minimize the total cost and the number of high severity missed responses. Contraints include the cost per unit deployment, cost of missing a fire, the severity of the fire.
• Part 2: Use machine learning to predict future fires based on historical environmental and wildfire data. The model should be able to predict the severity of the fire and the location of the fire. We want to easily visualize the predictions on a map.

Submission Project: https://devpost.com/software/firewatch-qn4yap

Frontend Setup

Prerequisite: Node.js

• Run cp .env.example .env
• Fill the .env file with the required information
• Run npm install
• Run npm run dev
• Naviguate to http://localhost:5173

Backend Setup

Prerequisite: Python

• Open a new terminal
• Run cd backend
• Run python -m venv venv
• Run
  • On Windows: venv\Scripts\activate
  • On Mac/Linux: source venv/bin/activate
• Run pip install -r requirements.txt
• Run python main.py (or maybe python3 main.py)
• API is now running on http://localhost:5000

Team Members

• Mohamed Amine Elarabi
• Mohammed Larbi Turki
• Abdul Rahman Zahid
• James Brutus