CSP Tri 3 - Pyre Wildfire Prediction Project

Project Overview

Welcome to our AP Computer Science Principles Trimester 3 repository! The main focus of this project is Pyre, an AI-driven wildfire prediction and risk assessment system.

Pyre: AI Wildfire Prediction and Mitigation

We're developing a machine learning application that leverages geospatial and environmental data to predict and mitigate the impact of wildfires. Our goal is to improve response time and preparedness by providing accurate fire risk assessments through:

• Predictive wildfire models
• Real-time fire risk mapping
• Adaptive emergency response recommendations

This project integrates cutting-edge AI and data analysis techniques to enhance wildfire management and public safety.

Repository Structure

This project is split across two repositories:

• Backend Repository: Contains API endpoints, ML models, and data processing
• Frontend Repository: Contains user interfaces, visualization components, and API integrations

Project Timeline

• Week 1 (March 12-21): Discovery, Planning, Setup, and Initial Data Exploration
• March 23 - April 12: Environmental Data Integration
• March 23 - April 19: ML Model Development
• March 30 - April 19: Backend Development
• April 6 - April 26: Frontend Development
• April 27 - May 10: Integration Testing
• May 11 - May 20: User Testing
• May 21 - May 30: Refinement
• May 31 - June 4: Final Deployment
• June 5 - June 9: Final Evaluation

Key Features

1. Wildfire Prediction System

   • Forecasts fire risk based on historical and real-time environmental data
   • Uses machine learning models trained on temperature, humidity, and wind conditions
   • Provides both short-term and long-term fire risk predictions

2. Fire Risk Mapping

   • Dynamically generates fire risk heatmaps
   • Integrates satellite and sensor data for real-time updates
   • Helps emergency services prioritize high-risk areas

3. Adaptive Emergency Response System

   • Recommends evacuation routes based on fire progression
   • Identifies optimal locations for firefighting resources
   • Uses AI to enhance response time and efficiency

4. User Interfaces

   • Web dashboard for emergency management teams
   • Mobile app for public alerts and safety recommendations
   • Interactive map for real-time fire risk visualization

Getting Started

Backend Setup

1. Clone the backend repository:

   git clone https://github.com/your-team/pyre-backend.git
   cd pyre-backend
   

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Run the backend server:

   python main.py
   

Frontend Setup

1. Clone the frontend repository:

   git clone https://github.com/examplelink.git
   

2. Use the Makefile to set up and run:

   make
   

Contributing

1. Create a new branch for your feature or fix
2. Make your changes
3. Submit a pull request with a detailed description
4. Request review from team members

Team

This project is part of our AP Computer Science Principles coursework.

License

This project is for educational purposes only.