This project aims to provide an intelligent solution for wildfire response and prediction using data-driven methodologies. It is designed to analyze wildfire risks and offer predictive insights to aid emergency response teams.

• Python (Core language)
• Flask (Web framework for the API)
• REST API (For communication between frontend and backend)
• Machine Learning (Random Forest Algorithm for wildfire prediction)
• Scheduling Algorithm (For optimizing emergency response planning)

• Python 3.x (Must be greater than 2.7)

Ensure you have Python installed before proceeding. You can check your version with:

python --version

Clone the project using the following command:

git clone https://github.com/Iktisad/conuhacks_sap_challenge.git

Navigate to the project directory:

cd conuhacks_sap_challenge  # Ensure this directory matches the cloned repository name

Create a virtual environment:

python -m venv .venv

Activate the virtual environment:

.venv\Scripts\activate.bat

.venv\Scripts\Activate.ps1

source .venv/bin/activate

Run the following command to install all required dependencies:

pip install -r requirements.txt

To run the project in debugging mode:

python run.py

Alternatively, you can run the project using Flask:

flask run

• Python
• Flask
• REST API
• Machine Learning
• Random Forest Algorithm
• Scheduling Algorithm
• Data Science

This project is licensed under the MIT License. See the LICENSE file for details.

For any inquiries or issues, feel free to reach out via GitHub Issues or email.