This project was created as a contribution and our entry for the LabLab.ai Hcakaton for Ai Connectivity.
Network Outage Forecaster is an AI-powered Python application designed to predict network outages using weather data. The project provides proactive alerts to underserved areas, schools, and organizations, helping them prepare for potential connectivity disruptions. Inspired by the recent Los Angeles wildfire outages, this tool aims to bridge digital accessibility gaps.
- AI-Powered Predictions: Leverages machine learning to analyze weather data and predict network outages.
- Proactive Alerts: Sends timely notifications to schools and underserved communities.
- Data Integration: Uses weather APIs and historical outage data for accurate forecasting.
- Scalability: Built for both small-scale local use and large-scale deployments.
To get started, follow these steps:
-
Clone the repository:
git clone https://github.com/tomolaoke/NetworkOutageForecaster.git cd NetworkOutageForecaster -
Set up a virtual environment: python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
-
Install dependencies: pip install -r requirements.txt
-
Add your weather API key in the .env file: env WEATHER_API_KEY=your_api_key_here
-
Run the application: python app.py
Usage Register schools or organizations in the system. Integrate your preferred weather API for real-time data. Receive proactive outage alerts based on weather forecasts.
Project Structure ├── app.py # Main application file ├── models/ # Contains AI models and forecasting logic ├── utils/ # Utility functions for data processing ├── templates/ # Frontend templates (if applicable) ├── requirements.txt # List of dependencies ├── README.md # Project documentation └── .gitignore # Ignored files and folders Contributing We welcome contributions! Please fork the repository and submit a pull request.
License This project is licensed under the MIT License.
Contact For inquiries or support, please reach out to:
Name: Tomola Oke Email: [email protected] GitHub: github.com/tomolaoke