AI for Connectivity Hackathon II: Building Resilient Networks 

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CODE n COFEE

Arslan-MIT

# AI-Powered Network Planner for Rural Connectivity

## 📌 Overview
This project, **AI-Powered Network Planner for Rural Connectivity**, leverages AI, geospatial data, and network analysis to optimize the placement of telecom towers in underserved rural areas. It integrates multiple datasets to identify the best locations for network expansion while considering cost, population density, and existing infrastructure.

## 🚀 Features
- **📡 Cell Tower Placement Optimization**: Uses K-Means clustering to determine the best locations for telecom towers.
- **📊 Internet Outage Analysis**: Integrates IODA API to analyze regional network outages.
- **📍 Geospatial Data Integration**: Processes OSM and OpenCellID data for real-world tower placement.
- **📈 Population-Based Network Planning**: Incorporates GHSL population density data for accurate demand forecasting.
- **🖥️ Interactive Dashboard**: Provides a user-friendly Streamlit interface for visualizing network expansion plans.


## 📊 Data Sources
- **[OpenCellID](https://opencellid.org/)** (Cell Tower Locations)
- **[OpenStreetMap](https://www.openstreetmap.org/)** (Geospatial Building Data)
- **[IODA](https://ioda.inetintel.cc.gatech.edu/)** (Internet Outage Data)
- **[GHSL](https://ghsl.jrc.ec.europa.eu/)** (Population Density Data)

## 🤖 AI Models Used
- **K-Means Clustering**: For optimal network tower placement.
- **Geospatial Analysis**: To integrate multiple datasets for better decision-making.

## 🚀 Future Enhancements
- Integration with real-time network performance APIs.
- Support for additional geospatial analysis methods.
- Cost-effectiveness analysis with financial models.

## 🛠 Contributors
- **Muhammad Arslan** (Lead Developer)

## 📜 License
This project is licensed under the MIT License.

## ⭐ Support
If you find this project useful, please ⭐ the repository and share your feedback!



AI-Powered Network Planner for Rural Connectivity is a data-driven tool that leverages AI and GIS data to optimize cellular tower placement in rural areas, improving connectivity and network coverage.



"CODE n COFEE team on AI for Connectivity Hackathon II: Building Resilient Networks Hackathon"

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