AI for Connectivity Hackathon II: Building Resilient Networks 

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Creating Connectivity Solutions for underdevoloped school areas and healthcare

ConnectAI

Sreelakshmi_Kaplingat

Amira

Jasper

Ursulaa

Clemence

The AI-powered Smart Energy Management System addresses high energy costs and unreliable electricity in rural telecom networks. Using datasets like VIIRS Nighttime Lights, OpenCellID, Sentinel-2, and Africa Bandwidth Maps, the system optimizes energy consumption across network nodes.

It employs machine learning to analyze real-time energy usage and predict consumption patterns, enabling dynamic power-saving modes for off-peak hours. Additionally, renewable energy integration is facilitated by identifying optimal locations for solar-powered Base Transceiver Stations (BTS) using Sentinel-2 imagery.

The system features a real-time AI-powered dashboard, offering network operators insights into energy consumption, grid stability, and alternative energy sources. OpenStreetMap and Global Electricity Grid data help in planning infrastructure placement.

This solution not only reduces operational costs but also contributes to sustainability goals by enabling efficient power utilization. Its scalability extends to multiple rural telecom sites, making it a vital innovation in network design and strategic planning.

An AI-powered system optimizing network energy in rural areas with unstable grids, using satellite data and ML for real-time monitoring, dynamic power-saving, and solar integration, cutting costs and ensuring sustainable connectivity.

"ConnectAI team on AI for Connectivity Hackathon II: Building Resilient Networks Hackathon"

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