README.md

metadata

title: AIforConnectivityHack
emoji: 🔥
colorFrom: red
colorTo: red
sdk: streamlit
sdk_version: 1.42.1
app_file: app.py
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Data Sources

• School/Hospital Locations: Giga
• Network Performance: Ookla Open Data

🏥 AI-Powered Public Sector Network Optimizer

Hackathon Submission for AI for Connectivity II
Enabling resilient, efficient connectivity for schools and healthcare facilities

📖 Problem Statement

Public sector networks in underserved regions face critical challenges:

Challenge	Impact
High Energy Costs	40-60% of operational budgets spent on power
Unplanned Downtime	15-20% annual connectivity loss in schools
Inefficient Maintenance	Reactive repairs cost 3-5× more than preventive
Environmental Impact	Each facility emits 12-18 tons CO₂ annually

This solution directly addresses these issues through AI-driven optimization of network infrastructure.

🛠️ Solution Overview

Architecture Diagram

Made with Excalidraw - Edit diagram

Key components:

1. Data Integration Layer
   • Giga school connectivity data
   • Ookla network performance metrics
   • IoT sensor streams
2. AI Engine
   • Energy consumption forecasting (Prophet)
   • Anomaly detection (Isolation Forest)
3. Optimization Layer
   • Maintenance scheduling
   • Cost-benefit simulations
4. Visualization Dashboard
   • Real-time monitoring
   • Predictive analytics

📊 Validation Metrics

Simulation Results (50 Facilities)

Metric	Improvement
Energy Costs Reduction	22.4%
Preventive Maintenance Rate	41% ↑
CO₂ Emissions Reduction	18.7 tons/yr
Network Uptime Improvement	31% ↑
Maintenance Cost Savings	$12,500/yr

Based on 6-month simulation using synthetic data mirroring real-world conditions

🚀 How to Use

1. Live Demo
   Access our hosted version on Hugging Face Spaces

2. Local Installation

   git clone https://github.com/your-username/public-sector-optimizer
   pip install -r requirements.txt
   streamlit run app.py