https://github.com/vickydev810/federated-urban-ai

A scalable system that uses data from city zones (traffic lights, CCTVs, sensors) to detect traffic congestion, emergencies, and road conditions via local federated learning. Agentic AI coordinates decentralized agents, while blockchain ensures transparent contributions and rewards for rapid emergency response and efficient zone management.
https://github.com/vickydev810/federated-urban-ai

Last synced: 4 months ago
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A scalable system that uses data from city zones (traffic lights, CCTVs, sensors) to detect traffic congestion, emergencies, and road conditions via local federated learning. Agentic AI coordinates decentralized agents, while blockchain ensures transparent contributions and rewards for rapid emergency response and efficient zone management.

• Host: GitHub
• URL: https://github.com/vickydev810/federated-urban-ai
• Owner: VickyDev810
• Created: 2025-04-14T06:43:34.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-04-16T14:00:52.000Z (about 1 year ago)
• Last Synced: 2025-04-16T20:59:35.302Z (about 1 year ago)
• Size: 123 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Federated Agentic AI Urban Monitoring System

A decentralized, AI-driven traffic and urban monitoring system leveraging federated learning, blockchain-based rewards, and agentic intelligence for real-time responsiveness and transparency.

## 🚦 What It Does

- Collects data from traffic lights, CCTVs, and sensors within defined city zones

- Uses autonomous agents to process data locally for:

  - Traffic congestion detection

  - Emergency situation alerts

  - Road maintenance monitoring

- Trains AI models locally using **Local Federated Learning**

- Syncs model updates via a **Central Agentic AI Server**

- Logs contributions and rewards zones via **Blockchain Smart Contracts**

- Automatically alerts emergency services in case of critical events

## 🧠 Key Technologies

- **Federated Learning (LFL)** for privacy-preserving local model training  

- **Agentic AI** for task distribution and orchestration  

- **Blockchain Layer** for contribution tracking and reward distribution  

- **Edge Processing** using lightweight local agents

## 🧩 Project Components

1. **Data Acquisition Module**  

2. **Edge Agent Processing**  

3. **Local Federated Learning**  

4. **Blockchain Transparency Layer**  

5. **Central Agentic AI Server**  

6. **Emergency Service Trigger System**

## 🔍 Vision

Build a scalable, smart city solution that incentivizes efficient zone-level response, supports emergency systems, and fosters transparent collaboration between municipal zones.

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> _"Cities don't just breathe — they learn, adapt, and respond."_