AI-Powered Virtual Smart City 🏙️

A fully virtual smart city simulation with IoT devices, real-time dashboard, and AI-based optimization.

🌟 Features

Backend (Python + FastAPI)

• Simulated IoT Devices:

  • 🚦 Traffic Sensors: Monitor vehicle flow, speed, and congestion
  • 💡 Street Lights: Adaptive brightness with energy tracking
  • ⚡ Smart Meters: Energy consumption monitoring for buildings
  • 🅿️ Parking Sensors: Real-time parking availability

• REST API: Complete endpoints for all device data

• WebSocket Streaming: Real-time data updates every 2 seconds

• AI Optimization: Rule-based logic for traffic, energy, and parking management

Frontend (React + Socket.IO)

• Real-time dashboard with live data visualization
• Interactive charts using Recharts
• AI insights and recommendations display
• Responsive design for all screen sizes

📁 Project Structure

IOTPJCT/
├── backend/
│   ├── main.py                 # FastAPI application
│   ├── requirements.txt        # Python dependencies
│   ├── models/
│   │   └── schemas.py         # Pydantic data models
│   ├── devices/
│   │   ├── traffic_sensor.py  # Traffic simulation
│   │   ├── street_light.py    # Street light simulation
│   │   ├── smart_meter.py     # Energy meter simulation
│   │   └── parking_sensor.py  # Parking simulation
│   └── ai/
│       └── optimizer.py       # AI optimization logic
├── frontend/
│   ├── src/
│   │   ├── App.jsx            # Main application component
│   │   ├── components/
│   │   │   ├── TrafficMonitor.jsx
│   │   │   ├── EnergyDashboard.jsx
│   │   │   ├── ParkingStatus.jsx
│   │   │   └── AIInsights.jsx
│   │   └── services/
│   │       └── api.js         # API and WebSocket services
│   ├── package.json
│   └── vite.config.js
├── README.md
└── .gitignore

🚀 Getting Started

Backend Setup

1. Navigate to backend directory:

   cd backend

2. Create virtual environment (recommended):

   python -m venv venv
   
   # Windows
   venv\Scripts\activate
   
   # Linux/Mac
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Run the server:

   uvicorn main:app --reload

   The backend will be available at:

   • API: http://localhost:8000
   • API Docs: http://localhost:8000/docs
   • WebSocket: ws://localhost:8000/ws

Frontend Setup

1. Navigate to frontend directory:

   cd frontend

2. Install dependencies:

   npm install

3. Run the development server:

   npm run dev

   The frontend will be available at http://localhost:3000

Running the Complete System

1. Start the backend (in one terminal):

   cd backend
   python -m uvicorn main:app --host 0.0.0.0 --port 8000

2. Start the frontend (in another terminal):

   cd frontend
   npm run dev

3. Open your browser to http://localhost:3000

The dashboard will automatically connect to the backend WebSocket and start displaying real-time data!

📡 API Endpoints

REST API

• GET / - API information and available endpoints
• GET /api/traffic - Current traffic sensor data
• GET /api/lights - Street light status and energy
• GET /api/energy - Smart meter readings
• GET /api/parking - Parking availability
• GET /api/overview - City-wide statistics
• GET /api/insights - AI-generated insights and recommendations

WebSocket

• WS /ws - Real-time data stream (updates every 2 seconds)

🤖 AI Features

The AI optimizer analyzes data in real-time and provides:

1. Traffic Optimization:

   • Congestion detection and alerts
   • Slow-moving traffic identification
   • Alternative route recommendations

2. Energy Management:

   • High consumption alerts
   • Street light dimming suggestions
   • Power quality monitoring

3. Parking Intelligence:

   • Low availability warnings
   • Overflow parking guidance
   • Real-time capacity monitoring

🎯 Simulated IoT Devices

Traffic Sensors (8 locations)

• Realistic time-of-day traffic patterns
• Rush hour simulation (7-9 AM, 5-7 PM)
• Vehicle counting and speed monitoring

Street Lights (12 units)

• Auto on/off based on time
• Adaptive brightness (dimmed 10 PM - 6 AM)
• Energy consumption tracking

Smart Meters (12 units)

• 6 Residential, 4 Commercial, 2 Industrial
• Building-specific consumption patterns
• Power quality metrics

Parking Sensors (102 spots)

• 5 parking locations across the city
• Dynamic occupancy based on time
• Duration tracking

🔧 Technology Stack

Backend:

• FastAPI - Modern Python web framework
• Uvicorn - ASGI server
• WebSockets - Real-time communication
• Pydantic - Data validation

Frontend (Coming next):

• React 18
• Socket.IO Client
• Recharts
• Axios

📊 Data Flow

1. IoT devices generate simulated data every 2 seconds
2. AI optimizer analyzes data and generates insights
3. Data is aggregated and sent via WebSocket
4. Frontend receives and visualizes real-time updates

🌐 WebSocket Data Format

{
  "type": "update",
  "timestamp": "2025-11-26T02:40:00",
  "data": {
    "traffic": [...],
    "lights": [...],
    "energy": [...],
    "parking": [...],
    "insights": [...],
    "overview": {...}
  }
}

📝 Development Notes

• All IoT data is simulated - no real devices required
• Devices use realistic patterns based on time of day
• AI uses rule-based logic (can be extended to ML models)
• WebSocket automatically reconnects on disconnection

✅ Project Status

1. ✅ Backend with IoT simulation - COMPLETED
2. ✅ Frontend React dashboard - COMPLETED
3. ✅ Data visualization with Recharts - COMPLETED
4. ⏳ 3D city visualization (optional enhancement)

🎨 Frontend Features

• Real-time Dashboard: Live updates every 2 seconds via WebSocket
• Traffic Monitor: Area charts showing vehicle counts and congestion levels
• Energy Dashboard: Bar charts for building consumption and street light status
• Parking Status: Pie charts and location-based availability tracking
• AI Insights: Real-time alerts and recommendations with severity indicators
• Responsive Design: Works on desktop, tablet, and mobile devices
• Dark Theme: Modern, premium UI with smooth animations

📄 License

This project is open source and available for educational purposes.

🤝 Contributing

Feel free to fork this project and submit pull requests!

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