🚦 Real-Time Traffic Monitoring & Intelligent Control System

An AI-powered smart traffic management system that leverages YOLOv8 for real-time vehicle detection and LSTM neural networks for traffic flow prediction. The system dynamically controls traffic signals, prioritizes emergency vehicles, and provides a live visualization dashboard.

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📸 Demo

🎥 Watch the Demo Video

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🧠 Key Features

• 🔍 Real-time vehicle detection using YOLOv8
• 🚨 Emergency vehicle recognition and priority control
• 📈 Traffic congestion prediction using LSTM neural networks
• 🟢 Adaptive traffic signal control
  • Dynamic green light extension
  • Idle time reduction
  • Emergency override logic
• 📊 Live dashboard visualization
  • Vehicle counts
  • Traffic decisions
  • Real-time updates
• 🎥 Supports video files and live camera feeds

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🧰 Technology Stack

Layer	Tools / Libraries
Object Detection	YOLOv8 (Ultralytics)
Video Processing	OpenCV
Prediction Model	TensorFlow / Keras (LSTM)
Dashboard UI	Plotly Dash
Backend Logic	Python (Multithreading)

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🚀 System Workflow

1. Video Input
   Captures real-time video from a camera or video file using OpenCV

2. Vehicle Detection
   YOLOv8 detects cars, buses, bikes, and emergency vehicles

3. Traffic Prediction
   LSTM model predicts congestion levels based on vehicle density

4. Decision Engine
   Adjusts traffic signal timing dynamically and prioritizes emergency vehicles

5. Live Dashboard
   Displays vehicle count and traffic decisions with periodic updates

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🖥️ Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/prattyan/traffic-manage
cd traffic-manage

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Prepare Input

• Add a sample video named traffic_video.mp4
  OR
• Connect a live camera feed

YOLOv8 model weights are automatically downloaded via Ultralytics.

4️⃣ Run the Application

python app.py

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📁 Project Structure

📂 traffic-monitoring-system/
│
├── traffic_video.mp4       # Sample traffic footage
├── traffic_lstm.h5         # Pre-trained LSTM model
├── yolov8n.pt              # YOLOv8 nano weights
├── app.py                  # Main application script
├── requirements.txt        # Dependencies
└── README.md               # Project documentation

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🔮 Future Enhancements

• 📡 Integration of multiple camera feeds
• 🗄️ Storage of historical traffic data
• 📢 Real-time alerts to traffic authorities
• ☁️ Cloud deployment for large-scale use
• 🧠 Reinforcement learning for smarter signal optimization

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🧑‍💻 Author

Prattyan Ghosh
📧 Email: prattyanghosh@gmail.com
🔗 LinkedIn | Portfolio

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