Smart Traffic Management System

AI-Powered Traffic Management System

Ever found yourself stuck at a red light on an empty street, wondering why the system isn't smarter? I'm excited to share my solution: an AI-Powered Smart Traffic Management System. This isn't just a concept; it's a fully functional prototype designed to reduce congestion and improve traffic flow in real-time.

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Key Features

• Real-Time Vehicle Detection: Utilizes OpenCV to process live video streams and accurately count vehicles in each lane.

• Adaptive Signal Control: Dynamically adjusts signal timings based on vehicle counts, giving priority to lanes with heavier traffic.

• Live Web Dashboard: A Flask-based dashboard visualizes live camera feeds, vehicle counts, and signal status, providing a real-time overview of traffic flow.

• Data Logging & Analytics: Logs traffic density to a SQL database for historical analysis, performance monitoring, and long-term city planning.

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How It Works: The Tech Stack

• Backend: Python with the Flask micro-framework.

• Computer Vision: OpenCV for real-time vehicle detection.

• Database: SQLAlchemy for interacting with an SQLite database.

• Frontend: HTML, CSS, and JavaScript with Bootstrap for a clean and responsive dashboard.

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This project demonstrates practical skills in Python, AI, Computer Vision, and Full-Stack Development. It's a great example of how technology can be used to solve real-world urban problems.