This project is an AI-driven intelligent traffic management system that uses computer vision and deep learning to monitor and control traffic signals in real time. The system processes live video feeds from traffic cameras and dynamically adjusts signal timing.
How It Works
The system detects vehicles on multiple roads and analyzes traffic density using PyTorch and OpenCV. Based on this data, it dynamically adjusts the green signal timing to prioritize heavily congested roads while minimizing delays for lighter traffic lanes.
System Architecture
The backend is powered by Flask, handling real-time AI inference, traffic data processing, and communication with the frontend via REST APIs. The frontend is built with ReactJS and Bootstrap, offering a clean, responsive interface that visualizes traffic density and signal states.
