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Sep 30, 2022
1 min read

Smart Traffic Management System using Computer Vision

Developed a dynamic traffic management system using computer vision to optimize traffic flow and ensure adherence to traffic signals.

The system calculates traffic density in different directions and dynamically adjusts traffic light timings. It employs OpenCV with YoloV3 to recognize various vehicle types and monitor adherence to traffic signals. Additionally, it captures snapshots of vehicles violating signals or obstructing zebra crossings, enhancing traffic law enforcement and management.

The project aims to improve traffic flow efficiency and safety by providing real-time traffic monitoring and automated control of traffic lights based on traffic density and vehicle behavior.