Canny Edge Detection for Obstacles Avoiding Vehicle Clogging and Monitoring

This essay seeks to highlight the growing issue of urban traffic congestion and the urgent need for cuttingedge tools and technology to raise the bar for traffic control. It has been shown that the existing techniques, such timers and human control, are inadequate in the face of this dilemma. This study proposes a system to measure vehicles in real time using digital image processing and “Canny Edge Detection” to control traffic. The response speed, automation, vehicle management, reliability, and general efficiency of the previous systems can all be significantly improved with this formidable traffic control system. In addition, appropriate schematics are used to show the entire process, which includes image acquisition, edge identification, and green signal allocation using sample photographs of various traffic situations. The outcomes are then observed. Flexible in that it modifies traffic light timing in accordance with current road conditions and obstacle avoidance strategies to minimize disruption.