TRAFFIC CONGESTION CONTROL USING IMAGE PROCESSING

Abstract

Traffic management is one of the most significant faced by urban areas globally. The growing number of vehicles and the inadequacy of conventional traffic control systems have exacerbated issues like traffic congestion, accidents, pollution, and inefficient emergency response times. This project proposes an innovative solution using image processing combined with Arduino-based traffic lights to enhance traffic management. Real-time traffic data is analyzed using python and OpenCV, while the control system, managed by Arduino Uno, adjusts traffic congestion, violations, and accidents, triggering real-time alerts to improve safety, response time, and optimize traffic flow. The proposed system is capable of reducing fuel consumption, minimizing accidents, and improving traffic flow, contributing to smarter cities