Intelligent Vision-Based Traffic Monitoring and Road Safety Management Using Artificial Intelligence and Deep Learning

Abstract

Due to rapid urban growth and population increase, traffic congestion and road accidents have become common problems. Traditional traffic systems use fixed signal timings and manual monitoring, which are less flexible. This research proposes a smart traffic monitoring system using AI and computer vision. Cameras continuously monitor vehicles at important road intersections. The system analyzes real-time images to measure traffic density and detect accidents. It also identifies emergency vehicles such as ambulances and fire engines. Image processing and deep learning help the system work in crowded and difficult conditions. When an accident or emergency is detected, alerts are sent to traffic authorities with location and time details. Testing shows improved vehicle detection and faster accident identification. Overall, the system improves traffic management, emergency response, and road safety.