Published Paper Details:

The AI system called "Road Traffic Analysis Using YOLO-V4 & Deep Sort" uses advanced technology to automate vehicle tracking in real time. Increasing numbers of urban residents and cars place heavy burdens on current traffic management systems that operate slowly and have limits. This project solves video monitoring difficulties by using YOLO-V4 for object detection and Deep Sort for multi-object tracking to process both streaming and recorded videos. The system recognizes motor vehicles, gives those ID numbers, and follows them across several images to reveal road patterns and vehicle movement. The system uses improved processing tools such as non-max suppression and Kalman filter methods to detect objects reliably. The system uses these technologies together with Python and TensorFlow to work in all types of roads and smart city settings at top speed. This project lets transportation authority's control road activity better to ease congestion and better protect their users. Our project will keep improving through the addition of traffic flow prediction systems based on IoT technology plus cloud architecture for wider implementation. Most modern traffic systems would benefit from the addition of smart tolling functions plus automatic detection of crimes and self-driving car assistance as part of intelligent transportation research.