The rapid growth of urbanization has resulted in increased vehicle density on roads, raising the demand for efficient and intelligent traffic monitoring systems. This paper presents a real-time vehicle detection, tracking, and recognition system using YOLOv26(ultralytics), the latest advancement in the You Only Look Once (YOLO) architecture. The proposed system leverages deep learning-based object detection to detect and classify vehicles from video streams captured by surveillance cameras. YOLOv26(ultralytics) offers improved accuracy and speed over its predecessors, making it highly suitable for real-time Intelligent Transportation System (ITS) applications. The system incorporates Deep SORT for robust multi-object tracking and supports recognition based on vehicle attributes including color, type, and license plate.
K et al. (Thu,) studied this question.