 The study utilizes advanced computer vision technology with deep learning algorithms to enhance real-time vehicle recognition and tracking for efficient and safe transportation systems. The S-Liteweight YOLO algorithm achieves 95.7% accuracy in vehicle recognition and the addition of the SE attention transfer mechanism and SPPS CSPC module further improves results. This research has a promising application prospect in traffic monitoring and big data creation for transportation. This article was authored by Ching-Win Yeoh, Yunching Song, and Xin Yue Zhao.