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The automotive industry has experienced a spectacular expansion in the last decade, with an increase in number of cars in metropolitan cities. Maintaining track of automobiles based on their plates number in order to manage vehicular traffic properly in the city has posed difficulty. This research presents an artificial intelligence-based technology technique (YOLO) for tracking vehicle movement based on the vehicle's plate number with data logging model and a centralized database structure for vehicles identification and monitoring, using other techniques such as image processing and IoT mechanism for detection and recognition accuracy. In order to create an Intelligent Plate Number Recognition (IPNR) System, this study employs artificial intelligence, computer vision (image processing), laser scanning technologies, and convolutional neural networks (CNN). This model concepts and computations underpin …