Improvement on Road Management System: Artificial Intelligence Application based on Plate Number Detection System using YOLO Algorithm
Zeng Yukun, Azman Ab Malik · Jurnal Kejuruteraan · 2025
Traffic jams is a typical urban problem caused by a variety of reasons such as high traffic volume, construction, roadwork, incidents, and accidents. With the development of urbanization, daily traffic has become a problem, especially in some key areas of heavy road or parking can cause serious traffic problems. There are many method has been suggest to reduce a traffic such as using public transport, carpooling, ridesharing, traffic management system, road infrastructure improvements, flexible work hours and promoting non motorized transport. One of the approach suggest is to improve a time consume by vehicle on the road. Abnormal pattern can be define by using plate number detection and the information will send to autorized organisation to alert or support for road management system. In this project, a system has been developed using Python and YOLO model to monitor a specified area with an external camera, identify vehicles within the area by recognize license plates. Based on the experiment conducted, 88.23% of number car plate has been indentified. The system aims to solve the problem of unauthorized road or parking by tracking the time or how long a vehicle stays in the monitored area. If a vehicle exceeds a predetermined time limit, the system triggers an alert to authorize people. The solution is designed to reduce traffic jam or parking area and ensure well-organized vehicle management in restricted areas.