Islam, Md. MotaharulNoor, JannatunArnob, Faed AhmedFuad, Md. AzmolNizam, Abu TahirSiam, Arifin Tanjim2021-09-072021-09-0720212021-06ID 17301145ID 17301154ID 17101393ID 17301123http://hdl.handle.net/10361/14986Cataloged from PDF version of thesis.Includes bibliographical references (pages 53-57).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.There has been an upsurge in the number of issues with Bangladesh’s present traffic control system. Hence, several accidents have occurred frequently. The two primary causes of a rise in the number of injuries are violations of traffic laws, such as illegal lane changes and excessive speeding. Here we have presented extensive research with an intention to resolve the current traffic management system using real-time object detection. In our proposed system, an edge node will detect the lane-based rule violation and send the data to the nearest intermediary node. Afterward, License plates as objects will be detected using YOLO object detection executed in the intermediary computing device. Finally, extracted license plate images from the intermediary nodes will be sent to BRTA traffic servers to detect the violator’s Bangla license plate number using pytesseract. We have built a data set of 1450 images for object detection and achieved an accuracy of 91%. Our system will assist the traffic control department in identifying those responsible for traffic rule violations and ensuring that the laws are strictly enforced.57 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Automatic License Plate Recognition (ALPR)Hough Line TransformYOLO Object DetectionFog ComputingOptical Character Recognition (OCR)Computer VisionData Traffic Management System (Computer system)Thesis