Edge Based Intelligent Secured Vehicle Filtering and Tracking System Using YOLO and EasyOCR

Edge computing is used in intelligent transportation systems to handle data faster and with less delay. Implementing the proposed system in edge computing improves security in intelligent transportation systems. Video surveillance has played an essential role in maintaining transportation systems, security monitoring, and surveillance. In recent times, vehicles involved in crimes, theft, and violating traffic rules are on the increase. Monitoring vehicles using traditional methods is time-consuming and an exhausting process. Existing systems make use of methods which only detect and trace a particular vehicle, which is inefficient for finding and tracking multiple vehicles simultaneously. In this paper, the proposed method generates a secured road map of vehicle travel using Google Maps. The proposed approach was incorporated into the electric eye, which employs masking for color detection and YOLOV5 was used to recognize text. The frames are taken from the video and processed to obtain the vehicle's license plate number. Localization, character, and vehicle color identification are used which helps in locating the vehicle faster.