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Title	Design & Implementation Of A Vehicle Detection And Tracking System Utilizing Yolov8 And Google Maps Api
ID_Doc	18406
Authors	Mhatre S.; Deshpande V.; Subhedar J.
Year	2024
Published	1st International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024
DOI	http://dx.doi.org/10.1109/ICECCC61767.2024.10593927
Abstract	This research paper presents a robust vehicle detection and tracking system that effectively leverages the powerful YOLOv8 object detection algorithm in conjunction with the Google Maps API. The proposed system aims to accurately identify and track vehicles, providing valuable insights for diverse applications such as vehicle tracing and surveillance. Through the seamless integration of YOLOv8 and the Google Maps API, the system demonstrates efficient vehicle information extraction from video streams, enabling intuitive visualization and mapping of detected vehicles on a geographic platform. Experimental evaluations affirm the system's effectiveness in accurate vehicle detection and tracking, highlighting its potential as a valuable tool for surveillance-related applications for smart cities. The experimental evaluations conducted on a standardized dataset demonstrate the system's capability to achieve an average vehicle detection accuracy of 95 % and a tracking efficiency with an aver-age processing time of 100 milliseconds per frame. These results underscore the practical viability and real-world applicability of the proposed system in enhancing transportation management and surveillance operations. © 2024 IEEE.
Author Keywords	Frame Cropping; Google Maps; OCR; Vehicle Detection and Tracking; Yolov8

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