Vehicle Monitoring System Using Object Detection 


Vol. 47,  No. 7, pp. 978-985, Jul.  2022
10.7840/kics.2022.47.7.978


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  Abstract

This paper designs a system that monitors traffic conditions and collects reliable traffic information using real-time object recognition of YOLOv5. The designed system uses only one camera and one AI board, making it easy to install on the move, and does not require professionals to install measuring equipment, solving the economic drawbacks of the existing traffic information collection system. Since YOLov5 is used for object recognition, it exhibits higher performance in speed and accuracy than CNN techniques that process images while moving filters sequentially. Therefore, reliable information collection will be possible, and the collected information is automatically stored in the server. By implementing this system, it is not only useful for estimating future traffic volume, collecting data necessary for road planning and management, but also expected to efficiently identify real-time traffic volume and reduce system costs.

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  Cite this article

[IEEE Style]

J. Jang, E. Park, J. Hwang, Y. Yoo, "Vehicle Monitoring System Using Object Detection," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 7, pp. 978-985, 2022. DOI: 10.7840/kics.2022.47.7.978.

[ACM Style]

Jin-ho Jang, Eun-young Park, Jeongsoo Hwang, and Younghwan Yoo. 2022. Vehicle Monitoring System Using Object Detection. The Journal of Korean Institute of Communications and Information Sciences, 47, 7, (2022), 978-985. DOI: 10.7840/kics.2022.47.7.978.

[KICS Style]

Jin-ho Jang, Eun-young Park, Jeongsoo Hwang, Younghwan Yoo, "Vehicle Monitoring System Using Object Detection," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 7, pp. 978-985, 7. 2022. (https://doi.org/10.7840/kics.2022.47.7.978)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880