과적 의심차량 추적에 관한 방법 연구 A Study on the Method of Tracking Suspected Vehicles with Overload
한국기계기술학회지
(韓國機械技術學會誌)
제25권 제6호
(2023.12)
pp.979-984
pp.979-984
한국기계기술학회
(Korean Society of Mechanical Technology)
초록
In contemporary society, traffic concerns and road safety are of paramount importance. Overloading and improper loading significantly jeopardize road safety. Leveraging AI Hub's CCTV traffic videos, overloading hazard data, and Yeosu Sunsin Bridge HS-WIM data from Jeollanam-do, we've crafted detection models. These models facilitate the development of a vehicle detection system calibrated for specific scenarios, making the detection of overloading and loading discrepancies more accessible. Such a system promises to streamline detection operations while substituting manual efforts with AI, thereby economizing on both time and resources.
저자