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논문 기본 정보

자료유형
학술저널
저자정보
Rifqi Muhammad Fikri (창원대학교) 황민태 (창원대학교)
저널정보
아태인문사회융합기술교류학회 아시아태평양융합연구교류논문지 아시아태평양융합연구교류논문지 제6권 제10호
발행연도
2020.1
수록면
137 - 146 (10page)

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This paper proposes a system that aimed to solve the lack of a charging station infrastructure by providing waiting time information to electric vehicle (EV) drivers for optimal charging options. This system determines the number of vehicle movements, such as entering or leaving the charging station in real-time. Furthermore, the Changwon National University area's charging station is simulated with a PC server and camera as the real-time video input; the OpenCV and MobileNet SSD object detection network is used to detect and track vehicle movements in the charging station, and the Firebase real-time database is used as the server. For the mobile application, maps featured with Kakao Maps API in the user interface are installed. In addition to the information regarding the current status of the charging station, a prediction system with Support Vector Regression (SVR) was added so that EV drivers can schedule charging ahead of time. Therefore, the proposed system aimed to assist EV drivers in navigation and reduce waiting times for charging. The simulation was conducted to evaluate the proposed system performance and got an average time-response result of 7.77 seconds from the moment EVs were detected until it was displayed in the mobile application interface.

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