Design of Path Prediction Smart Street Lighting System on the Internet of Things

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Tae Yeun Kim Nam Hong Park
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Fuzzy System Motion Sensor Neural Network System Path Prediction System Smart City Smart Street Lighting
In this paper, we propose a system for controlling the brightness of street lights by predicting pedestrian paths, identifying the position of pedestrians with motion sensing sensors and obtaining motion vectors based on past walking directions, then predicting pedestrian paths through the route prediction smart street lighting system. In addition, by using motion vector data, the pre-treatment process using linear interpolation method and the fuzzy system and neural network system were designed in parallel structure to increase efficiency and the rough set was used to correct errors. It is expected that the system proposed in this paper will be effective in securing the safety of pedestrians and reducing light pollution and energy by predicting the path of pedestrians in the detection of movement of pedestrians and in conjunction with smart street lightings.
조선대학교 기초과학연구원
Tae Yeun Kim. (2019). Design of Path Prediction Smart Street Lighting System on the Internet of Things, 조선자연과학논문집 | Vol.12, No.1 p.14 ~ p.19
Laboratory article
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2019 > Vol.12, No.1
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