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http://dx.doi.org/10.13160/ricns.2019.12.1.14

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

Kim, Tae Yeun (SW Convergence Education Institute, Chosun University)
Park, Nam Hong (SW Convergence Education Institute, Chosun University)
Publication Information
Journal of Integrative Natural Science / v.12, no.1, 2019 , pp. 14-19 More about this Journal
Abstract
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.
Keywords
Fuzzy System; Motion Sensor; Neural Network System; Path Prediction System; Smart City; Smart Street Lighting;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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