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http://dx.doi.org/10.9717/kmms.2020.23.7.870

A Study On Power Data Analysis And Risk Situation Prediction Using Smart Plug  

Jung, Se Hoon (School of Creative Convergence, Andong National University)
Kim, June Young (Dept. of Multimedia Eng., Sunchon National University)
Park, Jun (Dept. of Multimedia Eng., Sunchon National University)
Jang, Seung Min (NARAE INFO. Co., Ltd.)
Sim, Chun Bo (Dept. of Multimedia Eng., Sunchon National University)
Publication Information
Journal of Korea Multimedia Society / v.23, no.7, 2020 , pp. 870-882 More about this Journal
Abstract
It is that failure of equipment at the factory site causes personal injury and property damage. We are required a real-time monitoring and risk forecasting techniques to prevent for equipment failure. In this paper, we proposed a 3-phase smart plug and real-time monitoring system that can be used in factories, and collected environmental information and power information using a smart plug to analyze the data. In order to analyze the correlation between the risk situation and the collected data, we predicted the risk situation using Linear Regression, SVM, and ANN algorithms. As a result, the SVM and ANN algorithms obtained high predictive accuracy and developed a mobile app that could use it to check the risk forecast results.
Keywords
Smart Plug; Smart Factory; Data Analysis; Risk Situation Prediction;
Citations & Related Records
Times Cited By KSCI : 11  (Citation Analysis)
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