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A study on the development of an autonomous electrical safety management service using an IoT-based smart outlet

At present, individual households within a multi-family residential are at susceptible to electrical accidents. As if in a blind spot, they cannot be covered under electrical safety management. This paper presents issues about an autonomous electrical safety management service which uses smart outle...

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Bibliographic Details
Published in:International journal of electrical engineering & education 2021-04, Vol.58 (2), p.168-178
Main Authors: Lee, Ki-Yeon, Moon, Hyun-Wook, Kim, Dong-Woo, Lim, Young-Bae, Ryu, In-Ho
Format: Article
Language:English
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Summary:At present, individual households within a multi-family residential are at susceptible to electrical accidents. As if in a blind spot, they cannot be covered under electrical safety management. This paper presents issues about an autonomous electrical safety management service which uses smart outlets to ensure electrical safety for individual households. Risk factors surrounding electrical incidents occurring in a mashup tech-based environment were analyzed and a smart outlet equipped with a prediction technique was developed. In addition to this, an autonomous electrical safety management service scenario was developed to handle mechanical failures in autonomous electrical safety devices which run on IoT-based smart outlets. By utilizing such an autonomous electrical safety management service model, technology for electrical safety security was developed for individual households or each residential unit in multi-dwelling unit. The correlation among voltage, current, and zero phase current was analyzed to identify the risk factors of electrical accidents and to predict accidents. In order to detect arc faults, a new prediction technique was developed. The technique is based on the mashup technology after analyzing waveform and FFT derived from the correlation among voltage, current, and zero phase current. In particular, the techniques applied to analyze nonlinear models such as an arc fault show the diversity in the application areas of traditional fast fourier transform (FFT) algorithms. Furthermore, by using such a technique for electrical accident prediction, an autonomous electrical safety management model was developed. Thus, a measure to ensure micro-grid electrical safety was presented. There is the hope that this development of the management technique for individual households in connection with the fourth industrial revolution would contribute to electrical safety.
ISSN:0020-7209
2050-4578
DOI:10.1177/0020720918822753