• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/
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A Study on Development of App-Based Electric Fire Prediction System


Young-Kwan Choi, Eung-Kwon Kim, Journal of Internet Computing and Services, Vol. 14, No. 4, pp. 85-90, Aug. 2013
10.7472/jksii.2013.14.4.85, Full Text:  HTML
Keywords: Electric Fire Prediction System, arc detection, DSP(Digital Signal Processor), Smart phone App

Abstract

Currently, the electric fire prediction system uses PIC(Peripheral Interface Controller) for controller microprocessor. PIC has a slower computing speed than DSP does, so its real-time computing ability is inadequate. So with the basic characteristics waveform during arc generation as the standard reference, the comparison to this reference is used to predict and alarm electric fire from arc. While such alarm can be detected and taken care of from a remote central server, that prediction error rate is high and remote control in mobile environment is not available. In this article, the arc detection of time domain and frequency domain and wavelet-based adaptation algorithm executing the adaptation algorithm in conversion domain were applied to develop an electric fire prediction system loaded with new real-time arc detection algorithm using DSP. Also, remote control was made available through iPhone environment-based app development which enabled remote monitoring for arc's electric signal and power quality, and its utility was verified.


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Cite this article
[APA Style]
Choi, Y. & Kim, E. (2013). A Study on Development of App-Based Electric Fire Prediction System. Journal of Internet Computing and Services, 14(4), 85-90. DOI: 10.7472/jksii.2013.14.4.85.

[IEEE Style]
Y. Choi and E. Kim, "A Study on Development of App-Based Electric Fire Prediction System," Journal of Internet Computing and Services, vol. 14, no. 4, pp. 85-90, 2013. DOI: 10.7472/jksii.2013.14.4.85.

[ACM Style]
Young-Kwan Choi and Eung-Kwon Kim. 2013. A Study on Development of App-Based Electric Fire Prediction System. Journal of Internet Computing and Services, 14, 4, (2013), 85-90. DOI: 10.7472/jksii.2013.14.4.85.