A parallel multi-appliance recognition for smart meter

Lien Chun Wang, Wei Ting Cho, Yu Sheng Chiu, Chin-Feng Lai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This study proposes a non-invasive smart meter system that considers the power use habits of users unfamiliar with electric appliances, and can be used by inserting the smart meter into an electrical circuit. This study also creates a database mechanism, appliance recognition classification, and a waveform recognition method, in order to solve the large data volume problem in current appliance recognition systems. In comparison to other appliance recognition systems, the low-end embedded system chip used in this study has low power consumption, as well as high expandability and ease of use. This experiment is different from the research environments of other appliance recognition systems by considering parallel multi-appliance recognition and general users' habit of using power. This study will not make any assumption of power utilization in the experiment. The total system recognition rate is 84.42%, and the total recognition rate of a single electric appliance is 93.82%, proving the high feasibility of this study.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013
PublisherIEEE Computer Society
Pages475-480
Number of pages6
ISBN (Print)9781479933815
DOIs
Publication statusPublished - 2013 Jan 1
Event11th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2013 - Chengdu, Sichuan, China
Duration: 2013 Dec 212013 Dec 22

Publication series

NameProceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013

Other

Other11th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2013
CountryChina
CityChengdu, Sichuan
Period13-12-2113-12-22

Fingerprint

Electric appliances
Smart meters
Electric power utilization
Embedded systems
Experiments
Networks (circuits)

All Science Journal Classification (ASJC) codes

  • Software

Cite this

Wang, L. C., Cho, W. T., Chiu, Y. S., & Lai, C-F. (2013). A parallel multi-appliance recognition for smart meter. In Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013 (pp. 475-480). [6844410] (Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013). IEEE Computer Society. https://doi.org/10.1109/DASC.2013.110
Wang, Lien Chun ; Cho, Wei Ting ; Chiu, Yu Sheng ; Lai, Chin-Feng. / A parallel multi-appliance recognition for smart meter. Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013. IEEE Computer Society, 2013. pp. 475-480 (Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013).
@inproceedings{e7900feb30c0472e853f521aeb7e5810,
title = "A parallel multi-appliance recognition for smart meter",
abstract = "This study proposes a non-invasive smart meter system that considers the power use habits of users unfamiliar with electric appliances, and can be used by inserting the smart meter into an electrical circuit. This study also creates a database mechanism, appliance recognition classification, and a waveform recognition method, in order to solve the large data volume problem in current appliance recognition systems. In comparison to other appliance recognition systems, the low-end embedded system chip used in this study has low power consumption, as well as high expandability and ease of use. This experiment is different from the research environments of other appliance recognition systems by considering parallel multi-appliance recognition and general users' habit of using power. This study will not make any assumption of power utilization in the experiment. The total system recognition rate is 84.42{\%}, and the total recognition rate of a single electric appliance is 93.82{\%}, proving the high feasibility of this study.",
author = "Wang, {Lien Chun} and Cho, {Wei Ting} and Chiu, {Yu Sheng} and Chin-Feng Lai",
year = "2013",
month = "1",
day = "1",
doi = "10.1109/DASC.2013.110",
language = "English",
isbn = "9781479933815",
series = "Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013",
publisher = "IEEE Computer Society",
pages = "475--480",
booktitle = "Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013",
address = "United States",

}

Wang, LC, Cho, WT, Chiu, YS & Lai, C-F 2013, A parallel multi-appliance recognition for smart meter. in Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013., 6844410, Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013, IEEE Computer Society, pp. 475-480, 11th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2013, Chengdu, Sichuan, China, 13-12-21. https://doi.org/10.1109/DASC.2013.110

A parallel multi-appliance recognition for smart meter. / Wang, Lien Chun; Cho, Wei Ting; Chiu, Yu Sheng; Lai, Chin-Feng.

Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013. IEEE Computer Society, 2013. p. 475-480 6844410 (Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A parallel multi-appliance recognition for smart meter

AU - Wang, Lien Chun

AU - Cho, Wei Ting

AU - Chiu, Yu Sheng

AU - Lai, Chin-Feng

PY - 2013/1/1

Y1 - 2013/1/1

N2 - This study proposes a non-invasive smart meter system that considers the power use habits of users unfamiliar with electric appliances, and can be used by inserting the smart meter into an electrical circuit. This study also creates a database mechanism, appliance recognition classification, and a waveform recognition method, in order to solve the large data volume problem in current appliance recognition systems. In comparison to other appliance recognition systems, the low-end embedded system chip used in this study has low power consumption, as well as high expandability and ease of use. This experiment is different from the research environments of other appliance recognition systems by considering parallel multi-appliance recognition and general users' habit of using power. This study will not make any assumption of power utilization in the experiment. The total system recognition rate is 84.42%, and the total recognition rate of a single electric appliance is 93.82%, proving the high feasibility of this study.

AB - This study proposes a non-invasive smart meter system that considers the power use habits of users unfamiliar with electric appliances, and can be used by inserting the smart meter into an electrical circuit. This study also creates a database mechanism, appliance recognition classification, and a waveform recognition method, in order to solve the large data volume problem in current appliance recognition systems. In comparison to other appliance recognition systems, the low-end embedded system chip used in this study has low power consumption, as well as high expandability and ease of use. This experiment is different from the research environments of other appliance recognition systems by considering parallel multi-appliance recognition and general users' habit of using power. This study will not make any assumption of power utilization in the experiment. The total system recognition rate is 84.42%, and the total recognition rate of a single electric appliance is 93.82%, proving the high feasibility of this study.

UR - http://www.scopus.com/inward/record.url?scp=84904469712&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84904469712&partnerID=8YFLogxK

U2 - 10.1109/DASC.2013.110

DO - 10.1109/DASC.2013.110

M3 - Conference contribution

SN - 9781479933815

T3 - Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013

SP - 475

EP - 480

BT - Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013

PB - IEEE Computer Society

ER -

Wang LC, Cho WT, Chiu YS, Lai C-F. A parallel multi-appliance recognition for smart meter. In Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013. IEEE Computer Society. 2013. p. 475-480. 6844410. (Proceedings - 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, DASC 2013). https://doi.org/10.1109/DASC.2013.110