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The research of Automatic Classification of Products Using Smart Plug by Artificial Intelligence Technique

인공지능 기법으로 스마트 플러그를 이용한 제품 자동분류에 관한 연구

  • Son, Chang-Woo (Department of Electronic & Communication Eng, Korea Maritime University) ;
  • Lee, Sang-Bae (Department of Electronic & Communication Eng, Korea Maritime University)
  • Received : 2018.02.24
  • Accepted : 2018.05.24
  • Published : 2018.06.30

Abstract

The Smart plug is a device that connects between the outlet and the product at home, and it is an IoT type device that can drive energy saving and transmit information to the outside by power on / off control function and power measurement function. In this case, a smart plug that incorporates deep learning of intelligence technology that allows people to learn how to think about a computer, automatically classifies a product as it operates, and automatically tests the operating status of the washing machine by using input AC current pattern. Through this study, even if the product does not function as IoT, it can classify product type and operation state by smart plug connection alone, so we can draw a new paradigm of life pattern and energy saving in one family.

스마트 플러그는 가정집에서 콘센트와 제품 간 중간에 연결하는 장치로써, 전원 On/Off 제어 기능과 전력 측정 기능으로 에너지 절약을 유도하고 외부에 정보를 전송할 수 있는 IoT 기기를 말한다. 여기에 사람의 사고방식을 컴퓨터에 학습 시키는 인공지능 기술의 딥러닝을 스마트 플러그에 탑재하여, 입력 교류 전류 패턴을 이용하여 제품이 동작만 하면 어떤 제품인지 자동으로 분류하고 세탁기의 동작 상태를 자동으로 판단하는 시험을 하였다. 본 연구를 통해 제품이 IoT 기능이 안 되더라도 스마트 플러그 연결만으로도 제품의 종류와 동작 상태를 분류하므로, 한 가정의 생활패턴과 에너지 절감의 새로운 패러다임을 그릴 수 있을 것이다.

Keywords

References

  1. D. H. Ryu, "Networked Smart Plug System for Power Management of PC & Peripherals," Journal of the Korea Institute of Information and Communication Engineering, vol.16, no. 10, pp.2171-2176, Oct. 2012. https://doi.org/10.6109/jkiice.2012.16.10.2171
  2. Y. S. Kim, "Smart plug/home appliances spread User Experience(UX) Development Study" Sungkyunkwan University Industry Academia Collaboration Foundation, Technical Report, Sep. 2014.
  3. Google DeepMind Research Center AlphaGo, Mastering the ancient game of Go with Machine Learning.[Internet]. Available: https://reserch.googleblog.com/2016/01/alphago-mastering-ancient-game-of-go.httml.
  4. C. J. Seo "Smart electricity management system in homes using pattern analytically," M.S. thesis, Kwangwoon University, Korea 2013.
  5. W. S. Lee, S. H. Kim, J. Y. Ryu and T. W. Ban, "Fast Detection of Diseas in Livestock based on Deep Learning," Journal of the Korea Institute of Information and Communication Engineering. vol. 21, no. 4, pp. 1009-1015, Oct. 2017.
  6. G. Hinton, S. Osindero, "A Fast Learning Algorithm for Deep Belief Nets," Neural Computation, vol.18, no.7, pp. 1527-1554, May. 2006. https://doi.org/10.1162/neco.2006.18.7.1527
  7. Y. J. Kim, "Analysis of Image Big Data Using Deep Learning" Ph. D. dissertation, Chung Ang University, Korea 2017.
  8. S. David, H. Aja, M. Chris and G. Arthur, "Mastering the game of Go with deep neural network and tree search," Nature, vol. 529, pp. 484-489, Jan. 2016. https://doi.org/10.1038/nature16961