Household appliance recognition through a Bayes classification model

Da Yan, Yuan Jin, Hongsan Sun, Bing Dong, Zi Ye, Zhaoxuan Li, Yanping Yuan

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


With the acceleration of global warming and energy shortages, the smart grid has become the goal of power grid development, which makes intelligent household appliance control systems essential. To promote the integration of traditional household appliances into a new electrical system, this study focused on an appliance recognition algorithm applicable to traditional and typical household appliances. Using sequential appliance power consumption data from intelligent power sockets, this study generalized and extracted the characteristics of occupant behavior and power consumption of typical household appliances. A new recognition algorithm for household appliances, based on a Bayes classification model, is presented in this paper. Seven types of household appliances (refrigerator, electric cooker, air conditioner, television, laptop computer, washing machine, and water dispenser) were analyzed in 15 Beijing households. The proposed algorithm was proven to be applicable for appliance recognition.

Original languageEnglish (US)
Article number101393
JournalSustainable Cities and Society
StatePublished - Apr 2019
Externally publishedYes


  • Bayes classification
  • Household appliances
  • Occupant behavior
  • Recognition algorithm
  • Smart grid

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Civil and Structural Engineering
  • Renewable Energy, Sustainability and the Environment
  • Transportation


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