• DocumentCode
    598512
  • Title

    Integration of IoT Energy Management System with Appliance and Activity Recognition

  • Author

    Chin-Feng Lai ; Ying-Xun Lai ; Yang, L.T. ; Han-Chieh Chao

  • Author_Institution
    Inst. of Comput. Sci. & Inf. Eng., Nat. ILan Univ., Ilan, Taiwan
  • fYear
    2012
  • fDate
    20-23 Nov. 2012
  • Firstpage
    66
  • Lastpage
    71
  • Abstract
    The Internet of Things (IoT) extends and expands the range of the internet by interconnecting Internet and end device networks. As the raising of awareness about IoT, more and more application may applied for various areas. Especially, the development of intelligent energy saving becomes a new trend in all circles. This research integrated appliance and activity recognition mechanism for IoT energy management system. It presented a management service layer for the recognition of current household appliances, which not only establishes communication services among various appliances, and deduced human activity conducted for context data using Naive Bayes from the electric appliances in use and the variation of its states. Finally, the proposed system can automatically achieve energy management by controlling electric appliances.
  • Keywords
    Bayes methods; Internet of Things; domestic appliances; electrical products; energy conservation; energy management systems; Internet of Things; IoT energy management system service layer; Naive Bayes; activity recognition; appliance recognition; communication services; context data; electric appliances; energy saving; household appliance recognition; human activity; intelligent system development; Energy management; Home appliances; Humans; Internet; Protocols; Random variables; Vectors; Activity Recognition; Appliance Recognition; Energy Management; Internet of Things;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing and Communications (GreenCom), 2012 IEEE International Conference on
  • Conference_Location
    Besancon
  • Print_ISBN
    978-1-4673-5146-1
  • Type

    conf

  • DOI
    10.1109/GreenCom.2012.20
  • Filename
    6468296