• DocumentCode
    2728108
  • Title

    An Intelligent System for Mining Usage Patterns from Appliance Data in Smart Home Environment

  • Author

    Yi-Cheng Chen ; Yu-Lun Ko ; Wen-Chih Peng

  • Author_Institution
    Dept. of Comput. Sci., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • fYear
    2012
  • fDate
    16-18 Nov. 2012
  • Firstpage
    319
  • Lastpage
    322
  • Abstract
    In the last decade, considerable concern has arisen over the electricity saving due to the issue of reducing greenhouse gases. Previous studies on usage pattern utilization mainly are focused on power disaggregation and appliance recognition. Little attention has been paid to utilizing pattern mining for the target of energy saving. In this paper, we develop an intelligent system which analyzes appliance usage to extract users´ behavior patterns in a smart home environment. With the proposed system, users can acquire the electricity consumption of each appliance for energy saving easily. In advance, if the electricity cost is high, users can observe the abnormal usage of appliances from the proposed system. Furthermore, we also apply our system on real-world dataset to show the practicability of mining usage pattern in smart home environment.
  • Keywords
    air pollution control; behavioural sciences; building management systems; data mining; domestic appliances; energy conservation; home automation; power consumption; appliance data; appliance recognition; appliance usage; electricity consumption; electricity cost; electricity saving; energy saving; greenhouse gas reduction; intelligent system; power disaggregation; smart home environment; usage pattern mining; usage pattern utilization; user behavior pattern extraction; Clustering algorithms; Data mining; Electricity; Energy conservation; Feature extraction; Home appliances; Smart homes; abnormal detection; energy saving; smart home; usage pattern;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Technologies and Applications of Artificial Intelligence (TAAI), 2012 Conference on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4673-4976-5
  • Type

    conf

  • DOI
    10.1109/TAAI.2012.54
  • Filename
    6395048