Classification of Household Devices by Electricity Usage Profiles

  • Jason Lines
  • Anthony Bagnall
  • Patrick Caiger-Smith
  • Simon Anderson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6936)


This paper investigates how to classify household items such as televisions, kettles and refrigerators based only on their electricity usage profile every 15 minutes over a fixed interval of time. We address this time series classification problem through deriving a set of features that characterise the pattern of usage and the amount of power used when a device is on. We evaluate a wide range of classifiers on both the raw data and the derived feature set using both a daily and weekly usage profile and demonstrate that whilst some devices can be identified with a high degree of accuracy, others are very hard to disambiguate with this granularity of data.


time series classification electricity device classification 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jason Lines
    • 1
  • Anthony Bagnall
    • 1
  • Patrick Caiger-Smith
    • 2
  • Simon Anderson
    • 2
  1. 1.School of Computing SciencesUniversity of East AngliaUK
  2. 2.Green Energy OptionsHardwickUK

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