2011 | OriginalPaper | Buchkapitel
Classification of Household Devices by Electricity Usage Profiles
verfasst von : Jason Lines, Anthony Bagnall, Patrick Caiger-Smith, Simon Anderson
Erschienen in: Intelligent Data Engineering and Automated Learning - IDEAL 2011
Verlag: Springer Berlin Heidelberg
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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.