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Published in:
2019 | OriginalPaper | Chapter
Insights into Unsupervised Holiday Detection from Low-Resolution Smart Metering Data
Authors : Günther Eibl, Sebastian Burkhart, Dominik Engel
Published in: Information Systems Security and Privacy
Publisher: Springer International Publishing
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Abstract
Recently, first methods for holiday detection from unsupervised low-resolution smart metering data have been presented. However, due to the unsupervised nature of the problem, previous work only applied the algorithms on a few typical cases and lacks a systematic validation. This paper systematically validates the existing algorithm by visual inspection and shows that numerous cases exist, where implicit assumptions are not met and the methods fail. Moreover, it proposes a new, very simple rule-based method which is in principle able to overcome these problems. This method should be seen as a first step towards improvement, since it is not automated and needs a moderate amount of human intervention for each household.