Anomaly detection for an elderly personwatching system using multiple power consumption models

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We propose an anomaly detection method for watching elderly people using only the power data acquired by a smart meter. In a conventional system that uses only power data, a warning is issued if the power consumption does not increase after the wake-up time or when the amount of power does not change for a long time. These methods need to set the wake-up time and power threshold for each user. Furthermore, wrong warnings are issued while residents are out of the home. In our method, multiple common power consumption models are created for each household for each short time zone, and a watching system is constructed by regarding the gaps between these models and newly observed data as anomaly values. This can be automatically applied to various situations such as "during sleep," "during home activity" and "time zone for frequently going out in the daytime.

Original languageEnglish
Title of host publicationICPRAM 2017 - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods
EditorsMaria De De Marsico, Gabriella Sanniti di Baja, Ana Fred
PublisherSciTePress
Pages669-675
Number of pages7
ISBN (Electronic)9789897582226
DOIs
Publication statusPublished - 2017
Event6th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2017 - Porto, Portugal
Duration: Feb 24 2017Feb 26 2017

Publication series

NameICPRAM 2017 - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods
Volume2017-January

Conference

Conference6th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2017
CountryPortugal
CityPorto
Period2/24/172/26/17

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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