Fault detection for binary sensors in smart home environments

Juan Ye, Graeme Stevenson, Simon Dobson

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

10 Citations (Scopus)

Abstract

Experiments in assisted living confirm that such systems can provide context-aware services that enable occupants to remain active and independent. They also demonstrate that abnormal sensor events hamper the correct identification of critical (and potentially life-threatening) situations, and that existing learning, estimation, and time-based approaches are inaccurate and inflexible when applied to multiple people sharing a living space. We propose a technique that integrates the semantics of sensor readings with statistical outlier detection. We evaluate the technique against four real-world datasets that include multiple individuals, and show consistent rates of anomaly detection across different environments.
Original languageEnglish
Title of host publication2015 IEEE International Conference on Pervasive Computing and Communications (PerCom)
PublisherIEEE Computer Society
Pages20-28
Number of pages9
DOIs
Publication statusPublished - 23 Mar 2015
EventIEEE International Conference on Pervasive Computing and Communications (PerCom 2015) - Renaissance St. Louis Grand Hotel, St Louis, Missouri, United States
Duration: 23 Mar 201527 Mar 2015

Conference

ConferenceIEEE International Conference on Pervasive Computing and Communications (PerCom 2015)
Country/TerritoryUnited States
CitySt Louis, Missouri
Period23/03/1527/03/15

Keywords

  • Wireless sensor network
  • Fault detection
  • Activity recognition
  • Ontologies

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