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dc.contributor.authorYe, Juan
dc.contributor.authorStevenson, Graeme
dc.contributor.authorDobson, Simon
dc.date.accessioned2015-04-28T14:31:05Z
dc.date.available2015-04-28T14:31:05Z
dc.date.issued2015-03-23
dc.identifier.citationYe , J , Stevenson , G & Dobson , S 2015 , Fault detection for binary sensors in smart home environments . in 2015 IEEE International Conference on Pervasive Computing and Communications (PerCom) . IEEE Computer Society , pp. 20-28 , IEEE International Conference on Pervasive Computing and Communications (PerCom 2015) , St Louis, Missouri , United States , 23/03/15 . https://doi.org/10.1109/PERCOM.2015.7146505en
dc.identifier.citationconferenceen
dc.identifier.otherPURE: 167420227
dc.identifier.otherPURE UUID: f6ce9571-3445-4759-abfa-c073ffbed292
dc.identifier.otherScopus: 84942627224
dc.identifier.otherORCID: /0000-0002-2838-6836/work/68280962
dc.identifier.otherORCID: /0000-0001-9633-2103/work/70234164
dc.identifier.otherWOS: 000380505100004
dc.identifier.urihttps://hdl.handle.net/10023/6588
dc.description.abstractExperiments 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.
dc.format.extent9
dc.language.isoeng
dc.publisherIEEE Computer Society
dc.relation.ispartof2015 IEEE International Conference on Pervasive Computing and Communications (PerCom)en
dc.rights© 2015. IEEE. This is the accepted mansucript of a conference paper originally submitted to the IEEE International Conference on Pervasive Computing and Communications, Fault detection for binary sensors in smart home environments Ye, J., Stevenson, G. & Dobson, S. 23 Mar 2015 IEEE International Conference on Pervasive Computing and Communications (PerCom 2015). IEEE Computer Society, available from http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000551en
dc.subjectWireless sensor networken
dc.subjectFault detectionen
dc.subjectActivity recognitionen
dc.subjectOntologiesen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectNDASen
dc.subject.lccQA75en
dc.titleFault detection for binary sensors in smart home environmentsen
dc.typeConference itemen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1109/PERCOM.2015.7146505
dc.identifier.urlhttp://www.percom.org/en


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