Learning occupancy in single person offices with mixtures of multi-lag Markov chains

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dc.contributor.author Manna, Carlo
dc.contributor.author Fay, Damien
dc.contributor.author Brown, Kenneth N.
dc.contributor.author Wilson, Nic
dc.date.accessioned 2014-02-18T15:52:35Z
dc.date.available 2014-02-18T15:52:35Z
dc.date.issued 2013-11
dc.identifier.citation MANNA, C., FAY, D., BROWN, K. N. & WILSON, N. 2013. Learning occupancy in single person offices with mixtures of multi-lag Markov chains. In: Proceedings 25th International Conference on Tools with Artificial Intelligence ICTAI 2013. Washington DC, USA, 4-6 Nov. Los Alamitos, California: IEEE Computer Society, pp. 151-158. en
dc.identifier.startpage 151 en
dc.identifier.endpage 158 en
dc.identifier.isbn 978-1-4799-2971-9
dc.identifier.issn 1082-3409
dc.identifier.uri http://hdl.handle.net/10468/1393
dc.identifier.doi 10.1109/ICTAI.2013.32
dc.description.abstract The problem of real-time occupancy forecastingfor single person offices is critical for energy efficient buildings which use predictive control techniques. Due to the highly uncertain nature of occupancy dynamics, the modeling and prediction of occupancy is a challenging problem. This paper proposes an algorithm for learning and predicting single occupant presence in office buildings, by considering the occupant behaviour as an ensemble of multiple Markov models at different time lags. This model has been tested using real occupancy data collected from PIR sensors installed in three different buildings and compared with state of the art methods, reducing the error rate by on average 5% over the best comparator method. en
dc.description.sponsorship Irish Research Council for Science Engineering and Technology (Enterprise Partnership Scheme); Science Foundation Ireland (SFI Research Cluster ITOBO 07.SRC.I1170); Science Foundation Ireland (08/PI/I1912); Intel Labs Europe (Enterprise Partnership Scheme) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher IEEE Computer Society en
dc.relation.ispartof ICTAI 2013 IEEE 25th International Conference on Tools with Artificial Intelligence, Washington DD, USA, 4-6 Nov 2013
dc.rights © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. en
dc.subject Markov chains en
dc.subject Occupancy prediction en
dc.subject Building control en
dc.title Learning occupancy in single person offices with mixtures of multi-lag Markov chains en
dc.type Conference item en
dc.internal.authorcontactother Nic Wilson, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: n.wilson@4c.ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2014-01-16T12:44:52Z
dc.description.version Accepted Version en
dc.internal.rssid 237168659
dc.contributor.funder Irish Research Council for Science, Engineering and Technology en
dc.contributor.funder Science Foundation Ireland en
dc.contributor.funder Intel Labs Europe en
dc.contributor.funder Intel Corporation en
dc.description.status Peer reviewed en
dc.internal.copyrightchecked No. !!CORA!! Accepted version and set statement. http://www.ieee.org/publications_standards/publications/rights/rights_policies.html en
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Washington DC en
dc.internal.placepublication Los Alamitos, California en
dc.internal.IRISemailaddress n.wilson@ucc.ie en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Strategic Research Cluster/07/SRC/I1170/IE/SRC ITOBO: Information and Communication Technology for Sustainable and Optimised Building Operation/ en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Principal Investigator Programme (PI)/08/IN.1/I1912/IE/The Development of Artificial intelligence Approaches for Preferences in Combinational Problems/ en


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