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dc.contributor.authorSaralegui, Unai
dc.contributor.authorAntón, Miguel
dc.contributor.authorArbelaitz, Olatz
dc.contributor.authorMuguerza, Javier
dc.date.accessioned2019-01-24T14:33:21Z
dc.date.available2019-01-24T14:33:21Z
dc.date.issued2019
dc.identifier.citationSaralegui, Unai, Miguel Antón, Olatz Arbelaitz, and Javier Muguerza. “Smart Meeting Room Usage Information and Prediction by Modelling Occupancy Profiles.” Sensors 19, no. 2 (January 16, 2019): 353. doi:10.3390/s19020353.en
dc.identifier.issn1424-3210en
dc.identifier.urihttp://hdl.handle.net/11556/675
dc.description.abstractThe monitoring of small houses and rooms has become possible due to the advances in IoT sensors, actuators and low power communication protocols in the last few years. As buildings are one of the biggest energy consuming entities, monitoring them has great interest for trying to avoid non-necessary energy waste. Moreover, human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, so the ability to monitor and predict actions as opening windows, using rooms, etc. is gaining attention to develop stronger models which may lead to reduce the overall energy consumption of buildings, considering buildings thermal inertia and additional capabilities. In this paper, a case study is described in which four meeting rooms have been monitored to obtain information about the usage of the rooms and later use it to predict their future usage. The results show the possibility to deploy a simple and non-intrusive sensing system whose output could be used to develop advanced control strategies.en
dc.description.sponsorshipThis work was partially supported by the Department of Education, Universities and Research of the Basque Government (ADIAN research group, grant IT980-16) and by the Ministry of Economy and Competitiveness of the Spanish Government and the European Regional Development fund- ERDF (PhysComp project, TIN2017-85409-P).en
dc.language.isoengen
dc.publisherMDPIen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleSmart Meeting Room Usage Information and Prediction by Modelling Occupancy Profilesen
dc.typearticleen
dc.identifier.doi10.3390/s19020353en
dc.rights.accessRightsopenAccessen
dc.subject.keywordsBuildingsen
dc.subject.keywordsAmbient intelligenceen
dc.subject.keywordsOccupancy detectionen
dc.subject.keywordsBehaviour modellingen
dc.subject.keywordsSensor networksen
dc.subject.keywordsSmart meeting roomen
dc.subject.keywordsInternet of Things (IoT)en
dc.identifier.essn1424-8220en
dc.issue.number2en
dc.journal.titleSensorsen
dc.page.initial353en
dc.volume.number19en


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    Attribution 4.0 InternationalExcept where otherwise noted, this item's license is described as Attribution 4.0 International