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dc.contributor.authorSaralegui, Unai
dc.contributor.authorAnton, Miguel Angel
dc.contributor.authorOrdieres-Mere, Joaquin
dc.date.accessioned2017-09-14T11:26:41Z
dc.date.available2017-09-14T11:26:41Z
dc.date.issued2017
dc.identifier.citationWSEAS Transactions on Environment and Development, ISSN / E-ISSN: 1790-5079 / 2224-3496, Volume 13, 2017, Art. #33, pp. 327-334en
dc.identifier.issn1790-5079en
dc.identifier.urihttp://hdl.handle.net/11556/417
dc.description.abstractThis paper describes a procedure to gain additional information from an already existing infrastructure primarily designed for other purposes. The deployed sensor network consists of wirelessly communicated indoor climate monitoring sensors, for which it is tried to extend its usage by determining occupancy in the room they are located, in that way the system provides a higher level aspect of the house usage. An elderly caring institution’s building has been monitored for one year obtaining data about temperature, relative humidity and CO2 levels from five different rooms. Such data shows some interesting patterns as the air flow between the rooms which should be considered in any real case scenario. The data has been used to train some machine learning models, which show acceptable quality overall suggesting to use this kind of sensing equipment to perform an occupancy monitoring non-intrusively. The acquired knowledge could bring additional opportunities in the care of the elderly, especially for specific diseases that are usually accompanied by changes in patterns of behaviour. By using the occupancy status it could be possible to determine changes in the daily patterns in that segment of the population which could be an indicative of the initial states of a disease or a worsening in it.en
dc.language.isoengen
dc.publisherWorld Scientific and Engineering Academy and Society (WSEAS)en
dc.titleTaking advantage of an existing indoor climate monitorization for measuring occupancyen
dc.typejournal articleen
dc.isiNoen
dc.rights.accessRightsopen accessen
dc.subject.keywordsDomestic occupancyen
dc.subject.keywordsClimate sensorsen
dc.subject.keywordsPattern analysisen
dc.subject.keywordsHealth monitoringen
dc.subject.keywordsSmart buildingsen
dc.subject.keywordsMachine learningen
dc.subject.keywordsInternet of thingsen
dc.identifier.essn2224-3496en
dc.journal.titleWSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENTen
dc.page.final334en
dc.page.initial327en
dc.volume.number13en


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