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dc.contributor.authorTroncoso Pastoriza, Francisco Manuel 
dc.contributor.authorMartínez Comesaña, Miguel 
dc.contributor.authorOgando Martínez, Ana 
dc.contributor.authorLópez Gómez, Javier 
dc.contributor.authorEguía Oller, Pablo 
dc.contributor.authorFebrero Garrido, Lara 
dc.date.accessioned2022-11-23T13:47:43Z
dc.date.available2022-11-23T13:47:43Z
dc.date.issued2022-07
dc.identifier.citationAutomation in Construction, 139, 104261 (2022)spa
dc.identifier.issn09265805
dc.identifier.urihttp://hdl.handle.net/11093/4131
dc.descriptionFinanciaciado para publicación en acceso aberto: Universidade de Vigo/CISUG
dc.description.abstractProviding accurate information about the indoor environmental quality (IEQ) conditions inside building spaces is essential to assess the comfort levels of their occupants. These values may vary inside the same space, especially for large zones, requiring many sensors to produce a fine-grained representation of the space conditions, which increases hardware installation and maintenance costs. However, sound interpolation techniques may produce accurate values with fewer input points, reducing the number of sensors needed. This work presents a platform to automate this accurate IEQ representation based on a few sensor devices placed across a large building space. A case study is presented in a research centre in Spain using 8 wall-mounted devices and an additional moving device to train a machine learning model. The system yields accurate results for estimations at positions and times never seen before by the trained model, with relative errors between 4% and 10% for the analysed variables.en
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades | Ref. RTI2018-096296-B-C2spa
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades | Ref. FPU17/ 01834spa
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades | Ref. FPU19/01187spa
dc.description.sponsorshipUniversidad de Vigo | Ref. 00VI 131H 641.02spa
dc.language.isoengspa
dc.publisherAutomation in Constructionspa
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096296-B-C2/ES
dc.relationinfo:eu-repo/grantAgreement/MECD/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FPU17/01834/ES
dc.relationinfo:eu-repo/grantAgreement/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FPU19/01187/ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleIoT-based platform for automated IEQ spatio-temporal analysis in buildings using machine learning techniquesen
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.identifier.doi10.1016/j.autcon.2022.104261
dc.identifier.editorhttps://linkinghub.elsevier.com/retrieve/pii/S0926580522001340spa
dc.publisher.departamentoEnxeñaría mecánica, máquinas e motores térmicos e fluídosspa
dc.publisher.grupoinvestigacionGTE (Grupo de Tecnoloxía Enerxética)spa
dc.subject.unesco3305 Tecnología de la Construcciónspa
dc.subject.unesco3305.90 Transmisión de Calor en la Edificaciónspa
dc.date.updated2022-11-16T13:08:40Z
dc.computerCitationpub_title=Automation in Construction|volume=139|journal_number=|start_pag=104261|end_pag=spa


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