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Monitoring Thermal Comfort Level of Commercial Buildings' Occupants in a Hot-Humid Climate Country Using K-nearest Neighbors Model

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dc.citedby1
dc.contributor.authorHani Mohamed Salleh F.en_US
dc.contributor.authorBinti Saripuddin M.en_US
dc.contributor.authorid26423229000en_US
dc.contributor.authorid57220056898en_US
dc.date.accessioned2023-05-29T08:07:35Z
dc.date.available2023-05-29T08:07:35Z
dc.date.issued2020
dc.descriptionClimate models; Climatology; Motion compensation; Nearest neighbor search; Office buildings; Predictive analytics; Thermal comfort; Adaptive thermal comfort; Building energy performance; Commercial building; Hot humid climate; K-nearest neighbors; Predictive modeling; Temperate climate; Thermal comfort level; Monitoringen_US
dc.description.abstractThis paper presents a thermal comfort monitoring system that able to simulate the thermal comfort level of commercial building occupants in a hot-humid climate country. The main benefit of this monitoring system is to reduce the energy usage by observing the actual thermal comfort value of the building constantly. The predictive model proposed in this research aims to optimize building energy performance without sacrificing occupant thermal comfort. The system was developed based on KNN (K-nearest neighbors) model using the six thermal comfort factors. The data used for evaluating our proposed model was obtained from a study of adaptive thermal comfort of lecture halls in Malaysia universities. Another set of data is also used to assess the suitability of the proposed model when applied to data of non-hot humid climate (temperate climates). As a result, the proposed monitoring system scores 72.97% of accuracy outperforms PMV that scores 43% accuracy. As for non-hot humid climate country dataset, PMV outperforms our proposed monitoring system, with 35.13% accuracy while the proposed monitoring system only reach up to 18.19%. The results of the experiment reveal that the recommended model is only suitable for use on buildings in hot-humid climate country and may not be suitable for buildings in temperate climate country. � 2020 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9233145
dc.identifier.doi10.1109/ICPRE51194.2020.9233145
dc.identifier.epage215
dc.identifier.scopus2-s2.0-85096655966
dc.identifier.spage209
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85096655966&doi=10.1109%2fICPRE51194.2020.9233145&partnerID=40&md5=8142a6838f09d5a8cbb5d102f7877b49
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25249
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2020 5th International Conference on Power and Renewable Energy, ICPRE 2020
dc.titleMonitoring Thermal Comfort Level of Commercial Buildings' Occupants in a Hot-Humid Climate Country Using K-nearest Neighbors Modelen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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