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Real-time and contactless measurements of thermal discomfort based on human poses for energy efficient control of buildings
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. School of Building Services Science and Engineering, Xi'an University of Architecture and Technology, Xi'an, China.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.ORCID iD: 0000-0002-8704-8538
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2019 (English)In: Building and Environment, ISSN 0360-1323, E-ISSN 1873-684X, Vol. 162, article id 106284Article in journal (Refereed) Published
Abstract [en]

Individual thermal discomfort perception gives important feedback signals for energy efficient control of building heating, ventilation and air conditioning systems. However, there is few effective method to measure thermal discomfort status of occupants in a real-time and contactless way. A novel method based on contactless measurements of human thermal discomfort status was presented. Images of occupant poses, which are related to thermoregulation mechanisms, were captured by a digital camera and the corresponding 2D coordinates were obtained. These poses were converted into skeletal configurations. An algorithm was developed to recognize different poses related to thermal discomfort, such as hugging oneself or wiping sweat off the brow. The algorithm could recognize twelve thermal discomfort related human poses. These poses were derived from a questionnaire survey of 369 human subjects. Some other human subjects participated in the validation experiments of the proposed method. All twelve thermal discomfort related poses can be recognized effectively.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 162, article id 106284
Keywords [en]
Contactless measurement, Thermal discomfort, Human pose, Machine learning
National Category
Building Technologies
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-163213DOI: 10.1016/j.buildenv.2019.106284ISI: 000484514400018Scopus ID: 2-s2.0-85070109030OAI: oai:DiVA.org:umu-163213DiVA, id: diva2:1350163
Available from: 2019-09-10 Created: 2019-09-10 Last updated: 2019-11-14Bibliographically approved

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Yang, BinOlofsson, Thomas

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CiteExportLink to record
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  • apa
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