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Real-time and contactless measurements of thermal discomfort based on human poses for energy efficient control of buildings

Yang, Bin (author)
Umeå universitet,Institutionen för tillämpad fysik och elektronik,School of Building Services Science and Engineering, Xi'an University of Architecture and Technology, Xi'an, China,Xian Univ Architecture & Technol, Sch Bldg Serv Sci & Engn, Xian 710055, Shaanxi, Peoples R China.;Umea Univ, Dept Appl Phys & Elect, S-90187 Umea, Sweden.
Cheng, Xiaogang (author)
KTH,Skolan för elektroteknik och datavetenskap (EECS),Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing 210003, Jiangsu, Peoples R China.;Swiss Fed Inst Technol, Comp Vis Lab, CH-8092 Zurich, Switzerland.
Dai, Dengxin (author)
Swiss Fed Inst Technol, Comp Vis Lab, CH-8092 Zurich, Switzerland.
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Olofsson, Thomas, 1968- (author)
Umeå universitet,Institutionen för tillämpad fysik och elektronik,Umea Univ, Dept Appl Phys & Elect, S-90187 Umea, Sweden.
Li, Haibo (author)
KTH,Medieteknik och interaktionsdesign, MID
Meier, Alan (author)
Univ Calif Davis, Energy & Efficiency Inst, Davis, CA 95616 USA.
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 (creator_code:org_t)
Elsevier, 2019
2019
English.
In: Building and Environment. - : Elsevier. - 0360-1323 .- 1873-684X. ; 162
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • 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.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Husbyggnad (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Building Technologies (hsv//eng)

Keyword

Contactless measurement
Thermal discomfort
Human pose
Machine learning
datalogi
Computer Science

Publication and Content Type

ref (subject category)
art (subject category)

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