Automatic estimation of clothing insulation rate and metabolic rate for dynamic thermal comfort assessment
Existing heating, ventilation, and air-conditioning systems have difficulties in considering occupants’ dynamic thermal needs, thus resulting in overheating or overcooling with huge energy waste. This situation emphasizes the importance of occupant-oriented microclimate control where dynamic individ...
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Published in | Pattern analysis and applications : PAA Vol. 25; no. 3; pp. 619 - 634 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
London
Springer London
01.08.2022
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Summary: | Existing heating, ventilation, and air-conditioning systems have difficulties in considering occupants’ dynamic thermal needs, thus resulting in overheating or overcooling with huge energy waste. This situation emphasizes the importance of occupant-oriented microclimate control where dynamic individual thermal comfort assessment is the key. Therefore, in this paper, a vision-based approach to estimate individual clothing insulation rate (
I
cl
) and metabolic rate (
M
), the two critical factors to assess personal thermal comfort level, is proposed. Specifically, with a thermal camera as the input source, a convolutional neural network (CNN) is implemented to recognize an occupant’s clothes type and activity type simultaneously. The clothes type then helps to differentiate the skin region from the clothing-covered region, allowing to calculate the skin temperature and the clothes temperature. With the two recognized types and the two computed temperatures,
I
cl
and
M
can be estimated effectively. In the experimental phase, a novel thermal dataset is introduced, which allows evaluations of the CNN-based recognizer module, the skin and clothes temperatures acquisition module, as well as the
I
cl
and
M
estimation module, proving the effectiveness and automation of the proposed approach. |
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ISSN: | 1433-7541 1433-755X |
DOI: | 10.1007/s10044-021-00961-5 |