Understanding occupants’ thermal comfort is essential for the effective operation of Heating, Ventilation, and Air Conditioning (HVAC) systems. Existing studies of the “human-in-the-loop” HVAC control generally suffer from: (1) excessive reliance on cumbersome human feedback; and (2) intrusiveness caused by conventional data collection methods. To address these limitations, this paper investigates the low-cost thermal camera as a non-intrusive approach to assess thermal comfort in real time using facial skin temperature. The framework developed can automatically detect occupants, extract facial regions, measure skin temperature, and interpret thermal comfort with minimal interruption or participation of occupants. The framework is validated using the facial skin temperature collected from twelve occupants. Personal comfort models trained from different machine learning algorithms are compared and results show that Random Forest model can achieve an accuracy of 85% and also suggest that the skin temperature of ears, nose, and cheeks are most indicative of thermal comfort.
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Flexible and Stretchable 3ω Sensors for Thermal Characterization of Human Skin
Characterization of the thermal properties of the surface and subsurface structures of the skin can reveal the degree of hydration, the rate of blood flow in near‐surface micro‐ and macrovasculature, and other important physiological information of relevance to dermatological and overall health status. Here, a soft, stretchable thermal sensor, based on the so‐called three omega (i.e., 3ω) method, is introduced for accurate characterization of the thermal conductivity and diffusivity of materials systems, such as the skin, which can be challenging to measure using established techniques. Experiments on skin at different body locations and under different physical states demonstrate the possibilities. Systematic studies establish the underlying principles of operation in these unusual systems, thereby allowing rational design and use, through combined investigations based on analytical modeling, experimental measurements, and finite element analysis. The findings create broad opportunities for 3ω methods in biology, with utility ranging from the integration with surgical tools or implantable devices to noninvasive uses in clinical diagnostics and therapeutics.
more » « less- NSF-PAR ID:
- 10026458
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Functional Materials
- Volume:
- 27
- Issue:
- 26
- ISSN:
- 1616-301X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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