skip to main content

Title: Non-invasive (non-contact) measurements of human thermal physiology signals and thermal comfort/discomfort poses-A review.
Heating, ventilation and air-conditioning (HVAC) systems have been adopted to create comfortable, healthy and safe indoor environments. In the control loop, the technical feature of the human demand-oriented supply can help operate HVAC effectively. Among many technical options, real time monitoring based on feedback signals from end users has been frequently reported as a critical technology to confirm optimizing building performance. Recent studies have incorporated human thermal physiologysignals and thermal comfort/discomfort status as real-time feedback signals. A series of human subject experiments used to be conducted by primarily adopting subjective questionnaire surveys in a lab-setting study, which is limited in the application for reality. With the help of advanced technologies, physiological signals have been detected, measured and processed by using multiple technical formats, such as wearable sensors. Nevertheless, they mostly require physical contacts with the skin surface in spite of the small physical dimension and compatibility with other wearable accessories, such as goggles, and intelligent bracelets. Most recently, a low cost small infrared camera has been adopted for monitoring human facial images, which could detect the facial skin temperature and blood perfusion in a contactless way. Also, according to latest pilot studies, a conventional digital camera can generate infrared images with the more » help of new methods, such as the Euler video magnification technology. Human thermal comfort/discomfort poses can also be detected by video methods without contacting human bodies and be analyzed by the skeleton keypoints model. In this review, new sensing technologies were summarized, their cons and pros were discussed, and extended applications for the demand-oriented ventilation were also reviewed as potential development and applications. « less
Authors:
; ; ; ; ; ; ; ; ; ;
Award ID(s):
1707068
Publication Date:
NSF-PAR ID:
10301031
Journal Name:
Energy and buildings
Volume:
224
ISSN:
0378-7788
Sponsoring Org:
National Science Foundation
More Like this
  1. Heating, ventilation and air-conditioning (HVAC) systems have been adopted to create comfortable, healthy and safe indoor environments. In the control loop, the technical feature of the human demand-oriented supply can help operate HVAC effectively. Among many technical options, real time monitoring based on feedback signals from end users has been frequently reported as a critical technology to confirm optimizing building performance. Recent studies have incorporated human thermal physiology signals and thermal comfort/discomfort status as real-time feedback signals. A series of human subject experiments used to be conducted by primarily adopting subjective questionnaire surveys in a lab-setting study, which is limitedmore »in the application for reality. With the help of advanced technologies, physiological signals have been detected, measured and processed by using multiple technical formats, such as wearable sensors. Nevertheless, they mostly require physical contacts with the skin surface in spite of the small physical dimension and compatibility with other wearable accessories, such as goggles, and intelligent bracelets. Most recently, a low cost small infrared camera has been adopted for monitoring human facial images, which could detect the facial skin temperature and blood perfusion in a contactless way. Also, according to latest pilot studies, a conventional digital camera can generate infrared images with the help of new methods, such as the Euler video magnification technology. Human thermal comfort/discomfort poses can also be detected by video methods without contacting human bodies and be analyzed by the skeleton keypoints model. In this review, new sensing technologies were summarized, their cons and pros were discussed, and extended applications for the demand-oriented ventilation were also reviewed as potential development and applications.« less
  2. 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 themore »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.« less
  3. Thermal comfort is a significant factor in the indoor building environment because it influences both human productivity and health. A currently popular method for predicting thermal comfort levels, the Predicted Mean Vote (PMV) and Predicted Percent Dissatisfied (PPD) model, unfortunately, has certain limitations. Consequently, the development of a better method for making accurate predictions (especially for individuals) is needed. Our goal was to develop a tool to predict individual thermal comfort preferences and automatically control the heating, ventilation, and air conditioning (HVAC) systems. This study adopted a series of human-subject experiments to collect essential data. All collected data was analyzedmore »by adopting different machine learning algorithms. The machine learning algorithms predicted individual thermal comfort levels and thermal sensations, based on facial skin temperatures of participants in the experiments. These predictions were input data for the HVAC system control model, and results supported the potential for using facial skin temperatures to predict thermal comfort and thermal sensation levels. Moreover, this tool provided automatic control of the HVAC systems that can help improve the indoor environment of a building.« less
  4. It is well established that thermal comfort is an influential factor in human health and wellbeing. Uncomfortable thermal environments can reduce occupants’ comfort and productivity, and cause symptoms of sick building syndrome. To harness the built environment as a medium to support human health, well-being, and engagement, it is significantly important to understand occupants’ thermal comfort in real time. To this end, this study proposes a non-intrusive method to collect occupants’ facial skin temperature and interpret their thermal comfort conditions by fusing the thermal and RGB-D images collected from multiple low-cost thermographic and Kinect sensors. This study distinguishes from existingmore »methods of thermal comfort assessment in three ways: 1) it is a truly non-intrusive data collection approach which has a minimal interruption or participation of building occupants; 2) the proposed approach can simultaneously identify and interpret multiple occupants’ thermal comfort; 3) it uses low-cost thermographic and RGB-D cameras which can be rapidly deployed and reconfigured to adapt to various settings. This approach was experimentally evaluated in a transient heating environment (room temperature increased from 23 to 27 °C) to verify its applicability in real operational built environments. In total, all 6 subjects observed moderate to strong positive correlations between the ambient room temperature and subjects’ facial skin temperature collected using the proposed approach. Additionally, all 6 subjects have voted different thermal sensations at the beginning (the first 5 minutes) and at the end (the last 5 minutes) of the heating experiment, which can be reflected by the significant differences in the mean skin temperature of these two periods (p < .001). Results of this pilot study demonstrate the feasibility of applying the proposed non-intrusive approach to real multi-occupancy environments to dynamically interpret occupants’ thermal comfort and optimize the operation of building heating, ventilation and air conditioning (HVAC) systems.« less
  5. Understanding occupants’ thermal sensation and comfort is essential to defining the operational settings for Heating, Ventilation and Air Conditioning (HVAC) systems in buildings. Due to the continuous impact of human and environmental factors, occupants’ thermal sensation and comfort level can change over time. Thus, to dynamically control the environment, thermal comfort should be monitored in real time. This paper presents a novel non-intrusive infrared thermography framework to estimate an occupant’s thermal comfort level by measuring skin temperature collected from different facial regions using low- cost thermal cameras. Unlike existing methods that rely on placing sensors directly on humans for skinmore »temperature measurement, the proposed framework is able to detect the presence of occupants, extract facial regions, measure skin temperature features, and interpret thermal comfort conditions with minimal interruption of the building occupants. The method is validated by collecting thermal comfort data from a total of twelve subjects under cooling, heating and steady-state experiments. The results demonstrate that ears, nose and cheeks are most indicative of thermal comfort and the proposed framework can be used to assess occupants’ thermal comfort with an average accuracy of 85%.« less