Non-intrusive interpretation of human thermal comfort through analysis of facial infrared thermography

Li, Da; Menassa, Carol C.; Kamat, Vineet R.

doi:10.1016/j.enbuild.2018.07.025

Cited by 162 publications

(75 citation statements)

References 22 publications

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“…Recently, many studies [31][32][33][34] have been conducted to measure the skin temperatures of occupants using non-contact sensors. Using a non-contact sensor such as an IR camera, the skin temperature can be measured in real space without harming the occupants.…”

Section: Calculation Of Clothing Insulation Using a Human Thermoregulmentioning

confidence: 99%

Assessment of a Real-Time Prediction Method for High Clothing Thermal Insulation Using a Thermoregulation Model and an Infrared Camera

Lee¹,

Choi

Kim

et al. 2020

Atmosphere

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For evaluating the thermal comfort of occupants, human factors such as clothing thermal insulation (clo level) and metabolic rate (Met) are one of the important parameters as well as environmental factors such as air temperature (Ta) and humidity. In general, a fixed clo level is commonly used for controlling heating, ventilation, and air conditioning using the thermal comfort index. However, a fixed clo level can lead to errors for estimating the thermal comfort of occupants, because clo levels of occupants can vary with time and by season. The present study assesses a method for predicting the clo level of occupants using a thermoregulation model and an infrared (IR) camera. The Tanabe model and the Fanger model were used as the thermoregulation models, and the predicted performance for high clo level (winter clothing) was compared. The skin and clothing temperatures of eight subjects using a non-contact IR camera were measured in a climate chamber. In addition, the measured values were used for the thermoregulation models to predict the clo levels. As a result, the Tanabe model showed a better performance than the Fanger model for predicting clo levels. In addition, all models tended to predict a clo level higher than the traditional method.

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Section: Calculation Of Clothing Insulation Using a Human Thermoregulmentioning

confidence: 99%

Assessment of a Real-Time Prediction Method for High Clothing Thermal Insulation Using a Thermoregulation Model and an Infrared Camera

Lee¹,

Choi

Kim

et al. 2020

Atmosphere

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“…(Kim et al, 2018). Furthermore, emerging technologies, such as wearable devices and thermal imaging, could be used to learn comfort preferences more accurately (Burzo et al, 2014;Ghahramani et al, 2016;Li et al, 2018). Several ways to control the thermal environment based on occupant feedback have been developed, with some controlling the central HVAC system, such as comfy (www.…”

Section: Thermal Conditionsmentioning

confidence: 99%

Smart Desks to Promote Comfort, Health, and Productivity in Offices: A Vision for Future Workplaces

Aryal

Becerik-Gerber

Anselmo

et al. 2019

Front. Built Environ.

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People spend most of their day in buildings, and a large portion of the energy in buildings is used to control the indoor environment for creating acceptable conditions for occupants. However, the majority of the building systems are controlled based on a "one size fits all" scheme which cannot account for individual occupant preferences. This leads to discomfort, low satisfaction and negative impacts on occupants' productivity, health and well-being. In this paper, we describe our vision of how recent advances in Internet of Things (IoT) and machine learning can be used to add intelligence to an office desk to personalize the environment around the user. The smart desk can learn individual user preferences for the indoor environment, personalize the environment based on user preferences and act as an intelligent support system for improving user comfort, health and productivity. We briefly describe the recent advances made in different domains that can be leveraged to enhance occupant experience in buildings and describe the overall framework for the smart desk. We conclude the paper with a discussion of possible avenues for further research.

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“…These variations contribute to the skin temperature, that has been used as a well-known physiological parameter for thermal comfort quantification. To this end, given its non-intrusive nature, the infrared imaging technology has been used as a potential apparatus [15,16]. Moreover, the feasibility of using RGB video images by employing the photoplethysmography (PPG) has been also explored [20,22].…”

Section: Previous Studiesmentioning

confidence: 99%

“…Current research efforts are searching for physiological sensing systems (PSS) that can be used in practice to collect human contextual data not only for developing high-performance comfort profiles, but also for realization of comfort-aware HVAC operation. For example, Li, et al [15] and Ranjan and Scott [16] used an infrared imaging technology for this purpose. Our previous studies have shown that Doppler Radar Sensors (DRSs) have potentials of measuring human thermoregulation states as a non-intrusive apparatus for quantification of respiration [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Spatial Efficacy of Respiration Monitoring using Doppler Radars for Personalized Thermal Comfort Assessment

Jung¹,

Jazizadeh²

2019

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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Recent research efforts have shown that human thermophysiological features could play a crucial role in inferring occupants' thermal comfort, which is required for comfort-aware heating, ventilation, and air conditioning (HVAC) operation. Our previous studies have demonstrated that variations of respiration, a representative human thermophysiological feature, can be non-intrusively quantified by a Doppler radar sensor (DRS). However, in pursuit of enabling human-aware rooms in buildings, in this study we have explored the impact of distance and position of the respiration monitoring system to investigate the potential of DRS systems as a ubiquitous apparatus in the realworld scenarios. Through experimental studies, respiration characteristics were evaluated in different locations and angles relative to the location of the measurement device. The measurements were carried out using a DRS system and a respiratory belt for ground truth data collection. The noise artifacts were reduced by applying the Savitzky-Golay method and Hann window, and respiration was identified by selecting the frequency component with the maximum amplitude in the typical breathing frequency range (0.1 to 0.5 Hz). Our analyses demonstrated that the signal from a costeffective DRS technology without the use of external amplifiers could cover a range, within 1.0m longitudinally and 0.5m laterally, which is sufficient for an individual sensing given a normal office environment. It was also observed that the use of an external amplifier extends the range of the DRS sensing but at the same time accentuates the noise. Therefore, advanced noise removal methods are needed to increase the range of robust sensing. This study contributes to DRS deployment strategies for realization of comfort-aware systems.

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Non-intrusive interpretation of human thermal comfort through analysis of facial infrared thermography

Cited by 162 publications

References 22 publications

Assessment of a Real-Time Prediction Method for High Clothing Thermal Insulation Using a Thermoregulation Model and an Infrared Camera

Assessment of a Real-Time Prediction Method for High Clothing Thermal Insulation Using a Thermoregulation Model and an Infrared Camera

Smart Desks to Promote Comfort, Health, and Productivity in Offices: A Vision for Future Workplaces

Spatial Efficacy of Respiration Monitoring using Doppler Radars for Personalized Thermal Comfort Assessment

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