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1. Thermal Comfort: Radiant Systems - A Review of Experimentalbased thermal comfort research in Radiation systems

   JAWADWALA, HUZEFA ; TIAN, ROBERT ; YIN, HONGXI ; QU, MING ; LIU, XIAOLI ; HOLMES, NIALL ; KOHANOFF, JORGE ; JANI, RUCHITA ( March 2021 , 108th ACSA Annual Meeting Proceeding)

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   Buildings use 40% of the global energy consumption and emit 30% of the CO2 emissions [1]. Of the total building energy, 30-40% are for building heating and cooling systems, which regulate the indoor thermal environment and provide thermal comfort to occupants. In the United States, most buildings use forced air technology to deliver heating/cooling to the targeted thermal zones. However, this system may cause complaints about thermal comfort from inhabitants due to excessive draft movement, inhomogeneous conditioning, and difficulty in accurately controlling the temperature for a system serving multiple rooms. Therefore, researchers have suggested using a radiant heating and cooling system as a better alternative to all-air systems to address these issues. Radiant systems supply heating or cooling directly to the building space using radiation released by the heated or cooled building enclosure via the embedded heating or cooling tubes. In the cooling season, the radiant system often works with a separated dehumidifier to meet space latent and sensible cooling load (called separate sensible and latent cooling system SSLC). The SSLC has shown higher efficiency than forced air systems. However, it is unsure whether the radiant heating and cooling system can provide better thermal comfort to occupants. Moreover, the evaluation method for thermal comfort in the current standard is suitable for forced air systems. Therefore, a new method shall be developed to evaluate the radiation system’s thermal comfort. In this paper, we review the experiment-based studies on the thermal comfort of radiant systems. According to the experimental studies regarding thermal comfort and radiant systems, the key findings are concluded to help guide the evaluation of thermal comfort for radiant systems. 

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

   Li, Da ; Menassa, Carol. C ; and Kamat, Vineet R. ( January 2018 , Energy and buildings)

   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 skin 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%. 

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3. Thermal and RGB-D Sensor Fusion for Non-Intrusive Human Thermal Comfort Assessment

   Li, Da ; Menassa, Carol. C ; and Kamat, Vineet R. ( January 2019 , CIB World Building Congress 2019, Hong Kong)

   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 existing 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. 

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4. Feasibility of Low-Cost Infrared Thermal Imaging to Assess Occupants’ Thermal Comfort

   Li, Da ; Menassa, Carol. C ; and Kamat, Vineet R. ( January 2019 , International Conference on. Computing in Civil Engineering (i3CE): Smart Cities, Sustainability, and Resilience)

   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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5. Robust non-intrusive interpretation of occupant thermal comfort in built environments with low-cost networked thermal cameras

   Li, Da ; Menassa, Carol. C ; and Kamat, Vineet R. ( January 2019 , Applied energy)

   About 40% of the energy produced globally is consumed within buildings, primarily for providing occupants with comfortable work and living spaces. However, despite the significant impacts of such energy consumption on the environment, the lack of thermal comfort among occupants is a common problem that can lead to health complications and reduced productivity. To address this problem, it is particularly important to understand occupants’ thermal comfort in real-time to dynamically control the environment. This study investigates an infrared thermal camera network to extract skin temperature features and predict occupants’ thermal preferences at flexible distances and angles. This study distinguishes from existing methods in two ways: (1) the proposed method is a non-intrusive data collection approach which does not require human participation or personal devices; (2) it uses low-cost thermal cameras and RGB-D sensors which can be rapidly reconfigured to adapt to various settings and has little or no hardware infrastructure dependency. The proposed camera network is verified using the facial skin temperature collected from 16 subjects in a multi-occupancy experiment. The results show that all 16 subjects observed a statistically higher skin temperature as the room temperature increases. The variations in skin temperature also correspond to the distinct comfort states reported by the subjects. The post-experiment evaluation suggests that the networked thermal cameras have a minimal interruption of building occupants. The proposed approach demonstrates the potential to transition the human physiological data collection from an intrusive and wearable device-based approach to a truly non-intrusive and scalable approach. 

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