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1. 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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2. 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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3. A Low-Cost and Scalable Personalized Thermal Comfort Estimation System in Indoor Environments

   https://doi.org/10.1145/3458648.3460006  

   Wei, Peter; Liu, Yanchen; Kang, Hengjiu; Yang, Chenye; Jiang, Xiaofan (May 2021, Proceedings of the First International Workshop on Cyber-Physical-Human System Design and Implementation)

   null (Ed.)

   In commercial buildings, occupant thermal comfort is a key factor that must be optimized to provide a comfortable and productive work environment. However, current methods largely estimate thermal comfort based on preset models which do not incorporate real-time measurements or individual thermal preferences. In this work, we present a scalable system for estimating personalized thermal comfort using low-cost thermal camera based sensor nodes. This system extracts non-intrusive thermal measurements, is robust to different perspectives and environments, is easily deployable and low-cost, and can incorporate individual thermal feedback for more personalized thermal comfort estimates. In comparison with baseline methods, our system is able to improve thermal comfort estimates on the ASHRAE 7-point thermal sensation scale by 64% over baseline methods. 

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4. 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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5. Low-Energy Wearable Cooling Strategy for Thermal Comfort at a Warm Environment

   Belyamani, Mohamed; Hurley, Rachel; Zhang, Hui; Djamasbi, Soussan; Somasse, Gbetonmasse; Strauss, Sarah; Smith, Matthew; Liu, Shichao (July 2022, The 5th International Conference on Building Energy & Environment (COBEE))

   The objective of this study is to assess the effectiveness of wearable cooling in improving thermal comfort for a warm environment that would become prevalent due to more frequent extreme weather events, especially when air conditioning is not accessible for many developing countries. The experiment was conducted in an environment room with air temperature maintained at 31 °C and relative humidity at 55%. The study tested 30 participants using a wearable cooling device at the upper back location, while another 30 had no local cooling as the control group. Participants’ thermal comfort, thermal sensation and other metrics were assessed three times for a test session. The clothing insulation was 0.36 clo to simulate summer attire. The results showed significantly lower average local and whole-body thermal sensation for the participants with the wearable cooling device than the control group by considering all the votes during the entire session. Compared to the baseline, in particular, the local cooling group indicated a significant reduction in local thermal sensation for all three times of self-evaluation. Nevertheless, the reduction in overall thermal sensation occurred right after the local cooling was applied. Such a significant reduction was not observed after a while and then emerged again during the test, indicating an interactive phenomenon involving thermal adaptation and comfort restoration which will be investigated in the future. 

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