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1. Energy Co-simulation of the Hybrid Cooling Control with Synthetic Thermal Preference Distributions

   Lu, S. ; Zhiang, Z. ; Hameen, E. C. ; Lartigue, B. ; Karaguzel, O. ( January 2020 , Symposium on Simulation in Architecture and Urban Design (SIMAUD 2020))

   Thermal comfort and energy efficiency are always the two most significant objectives in HVAC operations. However, for conventional HVAC systems, the pursuit of high energy efficiency may be at the expense of satisfactory thermal comfort. Therefore, even if centralized HVAC systems nowadays have higher energy efficiency than before in office buildings, most of them cannot adapt the dynamic occupant behaviors or individual thermal comfort. In order to realize high energy efficiency while still maintain satisfactory thermal environment for occupants indoors, the integrated hybrid HVAC system has been developed for years such as task-ambient conditioning system. Moreover, the occupant-based HVAC control system such as human- in-the-loop has also been investigated so that the system can be adaptive based on occupant behaviors. However, most of research related to personalized air-conditioning system only focuses on field-study with limited scale (i.e. only one office room), this paper has proposed a co- simulation model in energyplus to simulate the hybrid cooling system with synthetic thermal comfort distributions based on global comfort database I&II. An optimization framework on cooling set-point is proposed with the objective of energy performance and the constraints of thermal comfort distribution developed by unsupervised Gaussian mixture model (GMM) clustering and kernel density estimation (KDE). The co-simulation results have illustrated that with the proposed optimization algorithm and the hybrid cooling system, HVAC demand power has decreased 5.3% on average with at least 90% of occupants feeling satisfied. 

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2. What drives our behaviors in buildings? A review on occupant interactions with building systems from the lens of behavioral theories

   https://doi.org/10.1016/j.buildenv.2020.106928  

   Arsalan Heydarian, Claire McIlvennie ( July 2020 , Building and environment)

   Occupant behavior has a significant impact on building systems’ operations and efficiency. As a result, several innovative approaches have been introduced to quantify the dynamics of occupants within indoor environments, such as interactions with different building systems and the impact of various feedback and interventions to reduce the building energy consumption. To achieve this, researchers have highlighted the importance of reducing energy consumption without impacting occupant comfort. As a result, there is an increasing body of research evaluating how different theories of behavior across a variety of disciplines can explain occupant interactions with building systems. Future progress in this area calls for an in-depth understanding of behavioral theories in explaining occupant interactions with different building systems. In this paper, we have used a structured literature review approach to investigate how different psychological, sociological, and economic theories have been applied to explain occupant interactions with heating and cooling (HVAC systems), opening windows and ventilation, lighting and shading, electronic appliances, domestic hot water, as well as energy conservation behaviors. Throughout the paper, we identify the most common theories and methodologies applied within the existing research, general findings related to how occupants interact with different building systems, as well as a number of identified gaps within the literature. Finally, we provide a discussion on directions for future research studies in this area under each building system. 

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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. An Open-Source Platform for Indoor Environment Monitoring with Participatory Comfort Sensing

   https://doi.org/10.3390/s23010364  

   Rosenberger, Joseph ; Guo, Zhong ; Coffman, Austin ; Agdas, Duzgun ; Barooah, Prabir ( January 2023 , Sensors)

   We present an open-source wireless network and data management system for collecting and storing indoor environmental measurements and perceived comfort via participatory sensing in commercial buildings. The system, called a personal comfort and indoor environment measurement (PCIEM) platform, consists of several devices placed in office occupants’ work areas, a wireless network, and a remote database to store the data. Each device, called a PCFN (personal comfort feedback node), contains a touchscreen through which the occupant can provide feedback on their perceived comfort on-demand, and several sensors to collect environmental data. The platform is designed to be part of an indoor climate control system that can enable personalized comfort control in real-time. We describe the design, prototyping, and initial deployment of a small number of PCFNs in a commercial building. We also provide lessons learned from these steps. Application of the data collected from the PCFNs for modeling and real-time control will be reported in future work. We use hardware components that are commercial and off-the-shelf, and our software design is based on open-source tools that are freely and publicly available to enable repeatability. 

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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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