Personal thermal comfort models based on physiological measurements – A design of experiments based review

Chen, Kai; Xu, Qian; Leow, Berlynette; Ghahramani, Ali

doi:10.1016/j.buildenv.2022.109919

Cited by 29 publications

(6 citation statements)

References 108 publications

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“…People can adapt to the cold environment through certain physiological adjustments. The four mechanisms that contribute to thermoregulation are sweating, shivering, vasodilation, and vasoconstriction [128]. When the body is exposed to cold ambient temperatures, the skin surface blood flow rate and skin temperature decrease, thereby preventing excessive body heat dissipation [41].…”

Section: Adaptive Behaviormentioning

confidence: 99%

A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China

Lin,

Chen,

Yang

et al. 2024

Energies

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There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants’ thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants’ comfort.

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Section: Adaptive Behaviormentioning

confidence: 99%

A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China

Lin,

Chen,

Yang

et al. 2024

Energies

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“…A comfortable atmosphere and environment will indirectly help someone relax while studying (Chen et al, 2023). If a person feels relaxed and comfortable while studying, it will be easier for them to concentrate (Taufik et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Training on Website Application Development for Coffee Shop Visitors for Students

Akbar Iskandar,

Kamaruddin,

Erwin Gatot Amiruddin

et al. 2024

j. abdimas cendekiawan Indones.

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The world of education has changed, What world of education which used to be a transfer of knowledge with a standardized model is now changing more straightforwardly, students who used to only be able to learn through teachers/lecturers, schools, campuses, and literature books, are now facilitated by existing facilities, such as the internet, Study Clubs, and learning places that are more following the modern lifestyle of students. So the idea emerged regarding planning training activities in coffee shops/cafes which are recreational and educational facilities by paying attention to all the facilities needed as well as alternatives and new functions that are well adapted, comfortable, and not just for relaxing. Training activities to create a website in a coffee shop/cafe is an alternative to obtaining a comfortable, minimalist, and modern learning atmosphere. An atmosphere that makes anyone feel at home, not only just eating and drinking but also still processing their productivity. Doing activities in a coffee shop/cafe reflects the lifestyle of today's students, which is realized in a new learning method that is expected to represent the mindset, ideas, and creativity of students.

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“…Machine learning has been addressed in reviews about thermal comfort [15][16][17][18], control of HVAC [19][20][21][22] and lighting systems [19][20][21][22], and occupant-centred control overall [8,23]. Moreover, reviews that address machine learning specifically bring together the authors who have used this approach to predict occupation [24,25] and windows opening [25], improve different aspects of lighting (technologies, efficiency, security, comfort) in in-and outdoor environments [26], create personalised thermal comfort models [27] and analyse the impact of thermal comfort on users' cognition, work and health [28].…”

Section: Introductionmentioning

confidence: 99%

Utilisation of Machine Learning in Control Systems Based on the Preference of Office Users

Bilésimo,

Ghisi

2024

Sustainability

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Reducing energy consumption is vital to save natural resources and contribute to the sustainable development in any sector of society. In the building sector, there are many well-known energy efficiency strategies currently being applied. However, considering the advances in technology and in comfort studies, it is possible to see that the current building sector scenario demands new energy efficiency strategies. Such strategies need to be capable of identifying and assuring comfortable environments according to users’ perceptions. Machine learning techniques can be a useful alternative to identify users’ preferences and control lighting and heating, ventilation and air-conditioning systems in buildings. This paper shows a systematic literature review on the use of machine learning algorithms on preference identification and environmental adequacy according to users’ demands. Its contribution is to explore beyond the performance and configurations of the algorithms, addressing users’ preference aspects as well. The strategies found in the literature provided promising results. The most used approach was supervised learning because data can be treated as categories. In general, the control systems have shown good performance, and so have the algorithms. Users were mostly satisfied with environmental conditions. Situations of dissatisfaction were associated with the occupant’s willingness to use the system more than with the control system’s performance. Furthermore, it is also possible to ally user-centred control and energy savings but this relies on occupants’ characteristics and the control strategies used. We underline the importance of identifying whether the users are willing to deal with an automatic control system before making any decision, even if the operation of the system is based on their preferred environmental conditions.

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Personal thermal comfort models based on physiological measurements – A design of experiments based review

Cited by 29 publications

References 108 publications

A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China

A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China

Training on Website Application Development for Coffee Shop Visitors for Students

Utilisation of Machine Learning in Control Systems Based on the Preference of Office Users

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