Thermal adaptive behavior and thermal comfort for occupants in multi-person offices with air-conditioning systems

Zheng, Peiping; Wang, Chunxiao; Liu, Yanchen; Lin, Borong; Wu, Huijun; Huang, Yu; Zhou, Xiaoqing

doi:10.1016/j.buildenv.2021.108432

Cited by 26 publications

(3 citation statements)

References 36 publications

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“…Therefore, the fusion of BIM and metaverse make it more flexible to conduct the construction design, building functional design and simulation for energy efficiency. Especially, it does not need to consider the pollution caused by the construction process, and allows to consider many influencing factors, such as climate [67], personnel activities [68], [69], building material [70], equipment [71], etc. Thus, the entire process is green and low-carbon.…”

Section: E Technical Application Scenarios 1) Restoration Of Cultural...mentioning

confidence: 99%

Fusion of Building Information Modeling and Blockchain for Metaverse: A Survey

Huang

Zeng

Zhao

et al. 2022

IEEE Open J. Comput. Soc.

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Section: E Technical Application Scenarios 1) Restoration Of Cultural...mentioning

confidence: 99%

Fusion of Building Information Modeling and Blockchain for Metaverse: A Survey

Huang

Zeng

Zhao

et al. 2022

IEEE Open J. Comput. Soc.

Self Cite

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“…Under such motivation, multiple studies such as in Asia, America and Australia have been further carried out to probe the adaptive thermal comfort based on field investigation [ [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] , [53] , [54] , [55] , [56] ]. The representative studies which including the research methods, paths and techniques adopted are summarized in Table 1 .…”

Section: Introductionmentioning

confidence: 99%

Thermal comfort and adaptive behaviors in office buildings: A pilot study in Turpan (China) during summer

Guo,

Tang,

Gao

et al. 2023

Heliyon

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“…2021 ; Pratt and Erickson 2020 ), optimizing occupants’ thermal comfort (Zheng et al. 2022 ), transforming water management (Doorn 2021 ), improving fault detection and diagnosis (Yun et al. 2021 ), etc.…”

Section: Introductionmentioning

confidence: 99%

AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

et al. 2022

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In theory, building automation and management systems (BAMSs) can provide all the components and functionalities required for analyzing and operating buildings. However, in reality, these systems can only ensure the control of heating ventilation and air conditioning system systems. Therefore, many other tasks are left to the operator, e.g. evaluating buildings’ performance, detecting abnormal energy consumption, identifying the changes needed to improve efficiency, ensuring the security and privacy of end-users, etc. To that end, there has been a movement for developing artificial intelligence (AI) big data analytic tools as they offer various new and tailor-made solutions that are incredibly appropriate for practical buildings’ management. Typically, they can help the operator in (i) analyzing the tons of connected equipment data; and; (ii) making intelligent, efficient, and on-time decisions to improve the buildings’ performance. This paper presents a comprehensive systematic survey on using AI-big data analytics in BAMSs. It covers various AI-based tasks, e.g. load forecasting, water management, indoor environmental quality monitoring, occupancy detection, etc. The first part of this paper adopts a well-designed taxonomy to overview existing frameworks. A comprehensive review is conducted about different aspects, including the learning process, building environment, computing platforms, and application scenario. Moving on, a critical discussion is performed to identify current challenges. The second part aims at providing the reader with insights into the real-world application of AI-big data analytics. Thus, three case studies that demonstrate the use of AI-big data analytics in BAMSs are presented, focusing on energy anomaly detection in residential and office buildings and energy and performance optimization in sports facilities. Lastly, future directions and valuable recommendations are identified to improve the performance and reliability of BAMSs in intelligent buildings.

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Thermal adaptive behavior and thermal comfort for occupants in multi-person offices with air-conditioning systems

Cited by 26 publications

References 36 publications

Fusion of Building Information Modeling and Blockchain for Metaverse: A Survey

Fusion of Building Information Modeling and Blockchain for Metaverse: A Survey

Thermal comfort and adaptive behaviors in office buildings: A pilot study in Turpan (China) during summer

AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

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