Application of machine learning in thermal comfort studies: A review of methods, performance and challenges

Fard, Zahra Qavidel; Zomorodian, Zahra Sadat; Korsavi, Sepideh Sadat

doi:10.1016/j.enbuild.2021.111771

Cited by 81 publications

(44 citation statements)

References 92 publications

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“…ML is a subfield of artificial intelligence, which is defined as the capability of a machine to imitate intelligent human behavior, being used to solve complex problems (Fard et al. , 2022).…”

Section: Resultsmentioning

confidence: 99%

“…Quality of data is a very relevant fact in order to correctly assess an environment. According to Fard et al. (2022), it is also important to develop sensors that are able to collect data without disturbing occupants.…”

Section: Future Trends and Gap Researchmentioning

confidence: 99%

“…Machine learning (ML) as a tool for building control ML is a subfield of artificial intelligence, which is defined as the capability of a machine to imitate intelligent human behavior, being used to solve complex problems (Fard et al, 2022). According to Xie et al (2020), ML methods have several applications, but currently are used mainly for presenting algorithms.…”

Section: Devices Used For Monitoring Ieq Parametersmentioning

confidence: 99%

“…Quality of data is a very relevant fact in order to correctly assess an environment. According to Fard et al (2022), it is also important to develop sensors that are able to collect data without disturbing occupants. Also, different occupant needs cannot be measured in a single indicator, because good air quality does not compensate for a situation of thermal discomfort (Kurnitski and Hogeling, 2018).…”

Section: Future Trends and Gap Researchmentioning

confidence: 99%

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The role of internet of things (IoT) in the assessment and communication of indoor environmental quality (IEQ) in buildings: a review

Broday

Silva

2022

SASBE

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PurposeThe changes brought by Industry 4.0 go beyond transformations in the industrial environment. The increasingly frequent digitization and robotization of activities is not only restricted to the industrial environment, but also to people's daily routine. People spend a large part of their time inside buildings, and maintaining adequate Indoor Environmental Quality (IEQ) is an essential factor for a healthy and productive environment. In this sense, the purpose of this study is to verify how the Internet of Things (IoT) is being used to improve the indoor environment, through sensors that instantly measure the conditions of the environment.Design/methodology/approachThe aim of this paper is to verify, through a literature review, how IoT is being used for building control (for energy saving purposes) and to monitor IEQ conditions inside buildings, in order to provide a better environment for occupants, in terms of health and comfort. By combining keywords in databases, PRISMA method was used to select the articles for analysis, and 91 articles were analyzed.FindingsThe main findings in this research are: (1) the main purpose for applying IoT inside buildings is to reduce energy consumption; (2) there is an interest in developing low-cost sensoring devices with a learning approach; (3) Machine Learning methods are mainly used for energy saving purposes and to learn about occupants' behavior inside buildings, focusing on thermal comfort; (4) sensors in the IoT era are a requirement to help improve people's comfort and well-being.Originality/valueStudies directly correlating IoT and IEQ are limited. This paper emphasises the link between them, through the presentation of recent methods to control the built environment.

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Section: Resultsmentioning

confidence: 99%

Section: Future Trends and Gap Researchmentioning

confidence: 99%

Section: Devices Used For Monitoring Ieq Parametersmentioning

confidence: 99%

Section: Future Trends and Gap Researchmentioning

confidence: 99%

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The role of internet of things (IoT) in the assessment and communication of indoor environmental quality (IEQ) in buildings: a review

Broday

Silva

2022

SASBE

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“…Thus, our prediction model can then be exploited to predict the indoor parameters in real time. It is worth noting that there are some works which aim to predict indoor thermal comfort [14][15][16]; however, almost all of them are based on either occupants' perception or indoor thermal conditions to determine the suitable indoor thermal comfort. Moreover, when detecting an indoor thermal discomfort, we propose a new genetic-based algorithm to find the most suitable values of indoor parameters, enabling the improvement of the indoor occupants' thermal comfort.…”

Section: Introductionmentioning

confidence: 99%

Providing Convenient Indoor Thermal Comfort in Real-Time Based on Energy-Efficiency IoT Network

et al. 2022

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Monitoring the thermal comfort of building occupants is crucial for ensuring sustainable and efficient energy consumption in residential buildings. It enables not only remote real-time detection of situations, but also a timely reaction to reduce the damage made by harmful situations in targeted buildings. In this paper, we first design a new Internet of Things (IoT) architecture in order to provide remote availability of both indoor and outdoor conditions, with respect to the limited energy of IoT devices. We then build a multi-output prediction model of indoor parameters using a random forest learning algorithm, and based on a longitudinal real dataset of one year. Our prediction model considers outdoor conditions to predict the indoor ones. Hence, it helps to detect discomfort situations in real-time when comparing predicted variables to real ones. Furthermore, when detecting an indoor thermal discomfort, we provide a new genetic-based algorithm to find the most suitable values of indoor parameters, enabling the improvement of the indoor occupants’ thermal comfort. Numerical results show the efficiency of our prediction scheme, reaching an accuracy of 96%, as well as our genetic-based scheme in optimizing the indoor thermal parameters by 85%.

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Prediction of Indoor Air Quality Using Artificial Intelligence

Kapoor¹,

Kumar²,

Kumar³

et al. 2023

Machine Intelligence, Big Data Analytics, and IoT in Image Processing

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Application of machine learning in thermal comfort studies: A review of methods, performance and challenges

Cited by 81 publications

References 92 publications

The role of internet of things (IoT) in the assessment and communication of indoor environmental quality (IEQ) in buildings: a review

The role of internet of things (IoT) in the assessment and communication of indoor environmental quality (IEQ) in buildings: a review

Providing Convenient Indoor Thermal Comfort in Real-Time Based on Energy-Efficiency IoT Network

Prediction of Indoor Air Quality Using Artificial Intelligence

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