A review on occupancy prediction through machine learning for enhancing energy efficiency, air quality and thermal comfort in the built environment

Zhang, Wuxia; Wu, Yupeng; Calautit, John Kaiser

doi:10.1016/j.rser.2022.112704

Cited by 120 publications

(49 citation statements)

References 156 publications

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“…Their findings show that Contents lists available at ScienceDirect Smart Energy journal homepage: www.journals.elsevier.com/smart-energy https://doi.org/10.1016/j.segy.2022.100091 the variations between the energy demand of households are highly dependent on the occupancy patterns and lifestyles and stress the challenge of predicting energy demand, given the stochastic nature of internal heat gains, equipment set points and window opening behavior. The non-trivial impact of occupancy behavior on energy consumption was also highlighted by other SDEWES works in the past, such as [6], where 160 machine learning-based building occupancy prediction studies are reviewed or [7], where a deep learning model is applied for detecting window openings, so as to more effectively manage building ventilation and reduce space heating demand.…”

Section: Smart Energy Demand For Sustainable Developmentmentioning

confidence: 88%

Smart energy demand for the sustainable development of energy, water and environment systems

Gjorgievski

Markovska²,

Mathiesen³

et al. 2022

Smart Energy

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Section: Smart Energy Demand For Sustainable Developmentmentioning

confidence: 88%

Smart energy demand for the sustainable development of energy, water and environment systems

Gjorgievski

Markovska²,

Mathiesen³

et al. 2022

Smart Energy

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“…There is growing evidence of the use of cutting‐edge technologies such as machine learning (ML), artificial intelligence (AI), Internet of Things (IoT), uncertainty analysis, and optimization techniques in assessing IEQ situations in smart buildings 22,200 . These new techniques can be used to accurately predict thermal comfort, GHG emissions, and IAQ 201 . It has been suggested the design of energy‐efficient sustainable buildings, including forecasting occupant's behavioral patterns, is possible through the application of ML.…”

Section: Discussionmentioning

confidence: 99%

Influence of phase change materials on thermal comfort, greenhouse gas emissions, and potential indoor air quality issues across different climatic regions: A critical review

Amoatey

Al‐Jabri

Al‐Saadi

2022

Intl J of Energy Research

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There has been growing interest in applying phase change materials (PCMs) in buildings owing to their energy conservation/latent heat storage properties and potential to improve thermal comfort. Various reviews have extensively discussed the thermophysical properties of PCMs and their energy-saving potential in buildings. However, comprehensive reviews on the indoor thermal/ personal comfort behavior of PCMs under different climates remain limited. Therefore, this study aims to present a comprehensive state-of-the-art review of the impact of PCMs on indoor thermal comfort levels in buildings located in cities within different subclimate zones and their personal cooling effect when integrated with clothing (vest). In addition, greenhouse gas (GHG) mitigation potentials and indoor air pollutant emission properties of PCM-enhanced buildings were also reviewed. Hundreds of published articles of PCMs in PubMed and Scopus databases, including a manual search approach, were utilized. The results from this state-of-the-art study have shown that incorporating PCMs in buildings satisfactorily reduced the indoor air temperature of most buildings located in hot climate (BSh, BWh) zones, but very limited studies have been performed in the cold (Dfc, BSk) environments. In general, there was an improvement in the thermal comfort levels of the PCM-enhanced buildings. However, these were mostly assessed using indices such as predicted mean vote, predicted percentage of dissatisfied, comfort index, and total discomfort change, without any comprehensive survey studies (eg, based on

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“…This is further exacerbated when windows are inadequate (Tien et al, 2022) during the dry season, causing unnecessary energy consumption and wastage, compromising the cooling system efficiency. Occupant behaviour influences and shapes the building's energy use and indoor environment quality (Zhang et al, 2022). In particular, the occupant's interaction with the building and its elements, such as window openings (Fabi et al 2012), has a considerable effect on the air change rate and the thermal comfort.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance Analysis of Energy Saving Strategies and the Risk of Occupant Thermal Discomfort in Residential Buildings in Warm Humid Climate

2023

IRJMETS

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The discomfort faced by occupants of buildings in warm humid climate are effect of high solar radiation, high humidity levels and less effective air flow; which cannot ensure occupant thermal comfort. As a result, these have contributed to use of artificial means to provide a comfortable thermal environment at high energy consumption. The thermal comfort of the occupants, a measure of the satisfaction with the indoor environmental conditions, is thus of great importance, and has been linked to the health, well-being, and productivity of occupants. To reduce energy use and costs, and to reduce greenhouse gas emissions, buildings continue to be targeted through energy efficient retrofits and natural ventilation design. Therefore, this paper reports on the evaluation done using questionnaire and physical measurement to determine the effect of energy saving strategies on occupant's thermal perception in residential buildings. Data on the indoor air flow in five different window openings in purposively selected rooms were used. The Analysis of Variance (ANOVA) test conducted at 95% confidence level showed that there was significant statistical difference between the occupant's thermal perception for the different window openings thus: F=65.555; p=.000. The sliding window had a mean value of 29.25; projected 28.14; casement 27.00; louvre 26.23 and casement with vent 24.97. The result shows that the ability to achieve a comfortable indoor environment for occupants by applying energy saving strategies is influenced by window design variables. Recommendations were made for energy saving strategies to be applied both in the design phase of a building and when renovating existing buildings to achieve low energy consumption and occupant thermal comfort.

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A review on occupancy prediction through machine learning for enhancing energy efficiency, air quality and thermal comfort in the built environment

Cited by 120 publications

References 156 publications

Smart energy demand for the sustainable development of energy, water and environment systems

Smart energy demand for the sustainable development of energy, water and environment systems

Influence of phase change materials on thermal comfort, greenhouse gas emissions, and potential indoor air quality issues across different climatic regions: A critical review

Performance Analysis of Energy Saving Strategies and the Risk of Occupant Thermal Discomfort in Residential Buildings in Warm Humid Climate

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