A systematic review of personal thermal comfort models

Building and Environment, Journal Year: 2021, Volume and Issue: 207, P. 108502 - 108502

Published: Oct. 28, 2021

Language: Английский

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Data-driven personal thermal comfort prediction: A literature review

Renewable and Sustainable Energy Reviews, Journal Year: 2022, Volume and Issue: 161, P. 112357 - 112357

Published: March 11, 2022

Language: Английский

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Advanced controls on energy reliability, flexibility and occupant-centric control for smart and energy-efficient buildings

Energy and Buildings, Journal Year: 2023, Volume and Issue: 297, P. 113436 - 113436

Published: Aug. 9, 2023

Language: Английский

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Building automation systems for energy and comfort management in green buildings: A critical review and future directions

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 179, P. 113301 - 113301

Published: April 18, 2023

Language: Английский

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Exploring the role of skin temperature in thermal sensation and thermal comfort: A comprehensive review

Energy and Built Environment, Journal Year: 2024, Volume and Issue: unknown

Published: March 1, 2024

The role of skin temperature as a determinant human thermal sensation and comfort has gained increasing recognition, prompting need for systematic review. This review examines the relationship between sensation, synthesizing insights from 172 studies published since 2000. It uniquely focuses on indispensable roles local mean temperatures, perspective not comprehensively explored in previous literature. reveals that most common measurement points are face hands, attributed to their higher sensitivity practical ease measurement. establishes clear linear user though affected by choice locations number points. A notable finding is varying impact overall changing environments, with heating less influential than cooling. also uncovers significant demographic variations strongly influenced differing temperatures across age groups, genders, climatic regions. For example, elderly populations exhibit decreased sensitivity, especially towards warmth. Gender differences significant, females experiencing warmer environments lower colder ones. Machine learning (ML)-based methods, classification tree-based support vector machine (SVM) techniques, dominate predicting comfort, leveraging data. While ML methods prevalent, statistical regression-based approaches offer valuable empirical insights. Thermo-physiological model-based provide reliable results incorporating detailed dynamics. identifies gap understanding how gender, age, regional influence diverse environments. study recommends conducting more nuanced experiments dissect these factors proposes integration individual variables into models personalize predictions.

Language: Английский

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Prediction of individual thermal comfort based on ensemble transfer learning method using wearable and environmental sensors

Building and Environment, Journal Year: 2021, Volume and Issue: 207, P. 108492 - 108492

Published: Oct. 28, 2021

Language: Английский

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A new thermal comfort model based on physiological parameters for the smart design and control of energy-efficient HVAC systems

Renewable and Sustainable Energy Reviews, Journal Year: 2022, Volume and Issue: 173, P. 113015 - 113015

Published: Dec. 2, 2022

Language: Английский

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Evaluation system of worker comfort for high geothermal tunnel during construction: A case study on the highway tunnel with the highest temperature in China

Tunnelling and Underground Space Technology, Journal Year: 2023, Volume and Issue: 135, P. 105028 - 105028

Published: Feb. 8, 2023

Language: Английский

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Computer vision to advance the sensing and control of built environment towards occupant-centric sustainable development: A critical review

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 192, P. 114165 - 114165

Published: Dec. 23, 2023

Language: Английский

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Comparison among different modeling approaches for personalized thermal comfort prediction when using personal comfort systems

Energy and Buildings, Journal Year: 2023, Volume and Issue: 285, P. 112873 - 112873

Published: Feb. 10, 2023

Language: Английский

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