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Measuring Human Comfort for Smart Building Application: Experimental Set-Up using WSN

Published: 18 October 2018 Publication History

Abstract

Realizing the importance of the effect of thermal comfort on the health and productivity of people, many researches have been done in this area at the beginning of last century. These works are carried out in climatic chambers or in situ, or models or with human beings. They aim to identify the conditions of comfort and acceptability of the thermal environment without trying to understand the mechanisms involved. Following this work, several indices of thermal comfort have been developed based on models of thermal comfort. The developed models are different; there are the physical models are often measuring instruments whose physical responses to the thermal environment are similar to those of the human body. Besides, one of the key objectives in studying the behavior of people in certain environmental and personal conditions is to predict the degree of satisfaction/dissatisfaction with the thermal environment. The objective is to propose a predictive model of the thermal sensation of the users of indoor environments using subjective variables.

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Cited By

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  • (2024)AI-Based Controls for Thermal Comfort in Adaptable Buildings: A ReviewBuildings10.3390/buildings1411351914:11(3519)Online publication date: 4-Nov-2024
  • (2021)Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniquesRenewable and Sustainable Energy Reviews10.1016/j.rser.2021.110969144(110969)Online publication date: Jul-2021

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  1. Measuring Human Comfort for Smart Building Application: Experimental Set-Up using WSN

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    cover image ACM Other conferences
    ICSDE'18: Proceedings of the 2nd International Conference on Smart Digital Environment
    October 2018
    214 pages
    ISBN:9781450365079
    DOI:10.1145/3289100
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 18 October 2018

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    Author Tags

    1. HVAC
    2. Human Thermal Comfort
    3. Indoor Environment
    4. Predictive Model
    5. Productivity
    6. Subjective Variables
    7. Thermal Sensation

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    ICSDE'18 Paper Acceptance Rate 32 of 80 submissions, 40%;
    Overall Acceptance Rate 68 of 219 submissions, 31%

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    View all
    • (2024)AI-Based Controls for Thermal Comfort in Adaptable Buildings: A ReviewBuildings10.3390/buildings1411351914:11(3519)Online publication date: 4-Nov-2024
    • (2021)Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniquesRenewable and Sustainable Energy Reviews10.1016/j.rser.2021.110969144(110969)Online publication date: Jul-2021

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