東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Advancing Comfort Technology and Ana...

Kim, Jihyun.

Linked to FindBook

Google Book

Amazon

博客來

Advancing Comfort Technology and Analytics to Personalize Thermal Experience in the Built Environment.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advancing Comfort Technology and Analytics to Personalize Thermal Experience in the Built Environment./
Author:	Kim, Jihyun.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	120 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-03, Section: B.
Contained By:	Dissertations Abstracts International80-03B.
Subject:	Architectural engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10744089
ISBN:	9780438323612

Advancing Comfort Technology and Analytics to Personalize Thermal Experience in the Built Environment.
Kim, Jihyun.

Advancing Comfort Technology and Analytics to Personalize Thermal Experience in the Built Environment. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 120 p.

Source: Dissertations Abstracts International, Volume: 80-03, Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2019.

This item must not be sold to any third party vendors.

Nearly 60% of global energy consumption in buildings is used for space heating and cooling to provide occupant comfort. Yet, a large portion of occupants are dissatisfied with the buildings' thermal environment. There are many reasons for thermal dissatisfaction in buildings, but a fundamental cause is the current practice of delivering uniform thermal conditions based on universal rules, without accounting for individual differences in comfort requirements. To address these issues, a growing body of research has emerged to better reflect individual' comfort requirements. This dissertation contributes to this research by providing the following primary innovations: 1) Internet-connected personal comfort system (PCS) and 2) personal comfort models that can help to deliver personalized comfort experiences in occupied spaces. In particular, I developed and field-tested the new capabilities of PCS (data reporting, wireless connectivity) that could support individualized learning and coordinated controls with other building systems. I also proposed a new framework for thermal comfort modeling - personal comfort models that can predict individuals' thermal comfort, instead of the average response of a large population, using Internet of Things and machine learning. As a practical use case, I developed a set of personal comfort models using the PCS field study data to demonstrate how the proposed framework can be implemented. The results showed that personal comfort models produced superior accuracy over conventional comfort models (PMV, adaptive) and that PCS heating and cooling control behavior was a strong predictor of individuals' thermal preference and could be used as an individualized comfort feedback for HVAC controls. The results of this dissertation showed a synergistic effect between PCS and personal comfort models that could enable occupant-centric comfort management in buildings.

ISBN: 9780438323612Subjects--Topical Terms:

3174102
Architectural engineering.

Advancing Comfort Technology and Analytics to Personalize Thermal Experience in the Built Environment.
LDR:03002nmm a2200313 4500 001 2207626
005 20190920102350.5
008 201008s2019 ||||||||||||||||| ||eng d
020 $a 9780438323612
035 $a (MiAaPQ)AAI10744089
035 $a (MiAaPQ)berkeley:17684
035 $a AAI10744089
040 $a MiAaPQ $c MiAaPQ
100 1 $a Kim, Jihyun. $3 1910175
245 1 0 $a Advancing Comfort Technology and Analytics to Personalize Thermal Experience in the Built Environment.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 120 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-03, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Brager, Gail.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a Nearly 60% of global energy consumption in buildings is used for space heating and cooling to provide occupant comfort. Yet, a large portion of occupants are dissatisfied with the buildings' thermal environment. There are many reasons for thermal dissatisfaction in buildings, but a fundamental cause is the current practice of delivering uniform thermal conditions based on universal rules, without accounting for individual differences in comfort requirements. To address these issues, a growing body of research has emerged to better reflect individual' comfort requirements. This dissertation contributes to this research by providing the following primary innovations: 1) Internet-connected personal comfort system (PCS) and 2) personal comfort models that can help to deliver personalized comfort experiences in occupied spaces. In particular, I developed and field-tested the new capabilities of PCS (data reporting, wireless connectivity) that could support individualized learning and coordinated controls with other building systems. I also proposed a new framework for thermal comfort modeling - personal comfort models that can predict individuals' thermal comfort, instead of the average response of a large population, using Internet of Things and machine learning. As a practical use case, I developed a set of personal comfort models using the PCS field study data to demonstrate how the proposed framework can be implemented. The results showed that personal comfort models produced superior accuracy over conventional comfort models (PMV, adaptive) and that PCS heating and cooling control behavior was a strong predictor of individuals' thermal preference and could be used as an individualized comfort feedback for HVAC controls. The results of this dissertation showed a synergistic effect between PCS and personal comfort models that could enable occupant-centric comfort management in buildings.
590 $a School code: 0028.
650 4 $a Architectural engineering. $3 3174102
690 $a 0462
710 2 $a University of California, Berkeley. $b Architecture. $3 1673934
773 0 $t Dissertations Abstracts International $g 80-03B.
790 $a 0028
791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10744089