Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM)

Recently there has been growing recognition of the value of Building Information Modeling (BIM) in the Architecture, Engineering and Construction (AEC) industry. However, building information are often displayed in text or 2D graph only, making it hard for the management to clearly understand the...

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Main Author: Lee, Han Xiang
Format: Final Year Project
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.22580 /
Published: Universiti Teknologi PETRONAS 2019
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access: http://utpedia.utp.edu.my/22580/1/Final%20Dissertation.pdf
http://utpedia.utp.edu.my/22580/
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spelling utp-utpedia.225802022-02-17T02:15:29Z http://utpedia.utp.edu.my/22580/ Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM) Lee, Han Xiang TA Engineering (General). Civil engineering (General) Recently there has been growing recognition of the value of Building Information Modeling (BIM) in the Architecture, Engineering and Construction (AEC) industry. However, building information are often displayed in text or 2D graph only, making it hard for the management to clearly understand the thermal environment of the building. While BIM model may present the thermal comfort in a three-dimensional space, it is usually limited by the skills requirement of the workers and its incapability to support real-time data that is constantly changing. In order to make BIM technology more valuable in the Operational and Management (O&M) stage of building, this project had developed a thermal comfort level analysis system by applying Internet-of-Things (IoT) technology to collect data from sensors, then analyse them to determine thermal comfort level, and present it in the BIM model through the webpage platform provided by Autodesk Forge. To determine the thermal comfort level, the Predicted Mean Vote (PMV) model is used to compute the thermal comfort level based on 6 primary influencing factors which consists of Dry Bulb Temperature, Mean Radiant Temperature, Relative Humidity, Air Velocity, Metabolic Rate and Clothing Level. Universiti Teknologi PETRONAS 2019-05 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/22580/1/Final%20Dissertation.pdf Lee, Han Xiang (2019) Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM). Universiti Teknologi PETRONAS. (Submitted)
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Lee, Han Xiang
Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM)
description Recently there has been growing recognition of the value of Building Information Modeling (BIM) in the Architecture, Engineering and Construction (AEC) industry. However, building information are often displayed in text or 2D graph only, making it hard for the management to clearly understand the thermal environment of the building. While BIM model may present the thermal comfort in a three-dimensional space, it is usually limited by the skills requirement of the workers and its incapability to support real-time data that is constantly changing. In order to make BIM technology more valuable in the Operational and Management (O&M) stage of building, this project had developed a thermal comfort level analysis system by applying Internet-of-Things (IoT) technology to collect data from sensors, then analyse them to determine thermal comfort level, and present it in the BIM model through the webpage platform provided by Autodesk Forge. To determine the thermal comfort level, the Predicted Mean Vote (PMV) model is used to compute the thermal comfort level based on 6 primary influencing factors which consists of Dry Bulb Temperature, Mean Radiant Temperature, Relative Humidity, Air Velocity, Metabolic Rate and Clothing Level.
format Final Year Project
author Lee, Han Xiang
author_sort Lee, Han Xiang
title Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM)
title_short Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM)
title_full Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM)
title_fullStr Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM)
title_full_unstemmed Developing Thermal Comfort Level Analysis System using Predicted Mean Vote (PMV) and Building Information Modeling (BIM)
title_sort developing thermal comfort level analysis system using predicted mean vote (pmv) and building information modeling (bim)
publisher Universiti Teknologi PETRONAS
publishDate 2019
url http://utpedia.utp.edu.my/22580/1/Final%20Dissertation.pdf
http://utpedia.utp.edu.my/22580/
_version_ 1741195837072998400
score 11.62408

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