Digital Twin-Based Automated Green Building Assessment Framework

Amos Darko, Jayasanka THANAWEERA ACHCHIGE, Albert P.C. Chan, Farzad Jalaei, Mark Kyeredey Ansah, De Graft Joe Opoku

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Accurate green building assessment (GBA) represents one of the best opportunities to understand the holistic sustainability strengths and weaknesses of existing buildings to inform their retrofitting decisions. However, the current process for GBA of existing buildings is very challenging, tedious, complex, time-consuming and costly, and suffers from lack of important data and information. Moreover, most GBA results are not leveraged to retrofit and improve the sustainability performance of existing buildings – they are mostly for just recognition and market edge. To address these limitations, this study aims to develop a framework for using Digital Twin (DT) technology to automate and improve GBA. Although unavailable static building data can be obtained from scan-to-building information modelling (BIM) process, real-time dynamic data cannot. Hence, real-time dynamic data from the internet of things (IoT) sensors and other data should be integrated into the BIM model to create the DT model of the building. A plug-in software can then be deployed to assess the sustainability performance level of the building within the DT environment automatically. The framework is based on the Building Environmental Assessment Method (BEAM) Plus, which is Hong Kong’s leading GBA system. A real DT should feedback into the physical twin after receiving and processing data from it. Therefore, the automated GBA results should inform retrofitting decisions of the physical building. This study contributes to the understanding of how DT can be used to automate and improve GBA, and how the results can be used to improve retrofitting decision-making.

Original languageEnglish
Title of host publicationAdvances in Information Technology in Civil and Building Engineering - Proceedings of ICCCBE 2022 - Volume 1
EditorsSebastian Skatulla, Hans Beushausen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages597-613
Number of pages17
ISBN (Print)9783031353987
DOIs
Publication statusPublished - Jan 2024
Event19th International Conference on Computing in Civil and Building Engineering, ICCCBE 2022 - Cape Town, South Africa
Duration: 26 Oct 202228 Oct 2022

Publication series

NameLecture Notes in Civil Engineering
Volume357
ISSN (Print)2366-2557
ISSN (Electronic)2366-2565

Conference

Conference19th International Conference on Computing in Civil and Building Engineering, ICCCBE 2022
Country/TerritorySouth Africa
CityCape Town
Period26/10/2228/10/22

Keywords

  • Accurate Green Building Assessment
  • BEAM Plus
  • Digital Twin
  • Existing Buildings
  • Plug-in
  • Retrofitting

ASJC Scopus subject areas

  • Civil and Structural Engineering

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