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A Digital Twin (DT) Framework at Design and Construction Phases

EasyChair Preprint no. 10884

9 pagesDate: September 11, 2023

Abstract

In the construction industry, Digital Twin (DT) encompasses real-time data collection on building models, operational parameters, and other pertinent factors. DT utilizes multidimensional, multi-perspective, and multi-disciplinary simulation processes to enable information mapping via virtual simulations. This study proposes a preliminary framework for applying DT core technologies such as Building Information Modeling (BIM) and the Internet of Things (IoT) into the design and construction phases of building projects, drawing on a comprehensive analysis of DT concepts, technologies, and applications within the construction field. Furthermore, semi-structured interviews and a case study were conducted to validate the framework, with the aim of improving construction site monitoring, quality, and safety. By providing access to a wealth of project information and data, DT can help decrease construction costs, improve quality, and enhance stakeholder management practices.

Keyphrases: Building Information Modeling, Digital Twin, Framework, Internet of Things

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:10884,
  author = {Enxi Cao and Fangyu Guo and Kaiyang Wang},
  title = {A Digital Twin (DT) Framework at Design and Construction Phases},
  howpublished = {EasyChair Preprint no. 10884},

  year = {EasyChair, 2023}}
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