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Lookup NU author(s): Professor Mohamad Kassem
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. The concept of digital twins is proposed as a new technology-led advancement to support the processes of the design, construction, and operation of built assets. Commonalities between the emerging definitions of digital twins describe them as digital or cyber environments that are bidirectionally-linked to their physical or real-life replica to enable simulation and data-centric decision making. Studies have started to investigate their role in the digitalization of asset delivery, including the management of built assets at different levels within the building and infrastructure sectors. However, questions persist regarding their actual applications and implementation chal-lenges, including their integration with other digital technologies (i.e., building information modeling, virtual and augmented reality, Internet of Things, artificial intelligence, and cloud computing). Within the built environment context, this study seeks to analyze the definitions and characteristics of a digital twin, its interactions with other digital technologies used in built asset delivery and operation, and its applications and challenges. To achieve this aim, the research utilizes a thorough literature review and semi-structured interviews with ten industry experts. The literature review explores the merits and the relevance of digital twins relative to existing digital technologies and highlights potential applications and challenges for their implementation. The data from the semi-structured interviews are classified into five themes: definitions and enablers of digital twins, applications and benefits, implementation challenges, existing practical applications, and future development. The findings provide a point of departure for future research aimed at clarifying the relationship between digital twins and other digital technologies and their key implementation challenges.
Author(s): Shahzad M, Shafiq MT, Douglas D, Kassem M
Publication type: Article
Publication status: Published
Online publication date: 25/01/2022
Acceptance date: 20/01/2022
Date deposited: 07/07/2022
ISSN (electronic): 2075-5309
Publisher: MDPI AG
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