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Review

Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment

School of Built Environment, Faculty of Arts, Design & Architecture, University of New South Wales, Sydney 2052, Australia
Academic Editor: Derek Clements-Croome
Buildings 2021, 11(4), 151; https://doi.org/10.3390/buildings11040151
Received: 24 February 2021 / Revised: 30 March 2021 / Accepted: 31 March 2021 / Published: 2 April 2021
(This article belongs to the Special Issue Sustainability and Energy Efficiency in Smart Cities and Construction)
Construction projects and cities account for over 50% of carbon emissions and energy consumption. Industry 4.0 and digital transformation may increase productivity and reduce energy consumption. A digital twin (DT) is a key enabler in implementing Industry 4.0 in the areas of construction and smart cities. It is an emerging technology that connects different objects by utilising the advanced Internet of Things (IoT). As a technology, it is in high demand in various industries, and its literature is growing exponentially. Previous digital modeling practices, the use of data acquisition tools, human–computer–machine interfaces, programmable cities, and infrastructure, as well as Building Information Modeling (BIM), have provided digital data for construction, monitoring, or controlling physical objects. However, a DT is supposed to offer much more than digital representation. Characteristics such as bi-directional data exchange and real-time self-management (e.g., self-awareness or self-optimisation) distinguish a DT from other information modeling systems. The need to develop and implement DT is rising because it could be a core technology in many industrial sectors post-COVID-19. This paper aims to clarify the DT concept and differentiate it from other advanced 3D modeling technologies, digital shadows, and information systems. It also intends to review the state of play in DT development and offer research directions for future investigation. It recommends the development of DT applications that offer rapid and accurate data analysis platforms for real-time decisions, self-operation, and remote supervision requirements post-COVID-19. The discussion in this paper mainly focuses on the Smart City, Engineering and Construction (SCEC) sectors. View Full-Text
Keywords: digital shadow; digital twin; sensor; internet of things; smart city; engineering; construction; energy; cyber-physical; deep learning; blockchain; Intelligent construction 4.0 digital shadow; digital twin; sensor; internet of things; smart city; engineering; construction; energy; cyber-physical; deep learning; blockchain; Intelligent construction 4.0
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MDPI and ACS Style

Sepasgozar, S.M.E. Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment. Buildings 2021, 11, 151. https://doi.org/10.3390/buildings11040151

AMA Style

Sepasgozar SME. Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment. Buildings. 2021; 11(4):151. https://doi.org/10.3390/buildings11040151

Chicago/Turabian Style

Sepasgozar, Samad M.E. 2021. "Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment" Buildings 11, no. 4: 151. https://doi.org/10.3390/buildings11040151

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