The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.
Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment
Open accessAbstract
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.
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Cites
Digital Twin in Industry: State-of-the-Art
Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2873186 · Cited by 4,391
Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems
Grieves, M., & Vickers, J. (2017) · Transdisciplinary Perspectives on Complex Systems · doi:10.1007/978-3-319-38756-7_4 · Cited by 3,727 · cited 2×
“The DT aggregate/environment (DTD/E) refers to multi-domain applications for employing the DT to meet various needs [82].”
BackgroundDigital Twin in manufacturing: A categorical literature review and classification
Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.08.474 · Cited by 3,612 · cited 2×
“, BIM) and DT as similar concepts or used them interchangeably [33,66,67].”
MethodDigital twin: Enabling technologies, challenges and open research
Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020) · IEEE Access · doi:10.1109/access.2020.2998358 · Cited by 2,965
Characterising the Digital Twin: A systematic literature review
Jones, D., Snider, C., Nassehi, A., Yon, J., & Hicks, B. (2020) · CIRP Journal of Manufacturing Science and Technology · doi:10.1016/j.cirpj.2020.02.002 · Cited by 2,422
The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles
Glaessgen, E., & Stargel, D. (2012) · 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA · doi:10.2514/6.2012-1818 · Cited by 2,404
Review of digital twin about concepts, technologies, and industrial applications
Liu, M., Fang, S., Dong, H., & Xu, C. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.017 · Cited by 1,875
Shaping the digital twin for design and production engineering
Schleich, B., Anwer, N., Mathieu, L., & Wartzack, S. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.04.040 · Cited by 1,305
The Social Shaping of Technology
Hoch, P. K., MacKenzie, D., & Wajcman, J. (1987) · Technology and Culture · doi:10.2307/3105489 · Cited by 1,040
The Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0
Uhlemann, T. H.-J., Lehmann, C., & Steinhilper, R. (2017) · Procedia CIRP · doi:10.1016/j.procir.2016.11.152 · Cited by 994
Cited by
A survey on AI-driven digital twins in Industry 4.0: smart manufacturing and advanced robotics
Huang, Z., Shen, Y., Li, J., Fey, M., & Brecher, C. (2021) · Sensors · doi:10.3390/s21196340 · Cited by 418
Technologies for digital twin applications in construction
Tuhaise, V. V., Tah, J. H. M., & Abanda, F. H. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.104931 · Cited by 308
Digital twins and industrial internet of things: uncovering operational intelligence in Industry 4.0
Attaran, S., Attaran, M., & Celik, B. G. (2024) · Decision Analytics Journal · doi:10.1016/j.dajour.2024.100398 · Cited by 122
Digital Revolution in the Energy Sector: Effects of Using Digital Twin Technology
Strielkowski, W., Rausser, G., & Kuzmin, E. (2022) · Lecture Notes in Information Systems and Organisation · doi:10.1007/978-3-030-94617-3_4 · Cited by 38
A review of drivers and barriers of Digital Twin adoption in building project development processes
Jahangir, M. F., Schultz, C. P. L., & Kamari, A. (2024) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2024.008 · Cited by 34
Metadata
- Authors
- Sepasgozar, S. M. E.
- Venue
- Buildings
- Publisher
- MDPI AG
- Published
- 2021-04-02
- Volume
- 11
- Issue
- 4
- Pages
- 151
- ISSN
- 2075-5309 (ISSN-L)
- OpenAlex
- W3150590266
- Cited by
- 367
- References
- 88
- FWCI
- 27.47
- Type
- journal article
- Language
- en
- Open access
- gold
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