Fuller, A ORCID: https://orcid.org/0000-0002-3391-2407, Fan, Z, Day, CR ORCID: https://orcid.org/0000-0001-9707-9189 and Barlow, C (2020) Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access, 8. 108952 - 108971.

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Abstract

Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.

Item Type: Article
Additional Information: The final version of this record can be found with all relevant information at; https://ieeexplore.ieee.org/document/9103025
Uncontrolled Keywords: applications, Computational modeling, Data analysis, Data models, deep learning, Digital twins, enabling technologies, industrial Internet of Things (IIoT), Internet of Things, Internet of Things (IoT), literature review, machine learning, Manufacturing, Smart cities
Subjects: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Natural Sciences > School of Computing and Mathematics
Depositing User: Symplectic
Date Deposited: 05 Aug 2020 13:51
Last Modified: 05 Aug 2020 13:51
URI: https://eprints.keele.ac.uk/id/eprint/8471

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