Minerva, R, Lee, GM and Crespi, N (2020) Digital Twin in the IoT context: a survey on technical features, scenarios and architectural models. Proceedings of the IEEE, 108 (10). pp. 1785-1824. ISSN 0018-9219

Preview

Text cDT version submitted.pdf - Accepted Version Download (3MB) | Preview

Abstract

Digital Twin is an emerging concept that is gaining attention in various industries. It refers to the ability to clone a physical object into a software counterpart. The softwarized object, termed logical object, reflects all the important properties and characteristics of the original object within a specific application context. To fully determine the expected properties of the Digital Twin, this paper surveys the state of the art starting from the original definition within the manufacturing industry. It takes into account related proposals emerging in other fields, namely, Augmented and Virtual Reality (e.g., avatars), Multi-agent systems, and virtualization. This survey thereby allows for the identification of an extensive set of Digital Twin features that point to the “softwarization” of physical objects. To properly consolidate a shared Digital Twin definition, a set of foundational properties is identified and proposed as a common ground outlining the essential characteristics (must-haves) of a Digital Twin. Once the Digital Twin definition has been consolidated, its technical and business value is discussed in terms of applicability and opportunities. Four application scenarios illustrate how the Digital Twin concept can be used and how some industries are applying it. The scenarios also lead to a generic DT architectural Model. This analysis is then complemented by the identification of software architecture models and guidelines in order to present a general functional framework for the Digital Twin. The paper, eventually, analyses a set of possible evolution paths for the Digital Twin considering its possible usage as a major enabler for the softwarization process.

Item Type:	Article
Additional Information:	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords:	0801 Artificial Intelligence and Image Processing, 0903 Biomedical Engineering, 0906 Electrical and Electronic Engineering
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Computer Science & Mathematics
Publisher:	IEEE
Date Deposited:	27 May 2020 09:56
Last Modified:	18 Aug 2022 11:00
DOI or ID number:	10.1109/JPROC.2020.2998530
URI:	https://researchonline.ljmu.ac.uk/id/eprint/13014

View Item