Digital Twin Perspective of Fourth Industrial and Healthcare Revolution
Digital Twin (DT) is bringing revolution to our lives by a digital representation of the physical system. DT is the creation of the joint usage of various technologies like Cyber-Physical System (CPS), Internet of Things (IoT), Big Data, Edge Computing (EC), Artificial Intelligence (AI), and Machine...
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Published in | IEEE access Vol. 10; pp. 25732 - 25754 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Piscataway
IEEE
2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 2169-3536 2169-3536 |
DOI | 10.1109/ACCESS.2022.3156062 |
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Abstract | Digital Twin (DT) is bringing revolution to our lives by a digital representation of the physical system. DT is the creation of the joint usage of various technologies like Cyber-Physical System (CPS), Internet of Things (IoT), Big Data, Edge Computing (EC), Artificial Intelligence (AI), and Machine Learning (ML), etc. DTs are established to optimize a wide range of applications of industry, healthcare, smart cities, smart homes, etc. It is still in its early development stages. This paper fills the gaps by combining the extensive information on technologies utilized in the creation of DT in industry and healthcare. The paper focuses on studying the characteristics of DT, communication technologies and tools utilized in the creation of DT models, reference models, standards, and the researcher's recent work in smart manufacturing and healthcare. Challenges and open issues that need attention are also discussed. |
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AbstractList | Digital Twin (DT) is bringing revolution to our lives by a digital representation of the physical system. DT is the creation of the joint usage of various technologies like Cyber-Physical System (CPS), Internet of Things (IoT), Big Data, Edge Computing (EC), Artificial Intelligence (AI), and Machine Learning (ML), etc. DTs are established to optimize a wide range of applications of industry, healthcare, smart cities, smart homes, etc. It is still in its early development stages. This paper fills the gaps by combining the extensive information on technologies utilized in the creation of DT in industry and healthcare. The paper focuses on studying the characteristics of DT, communication technologies and tools utilized in the creation of DT models, reference models, standards, and the researcher’s recent work in smart manufacturing and healthcare. Challenges and open issues that need attention are also discussed. |
Author | Khan, Sagheer Arslan, Tughrul Ratnarajah, Tharmalingam |
Author_xml | – sequence: 1 givenname: Sagheer orcidid: 0000-0002-9027-8860 surname: Khan fullname: Khan, Sagheer email: s.khan-35@sms.ed.ac.uk organization: School of Engineering, The University of Edinburgh, Edinburgh, U.K – sequence: 2 givenname: Tughrul surname: Arslan fullname: Arslan, Tughrul organization: School of Engineering, The University of Edinburgh, Edinburgh, U.K – sequence: 3 givenname: Tharmalingam orcidid: 0000-0002-7636-1246 surname: Ratnarajah fullname: Ratnarajah, Tharmalingam organization: School of Engineering, The University of Edinburgh, Edinburgh, U.K |
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SubjectTerms | Artificial intelligence big data analytics cloud communication technologies Communications technology Cyber-physical systems digital twin Digital twins Edge computing fog Fourth Industrial Revolution Health care health care 4.0 Industries industry 4.0 Internet of Things Machine learning Medical services RAMI 4.0 Smart buildings Smart manufacturing |
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Title | Digital Twin Perspective of Fourth Industrial and Healthcare Revolution |
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