Digital Twin Perspective of Fourth Industrial and Healthcare Revolution

• Published in: IEEE access Vol. 10; pp. 25732 - 25754
• Main Authors: Khan, Sagheer, Arslan, Tughrul, Ratnarajah, Tharmalingam
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 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
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3156062

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.