Digital twin: Data exploration, architecture, implementation and future.

Md Shezad Dihan, Anwar Islam Akash, Zinat Tasneem, Prangon Das, Sajal Kumar Das, Md Robiul Islam, Md Manirul Islam, Faisal R Badal, Md Firoj Ali, Md Hafiz Ahamed, Sarafat Hussain Abhi, Subrata Kumar Sarker, Md Mehedi Hasan
Author Information
  1. Md Shezad Dihan: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  2. Anwar Islam Akash: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  3. Zinat Tasneem: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  4. Prangon Das: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  5. Sajal Kumar Das: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  6. Md Robiul Islam: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  7. Md Manirul Islam: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  8. Faisal R Badal: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  9. Md Firoj Ali: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  10. Md Hafiz Ahamed: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  11. Sarafat Hussain Abhi: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  12. Subrata Kumar Sarker: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  13. Md Mehedi Hasan: Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.

Abstract

A Digital Twin (DT) is a digital copy or virtual representation of an object, process, service, or system in the real world. It was first introduced to the world by the National Aeronautics and Space Administration (NASA) through its Apollo Mission in the '60s. It can successfully design a virtual object from its physical counterpart. However, the main function of a digital twin system is to provide a bidirectional data flow between the physical and the virtual entity so that it can continuously upgrade the physical counterpart. It is a state-of-the-art iterative method for creating an autonomous system. Data is the brain or building block of any digital twin system. The articles that are found online cover an individual field or two at a time regarding data analysis technology. There are no overall studies found regarding this manner online. The purpose of this study is to provide an overview of the data level in the digital twin system, and it involves the data at various phases. This paper will provide a comparative study among all the fields in which digital twins have been applied in recent years. Digital twin works with a vast amount of data, which needs to be organized, stored, linked, and put together, which is also a motive of our study. Data is essential for building virtual models, making cyber-physical connections, and running intelligent operations. The current development status and the challenges present in the different phases of digital twin data analysis have been discussed. This paper also outlines how DT is used in different fields, like manufacturing, urban planning, agriculture, medicine, robotics, and the military/aviation industry, and shows a data structure based on every sector using recent review papers. Finally, we attempted to give a horizontal comparison based on the features of the data across various fields, to extract the commonalities and uniqueness of the data in different sectors, and to shed light on the challenges at the current level as well as the limitations and future of DT from a data standpoint.

Keywords

References

  1. Eur Heart J. 2020 Dec 21;41(48):4556-4564 [PMID: 32128588]
  2. IEEE Access. 2020 Oct 26;9:44173-44197 [PMID: 34786312]
  3. Sensors (Basel). 2022 Sep 14;22(18): [PMID: 36146313]
  4. Sensors (Basel). 2020 Oct 21;20(20): [PMID: 33096595]
  5. Comput Intell Neurosci. 2022 Jan 13;2022:7786441 [PMID: 35035466]
  6. Comput Math Methods Med. 2017;2017:6120820 [PMID: 29375652]
  7. Sensors (Basel). 2022 Jan 10;22(2): [PMID: 35062459]
  8. J Am Med Inform Assoc. 2022 Aug 16;29(9):1642-1653 [PMID: 35818340]

Word Cloud

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