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Modeling Methods of 3D Model in Digital Twins

Ruijun Liu1, Haisheng Li1,*, Zhihan Lv2

1 School of Computer Science and Engineering, Beijing Technology and Business University, Beijing, 100080, China
2 Department of Game Design, Faculty of Art, Uppsala University, Uppsala, S-75105, Sweden

* Corresponding Author: Haisheng Li. Email: email

Computer Modeling in Engineering & Sciences 2023, 136(2), 985-1022. https://doi.org/10.32604/cmes.2023.023154

Abstract

To understand the current application and development of 3D modeling in Digital Twins (DTs), abundant literatures on DTs and 3D modeling are investigated by means of literature review. The transition process from 3D modeling to DTs modeling is analyzed, as well as the current application of DTs modeling in various industries. The application of 3D DTs modeling in the fields of smart manufacturing, smart ecology, smart transportation, and smart buildings in smart cities is analyzed in detail, and the current limitations are summarized. It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles. At the same time, the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data, Internet of Things, Cloud Computing, Artificial Intelligence, and game technology. Therefore, although some results have been achieved, there are still limitations. This work aims to provide a good theoretical support for the further development of 3D DTs modeling.

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APA Style
Liu, R., Li, H., Lv, Z. (2023). Modeling methods of 3D model in digital twins. Computer Modeling in Engineering & Sciences, 136(2), 985-1022. https://doi.org/10.32604/cmes.2023.023154
Vancouver Style
Liu R, Li H, Lv Z. Modeling methods of 3D model in digital twins. Comput Model Eng Sci. 2023;136(2):985-1022 https://doi.org/10.32604/cmes.2023.023154
IEEE Style
R. Liu, H. Li, and Z. Lv "Modeling Methods of 3D Model in Digital Twins," Comput. Model. Eng. Sci., vol. 136, no. 2, pp. 985-1022. 2023. https://doi.org/10.32604/cmes.2023.023154



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