Vol.15, No.3, 2021, pp.183-206, doi:10.32604/sdhm.2021.018247
OPEN ACCESS
REVIEW
Digital Twin-Driven Intelligent Construction: Features and Trends
  • Hao Zhang1, Yongqi Zhou1, Huaxin Zhu2, Dragoslav Sumarac1,3, Maosen Cao4,*
1 College of Civil and Architecture Engineering, Chuzhou University, Chuzhou, 23900, China
2 Jiangsu Zhongji Engineering Technology Research Co., Ltd., Nantong, 226001, China
3 Department of Technical Sciences, State University of Novi Pazar, Novi Pazar, 36300, Serbia
4 College of Mechanics and Materials, Hohai University, Nanjing, 210098, China
* Corresponding Author: Maosen Cao. Email:
Received 01 January 2021; Accepted 15 July 2021; Issue published 07 September 2021
Abstract
Digital twin (DT) can achieve real-time information fusion and interactive feedback between virtual space and physical space. This technology involves a digital model, real-time information management, comprehensive intelligent perception networks, etc., and it can drive the rapid conceptual development of intelligent construction (IC) such as smart factories, smart cities, and smart medical care. Nevertheless, the actual use of DT in IC is partially pending, with numerous scientific factors still not clarified. An overall survey on pending issues and unsolved scientific factors is needed for the development of DT-driven IC. To this end, this study aims to provide a comprehensive review of the state of the art and state of the use of DT-driven IC. The use of DT in planning, design, manufacturing, operation, and maintenance management of IC is demonstrated and analyzed, following which the driving functions of DT in IC are detailed from four aspects: information perception and analysis, data mining and modeling, state assessment and prediction, intelligent optimization and decision-making. Furthermore, the future direction of research, using DT in IC, is presented with some comments and suggestions. This work will help researchers gain in-depth and systematic understanding of the use of DT, and help practitioners to better promote its implementation in IC.
Keywords
Digital twin; intelligent construction; information perception and interaction; data mining and modeling; state assessment and prediction; intelligent optimization and decision; big data; virtual and physical spaces
Cite This Article
Zhang, H., Zhou, Y., Zhu, H., Sumarac, D., Cao, M. (2021). Digital Twin-Driven Intelligent Construction: Features and Trends. Structural Durability & Health Monitoring, 15(3), 183–206.
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