| Title |
Digital twin-supported smart city: Status, challenges and future research directions |
| ID_Doc |
37987 |
| Authors |
Wang, H; Chen, XW; Jia, F; Cheng, XJ |
| Title |
Digital twin-supported smart city: Status, challenges and future research directions |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.eswa.2023.119531 |
| Abstract |
A city can be considered a carrier of multiple sources of data and information that are updated in real time and experiences continuous operation and development. Therefore, a system that can obtain and manage data/information gathered from different physical objects in a city in real time is needed. Digital twin (DT) technology is a virtual representation of an object or system that spans its lifecycle; it is updated from real-time data and uses simulation, machine learning and reasoning to help with decision-making. However, how to apply these features of the DT to better manage smart cities (SCs) has not yet been systematically summarized and analysed. In this study, 202 papers on DT-supported SCs are reviewed, based on which the drivers and challenges of applying DTsupported SCs and the solutions for the challenges were identified. In addition, this study explored the possible outcomes of applying DT-supported technologies in SCs. This study also contributes to the DT-supported SCs for city management research and practice. |
| Author Keywords |
Digital twin; Smart city; Information management; Data management; Literature review |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000922151900001 |
| WoS Category |
Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Operations Research & Management Science |
| Research Area |
Computer Science; Engineering; Operations Research & Management Science |
| PDF |
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