Digital twin-supported smart city: Status, challenges and future research directions

Hao Wang; Xiaowei Chen; Fu Jia; Xiaojuan Cheng

doi:10.1016/j.eswa.2023.119531

Digital twin-supported smart city: Status, challenges and future research directions

Hao Wang, Xiaowei Chen, Fu Jia^*, Xiaojuan Cheng

^*Corresponding author for this work

The York Management School

Research output: Contribution to journal › Article › peer-review

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 DT-supported 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.

Original language	English
Article number	119531
Number of pages	16
Journal	Expert systems with applications
Volume	217
Early online date	14 Jan 2023
DOIs	https://doi.org/10.1016/j.eswa.2023.119531
Publication status	Published - 1 May 2023

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10.1016/j.eswa.2023.119531

Cite this

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title = "Digital twin-supported smart city: Status, challenges and future research directions",

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 DT-supported 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.",

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AU - Wang, Hao

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