Impact of Digital Twins and Metaverse on Cities: History, Current Situation, and Application Perspectives
Source abstract
Abstract
To promote the expansion and adoption of Digital Twins (DTs) in Smart Cities (SCs), a detailed review of the impact of DTs and digitalization on cities is made to assess the progression of cities and standardization of their management mode. Combined with the technical elements of DTs, the coupling effect of DTs technology and urban construction and the internal logic of DTs technology embedded in urban construction are discussed. Relevant literature covering the full range of DTs technologies and their applications is collected, evaluated, and collated, relevant studies are concatenated, and relevant accepted conclusions are summarized by modules. First, the historical process and construction content of a Digital City (DC) under modern demand are analyzed, and the main ideas of a DC design and construction are discussed in combination with the key technology of DTs. Then, the metaverse is the product of the combination of various technologies in different scenes. It is a key component to promote the integration of the real world and the digital world and can provide more advanced technical support in the construction of the DC. DTs urban technology architecture is composed of an infrastructure terminal information center terminal and application server end. Urban intelligent management is realized through physical urban data collection, transmission, processing, and digital urban visualization. The construction of DTs urban platform can improve the city’s perception and decision-making ability and bring a broader vision for future planning and progression. The interactive experience of the virtual world covered by the metaverse can effectively support and promote the integration of the virtual and real, and will also greatly promote the construction of SCs. In summary, this work is of important reference value for the overall development and practical adoption of DTs cities, which improves the overall operation efficiency and the governance level of cities.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Smart Cities and Technologies · Air Quality Monitoring and Forecasting · Digital Transformation in Industry
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Game Design, Faculty of Arts, Uppsala University, SE-75105 Uppsala, Sweden
Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100008, China
Centre for Transport Studies, Imperial College London, London SW7 2AZ, UK
Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi P.O. Box 54115, United Arab Emirates
References (100+)
Show source-provided references
1. Information security of Russia in the digital economy: The economic and legal aspects10.14505//jarle.v9.1(31).12 ↗
2. International entrepreneurship in the post Covid world10.1016/j.jwb.2020.101143 ↗
3. Functioning of agroindustrial complex in the conditions of digital economy
4. A proactive role of IoT devices in building smart cities10.1016/j.iotcps.2021.08.001 ↗
5. Sensible and secure IoT communication for digital twins, cyber twins, web twins10.1016/j.iotcps.2021.12.003 ↗
6. Industrial internet of things: Recent advances, enabling technologies and open challenges10.1016/j.compeleceng.2019.106522 ↗
7. Utilizing geospatial information to implement SDGs and monitor their Progress10.1007/s10661-019-7996-9 ↗
8. Assessment of municipal solid waste selective collection scenarios with geographic information systems in Bolivia10.1016/j.wasman.2019.12.010 ↗
9. Planning utility infrastructure requirements for smart cities using the integration between BIM and GIS10.1016/j.scs.2020.102120 ↗
10. Smart Earth Technologies: A pressing need for abating pollution for a better tomorrow10.1007/s11356-021-14481-6 ↗
11. National integrity strategy implementation in land administration to prevent corruption in Bangladesh10.1007/s43545-022-00352-5 ↗
12. Gella, G.W., Wendt, L., Lang, S., Tiede, D., Hofer, B., Gao, Y., and Braun, A. (2022). Mapping of Dwellings in IDP/Refugee Settlements from Very High-Resolution Satellite Imagery Using a Mask Region-Based Convolutional Neural Network. Remote Sens., 14.10.3390/rs14030689 ↗
13. A Metaheuristic Optimization Algorithm for energy efficiency in Digital Twins10.1016/j.iotcps.2022.08.001 ↗
14. Nguyen, D.D., Rohacs, J., and Rohacs, D. (2021). Autonomous flight trajectory control system for drones in smart city traffic management. ISPRS Int. J. Geo-Inf., 10.10.3390/ijgi10050338 ↗
15. Research on 3D urban landscape design and evaluation based on geographic information system10.1007/s12665-021-09886-y ↗
16. Digital twin networks: A survey10.1109/JIOT.2021.3079510 ↗
17. Multi-sensor information fusion for Internet of Things assisted automated guided vehicles in smart city10.1016/j.scs.2020.102539 ↗
18. Deep learning-based urban big data fusion in smart cities: Towards traffic monitoring and flow-preserving fusion10.1016/j.compeleceng.2020.106906 ↗
19. An intelligent urban traffic data fusion analysis method based on improved artificial neural network10.3233/JIFS-179273 ↗
20. Agostinelli, S., Cumo, F., Guidi, G., and Tomazzoli, C. (2021). Cyber-physical systems improving building energy management: Digital twin and artificial intelligence. Energies, 14.10.3390/en14082338 ↗
21. Novel system design and implementation for the smart city vertical market10.1109/MCOM.001.2000945 ↗
22. What is and What is not the Digital Earth?
23. Geovisualization with immersive virtual environments in theory and practice10.1080/17538947.2018.1501106 ↗
24. Digital Earth—From surface to deep: Introduction to the Special issue10.1007/s11707-021-0946-1 ↗
25. Energy-efficient SDN for Internet of Things in smart city10.1016/j.iotcps.2022.07.003 ↗
26. Product decision-making information systems, real-time sensor networks, and artificial intelligence-driven big data analytics in sustainable Industry 4.010.22381/emfm16220213 ↗
27. Urban utility tunnels as a long-term solution for the sustainable revitalization of historic centres: The case study of Pamplona-Spain10.1016/j.tust.2018.07.024 ↗
28. Cutting through the clutter of smart city definitions: A reading into the smart city perceptions in India10.1016/j.ccs.2019.05.005 ↗
29. Exploring the Smart City indexes and the role of macro factors for measuring cities smartness10.1007/s11205-019-02168-y ↗
30. Understanding smart cities as a glocal strategy: A comparison between Italy and China10.1016/j.techfore.2018.07.025 ↗
31. A cross-reading approach to smart city: A european perspective of chinese smart cities10.3390/smartcities1010003 ↗
32. WeChat as infrastructure: The techno-nationalist shaping of Chinese digital platforms10.1080/17544750.2019.1572633 ↗
33. Is smart city resilient? Evidence from China10.1016/j.scs.2019.101636 ↗
34. Quality inspection and analysis of three-dimensional geographic information model based on oblique photogrammetry
35. Research on rain slope stability and digital village construction in mountainous areas based on remote sensing images10.1007/s12517-021-08165-1 ↗
36. Lai, J.S., Peng, Y.C., Chang, M.J., and Huang, J.Y. (2020). Panoramic Mapping with Information Technologies for Supporting Engineering Education: A Preliminary Exploration. ISPRS Int. J. Geo-Inf., 9.10.3390/ijgi9110689 ↗
37. Intelligent manufacturing production line data monitoring system for industrial internet of things10.1016/j.comcom.2019.12.035 ↗
38. Predicting demand for air taxi urban aviation services using machine learning algorithms10.1016/j.jairtraman.2021.102043 ↗
39. Leveraging machine learning to understand urban change with net construction10.1016/j.landurbplan.2021.104239 ↗
40. Development and validation of a machine learning algorithm for predicting the risk of postpartum depression among pregnant women10.1016/j.jad.2020.09.113 ↗
41. Digital Twins by Study and Engineering10.46932/sfjdv2n1-022 ↗
42. Toward intelligent cyber-physical systems: Digital twin meets artificial intelligence10.1109/MCOM.001.2001237 ↗
43. The Internet of Things and fast data streams: Prospects for geospatial data science in emerging information ecosystems10.1080/15230406.2018.1503973 ↗
44. Applying Cross-modality Data Processing for Infarction Learning in Medical Internet of Things10.1109/JIOT.2021.3068775 ↗
45. Wu, Y., Lin, S., Peng, F., and Li, Q. (2019). Methods and application of archeological cloud platform for grand sites based on spatio-temporal big data. ISPRS Int. J. Geo-Inf., 8.10.3390/ijgi8090377 ↗
46. Big Data and cloud computing: Innovation opportunities and challenges10.1080/17538947.2016.1239771 ↗
47. Spatial cloud computing: How can the geospatial sciences use and help shape cloud computing?10.1080/17538947.2011.587547 ↗
48. Petroleum pipeline monitoring using an internet of things (IoT) platform10.1007/s42452-021-04225-z ↗
49. Design of low-energy buildings in densely populated urban areas based on IoT10.1016/j.egyr.2022.03.139 ↗
50. Topological integration of BIM and geospatial water utility networks across the building envelope10.1016/j.compenvurbsys.2020.101570 ↗
51. Blockchain technology and IoT-edge framework for sharing healthcare services10.1007/s00500-021-06041-4 ↗
52. A survey on the role of Internet of Things for adopting and promoting Agriculture 4.010.1016/j.jnca.2021.103107 ↗
53. Latif, S., Driss, M., Boulila, W., Huma, Z., Jamal, S.S., Idrees, Z., and Ahmad, J. (2021). Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions. Sensors, 21.10.3390/s21227518 ↗
54. Interconnected sensor networks and digital urban governance in data-driven smart sustainable cities
55. Gorelova, I., Dmitrieva, D., Dedova, M., and Savastano, M. (2021). Antecedents and consequences of digital entrepreneurial ecosystems in the interaction process with smart city development. Adm. Sci., 11.10.3390/admsci11030094 ↗
56. Fostering Innovation Through Intrapreneurship in the South African Public Service
57. Smart tourism cities: A duality of place where technology supports the convergence of touristic and residential experiences10.1080/10941665.2021.1897636 ↗
58. A social sensing approach for everyday urban problem-handling with the 12345-complaint hotline data10.1016/j.compenvurbsys.2022.101790 ↗
59. Macroscopic modeling and dynamic control of on-street cruising-for-parking of autonomous vehicles in a multi-region urban road network10.1016/j.trc.2021.103176 ↗
60. Llanquileo-Melgarejo, P., Molinos-Senante, M., Romano, G., and Carosi, L. (2021). Evaluation of the impact of separative collection and recycling of municipal solid waste on performance: An empirical application for Chile. Sustainability, 13.10.3390/su13042022 ↗
61. Implementation of solar energy in smart cities using an integration of artificial neural network, photovoltaic system and classical Delphi methods10.1016/j.scs.2021.103149 ↗
62. RIOMS: An intelligent system for operation and maintenance of urban roads using spatio-temporal data in smart cities10.1016/j.future.2020.09.010 ↗
63. Socialized Learning for Smart Cities: Cognitive Paradigm, Methodology, and Solution10.1109/MWC.111.2100023 ↗
64. An application framework of digital twin and its case study10.1007/s12652-018-0911-3 ↗
65. The digital twin implementation for linking the virtual representation of human-based production tasks to their physical counterpart in the factory-floor10.1080/0951192X.2018.1529430 ↗
66. A review on simulation in digital twin for aerospace, manufacturing and robotics10.1016/j.matpr.2020.06.446 ↗
67. Integrated digital twin and blockchain framework to support accountable information sharing in construction projects10.1016/j.autcon.2021.103688 ↗
68. Smart city as a smart service system: Human-computer interaction and smart city surveillance systems10.1016/j.chb.2021.106923 ↗
69. Kang, Y., Choi, N., and Kim, S. (2021). Searching for New Model of Digital Informatics for Human–Computer Interaction: Testing the Institution-Based Technology Acceptance Model (ITAM). Int. J. Environ. Res. Public Health, 18.10.3390/ijerph18115593 ↗
70. Banfi, F., and Previtali, M. (2021). Human–Computer Interaction Based on Scan-to-BIM Models, Digital Photogrammetry, Visual Programming Language and eXtended Reality (XR). Appl. Sci., 11.10.3390/app11136109 ↗
71. How to model and implement connections between physical and virtual models for digital twin application10.1016/j.jmsy.2020.05.012 ↗
72. The connotation of digital twin, and the construction and application method of shop-floor digital twin10.1016/j.rcim.2020.102075 ↗
73. Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues10.1016/j.rcim.2019.101837 ↗
74. Defining a digital twin-based cyber-physical production system for autonomous manufacturing in smart shop floors10.1080/00207543.2019.1566661 ↗
75. A digital twin-driven hybrid approach for the prediction of performance degradation in transmission unit of CNC machine tool10.1016/j.rcim.2021.102230 ↗
76. Liu, Z., Yuan, C., Sun, Z., and Cao, C. (2022). Digital Twins-Based Impact Response Prediction of Prestressed Steel Structure. Sensors, 22.10.3390/s22041647 ↗
77. Telemedicine in the COVID-19 pandemic: Motivations for integrated, interconnected, and community-based health delivery in resource-scarce settings?10.3389/fpsyt.2020.564452 ↗
78. A data-driven model of the COVID-19 spread among interconnected populations: Epidemiological and mobility aspects following the lockdown in Italy10.1007/s11071-021-06840-2 ↗
79. The COVID-19 (Coronavirus) pandemic: Consequences for occupational health10.5271/sjweh.3893 ↗
80. Intelligent edge computing based on machine learning for smart city10.1016/j.future.2020.08.037 ↗
81. A visualized botnet detection system based deep learning for the Internet of Things networks of smart cities10.1109/TIA.2020.2971952 ↗
82. A systematic review of a digital twin city: A new pattern of urban governance toward smart cities
83. Digital economy as a factor in the technological development of the mineral sector10.1007/s11053-019-09568-4 ↗
84. Implementation of digital manufacturing technologies: Antecedents and consequences10.1016/j.ijpe.2020.107748 ↗
85. Tambare, P., Meshram, C., Lee, C.C., Ramteke, R.J., and Imoize, A.L. (2021). Performance measurement system and quality management in data-driven Industry 4.0: A review. Sensors, 22.10.3390/s22010224 ↗
86. Terra: A smart and sensible digital twin framework for robust robot deployment in challenging environments10.1109/JIOT.2021.3068736 ↗
87. Digital twin-enabled smart industrial systems: Recent developments and future perspectives10.1080/0951192X.2021.1959710 ↗
88. Big data analysis of the internet of things in the digital twins of smart city based on deep learning10.1016/j.future.2021.10.006 ↗
89. Automatic traffic modelling for creating digital twins to facilitate autonomous vehicle development10.1080/09540091.2021.1997914 ↗
90. Liu, Z., Meng, X., Xing, Z., Shi, G., and Meng, X. (2021). Digital Twin-Based Safety Risk Coupling of Prefabricated Building Hoisting. Sensors, 21.10.3390/s21113583 ↗
91. Digital twin analysis to promote safety and security in autonomous vehicles10.1109/MCOMSTD.011.2100004 ↗
92. Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management10.1016/j.ijinfomgt.2019.102049 ↗
93. The use of digital twins in healthcare: Socio-ethical benefits and socio-ethical risks10.1186/s40504-021-00113-x ↗
94. Cognition digital twins for personalized information systems of smart cities: Proof of concept10.1061/(ASCE)ME.1943-5479.0000740 ↗
95. Digital twin: Empowering enterprises towards a system-of-systems approach10.1007/s12599-019-00624-0 ↗
96. A digital-twin visualized architecture for Flexible Manufacturing System10.1016/j.jmsy.2021.05.010 ↗
97. Pérez, L., Rodríguez-Jiménez, S., Rodríguez, N., Usamentiaga, R., and García, D.F. (2020). Digital twin and virtual reality based methodology for multi-robot manufacturing cell commissioning. Appl. Sci., 10.10.3390/app10103633 ↗
98. Consuming takeaway food: Convenience, waste and Chinese young people’s urban lifestyle10.1177/1469540519882487 ↗
99. Munawar, H.S., Qayyum, S., Ullah, F., and Sepasgozar, S. (2020). Big data and its applications in smart real estate and the disaster management life cycle: A systematic analysis. Big Data Cogn. Comput., 4.10.3390/bdcc4020004 ↗
100. Preventing COVID-19 from the perspective of industrial information integration: Evaluation and continuous improvement of information networks for sustainable epidemic prevention