Digital Twin of City: Concept Overview
Abstract
This article presents the concept of the digital twin of a city. The urban economy is a complex multi-vector system. Creating a single digital twin of such a system is now a difficult task to solve. In this article the concept of a digital twin of a city is presented. The authors propose an evolutionary approach to this problem, according to which digital twins of individual elements of the urban environment are consistently built on a single hardware and software platform. These digital twins are linked in a single cooperative system that allows one digital twin to use data produced by other digital twins. The article gives the definition and architecture of such a system. It describes the classes of models that can be used to create digital twins. Special attention is paid to neural network models and models for data analysis. The information infrastructure of the digital twin of a city, including sensory networks, data cleansing mechanisms and nebulous calculations, is considered.
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Implementation of big data in urban space applications enables monitoring of behavioral patterns and lifestyle and their interaction with population, economic development, construction and infrastructure.
“Furthermore, the implementation of big data in urban space applications enables monitoring of behavioral patterns and lifestyle and their interaction with population, economic development, construction and infrastructure [21].”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [21]
Cites
You Only Look Once: Unified, Real-Time Object Detection
Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.91 · Cited by 53,803 · see citing works
Another look at measures of forecast accuracy
Hyndman, R. J., & Koehler, A. B. (2006) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2006.03.001 · Cited by 5,757 · see citing works
Urban Digital Twins for Smart Cities and Citizens: The Case Study of Herrenberg, Germany
Dembski, F., Wössner, U., Letzgus, M., Ruddat, M., & Yamu, C. (2020) · Sustainability · doi:10.3390/su12062307 · Cited by 622 · see citing works
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Digital Twin Technology Challenges and Applications: A Comprehensive Review
Botín-Sanabria, D. M., Mihaita, A.-S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., & Lozoya-Santos, J. D. J. (2022) · Remote Sensing · doi:10.3390/rs14061335 · Cited by 878 · see citing works
Optimal Sensor Placement for Structural Health Monitoring: A Comprehensive Review
Sun, Z., Mahmoodian, M., Sidiq, A., Jayasinghe, S., Shahrivar, F., & Setunge, S. (2025) · Journal of Sensor and Actuator Networks · doi:10.3390/jsan14020022 · Cited by 53 · see citing works
- Authors
- Ivanov, S., Nikolskaya, K., Radchenko, G., Sokolinsky, L., & Zymbler, M.
- Affiliations
- South Ural State University (RU)
- Venue
- 2020 Global Smart Industry Conference (GloSIC)
- Publisher
- IEEE
- Published
- 2020-11-17
- Pages
- 178-186
- OpenAlex
- W3106864127
- Cited by
- 138
- References
- 3
- Citations by year
- 2026: 11 · 2025: 34 · 2024: 35 · 2023: 35 · 2022: 18 · 2021: 5
- FWCI
- 30.31
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Global Smart Industry Conference (GloSIC) (publishedVersion)
- Funders
- Ministry of Science and Higher Education of the Russian Federation
- Russian Foundation for Basic Research
- Topics
- Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Building and Construction › 3D Modeling in Geospatial Applications
- Keywords
- urban systems, evolutionary perspective, neural network model, data analysis model, information infrastructure, sensory networks, data cleaning
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