Skip to main content

Digital Twin Applications for Smart and Connected Cities

Abstract

A virtual representation of a physical object, system, process, or service can be defined as a Digital Twin (DT). DT technologies offer the capability of providing organizations with media to monitor the activities, relations, co-actions, and outcomes of alternative decisions in the real system via the virtual duplicate of the system. Cities are complex systems that include subsystems that should be continuously controlled and supplied with effective solutions. These are public transportation, communication, waste management, energy management, and public healthcare. A DT provides numerous solution advantages by providing various applications connected to the underlying technologies. It helps to improve the capabilities related to all these assets or services by integrating them with the management processes and improved policies in a city. Internet of Things (IoT) is an effective capability that provides the interaction between all the components in the smart city via DT technologies. This chapter explains how DT technologies are applied to smart cities in different city functions that are affected by the economic advantage, costs of implementation, and the integration of these functions with information systems capabilities. Accordingly, alternative technological methods and ideas are being examined to improve citizens’ lives by optimizing the use of limited resources.

Keywords

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Farsi, M., Daneshkhah, A., Hosseinian-Far, A., & Jahankhani, H. (2020). Digital twin technologies and smart cities. Springer.

    Google Scholar 

  2. Kaluarachchi, Y. (2022). Implementing data-driven smart city applications for future cities. Smart Cities, 5(2), 455–474.

    Article  Google Scholar 

  3. Madakam, S., Lake, V., Lake, V., Lake, V., et al. (2015). Internet of things (IoT): A literature review. Journal of Computer and Communications, 3(05), 164.

    Article  Google Scholar 

  4. Al Nuaimi, E., Al Neyadi, H., Mohamed, N., & Al-Jaroodi, J. (2015). Applications of big data to smart cities. Journal of Internet Services and Applications, 6(1), 1–15.

    Article  Google Scholar 

  5. Angelidou, M. (2017). The role of smart city characteristics in the plans of fifteen cities. Journal of Urban Technology, 24(4), 3–28.

    Article  Google Scholar 

  6. Julien, N., & Martin, E. (2021). How to characterize a digital twin: A usage-driven classification. IFAC-PapersOnLine, 54(1), 894–899.

    Article  Google Scholar 

  7. Glaessgen, E., & Stargel, D. (2012). The digital twin paradigm for future NASA and US air force vehicles. In 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA (p. 1818).

    Google Scholar 

  8. Singh, S., Weeber, M., & Birke, K.-P. (2021). Advancing digital twin implementation: A toolbox for modelling and simulation. Procedia CIRP, 99, 567–572.

    Article  Google Scholar 

  9. Hyre, A., Harris, G., Osho, J., Pantelidakis, M., Mykoniatis, K., & Liu, J. (2022). Digital twins: Representation, replication, reality, and relational (4rs). Manufacturing Letters, 31, 20–23.

    Article  Google Scholar 

  10. Ramu, S. P., Boopalan, P., Pham, Q.-V., Maddikunta, P. K. R., Huynh-The, T., Alazab, M., Nguyen, T. T., & Gadekallu, T. R. (2022). Federated learning enabled digital twins for smart cities: Concepts, recent advances, and future directions. Sustainable Cities and Society, 79, 103663.

    Article  Google Scholar 

  11. Huang, H., Yao, X. A., Krisp, J. M., & Jiang, B. (2021). Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions. Computers, Environment and Urban Systems, 90, 101712.

    Article  Google Scholar 

  12. White, G., Zink, A., Codecá, L., & Clarke, S. (2021). A digital twin smart city for citizen feedback. Cities, 110, 103064.

    Article  Google Scholar 

  13. Broo, D. G., Bravo-Haro, M., & Schooling, J. (2022). Design and implementation of a smart infrastructure digital twin. Automation in Construction, 136, 104171.

    Article  Google Scholar 

  14. Deng, T., Zhang, K., & Shen, Z.-J.M. (2021). A systematic review of a digital twin city: A new pattern of urban governance toward smart cities. Journal of Management Science and Engineering, 6(2), 125–134.

    Article  Google Scholar 

  15. Sarp, S., Kuzlu, M., Zhao, Y., Cetin, M., & Guler, O. (2021). A comparison of deep learning algorithms on image data for detecting floodwater on roadways. Computer Science and Information Systems, 00, 58–58.

    Google Scholar 

  16. Visan, M., Negrea, S. L., & Mone, F. (2022). Towards intelligent public transport systems in smart cities; collaborative decisions to be made. Procedia Computer Science, 199, 1221–1228.

    Article  Google Scholar 

  17. Utku, D. H., & Soyöz, B. (2020). A mathematical model on liquefied natural gas supply chain with uncertain demand. SN Applied Sciences, 2(9), 1–15.

    Article  Google Scholar 

  18. UTKU, D. H. (2022). An application: A multi-mode natural gas and liquefied natural gas supply chain management problem. Journal of Engineering Research.

    Google Scholar 

  19. Sarp, S., Kuzlu, M., Cetin, M., Sazara, C., & Guler, O. (2020). Detecting floodwater on roadways from image data using mask-r-CNN (pp. 1–6).

    Google Scholar 

  20. Wu, J., Wang, X., Dang, Y., & Lv, Z. (2022). Digital twins and artificial intelligence in transportation infrastructure: Classification, application, and future research directions. Computers and Electrical Engineering, 101, 107983.

    Article  Google Scholar 

  21. Calvillo, C. F., Sánchez-Miralles, A., & Villar, J. (2016). Energy management and planning in smart cities. Renewable and Sustainable Energy Reviews, 55, 273–287.

    Article  Google Scholar 

  22. Wibawa, F., Catak, F. O., Kuzlu, M., Sarp, S., & Cali, U. (2022). Homomorphic encryption and federated learning based privacy-preserving CNN training: Covid-19 detection use-case. In Proceedings of the 2022 European Interdisciplinary Cybersecurity Conference (pp. 85–90).

    Google Scholar 

  23. Sarp, S., Zhao, Y., & Kuzlu, M. (2022). Artificial intelligence-powered chronic wound management system: Towards human digital twins.

    Google Scholar 

  24. UNICEF. et al. (2019). Advantage or paradox? The challenge for children and young people of growing up urban. United Nations.

    Google Scholar 

  25. Sarp, S., Kuzlu, M., Wilson, E., & Guler, O. (2021). Wg2an: Synthetic wound image generation using generative adversarial network. The Journal of Engineering, 2021(5), 286–294.

    Article  Google Scholar 

  26. Utku, D. H., & Erol, S. (2020). The hazardous waste location and routing problem: An application in Marmara region in turkey. SN Applied Sciences, 2(2), 1–17.

    Article  Google Scholar 

  27. Kohne, T., Burkhardt, M., Theisinger, L., & Weigold, M. (2021). Technical and digital twin concept of an industrial heat transfer station for low exergy waste heat. Procedia CIRP, 104, 223–228.

    Article  Google Scholar 

  28. Ramu, S. P., Boopalan, P., Pham, Q.-V., Maddikunta, P. K. R., Huynh-The, T., Alazab, M., Nguyen, T. T., & Gadekallu, T. R. (2022). Federated learning enabled digital twins for smart cities: Concepts, recent advances, and future directions. Sustainable Cities and Society, 79, 103663.

    Article  Google Scholar 

  29. Lee, J., Cameron, I., & Hassall, M. (2019). Improving process safety: What roles for digitalization and industry 4.0? Process safety and environmental protection, 132, 325–339.

    Article  Google Scholar 

  30. Madni, A. M., Madni, C. C., & Lucero, S. D. (2019). Leveraging digital twin technology in model-based systems engineering. Systems, 7(1), 7.

    Article  Google Scholar 

  31. Rosan, C. D., & Pearsall, H. (2017). Growing a sustainable city?: The question of urban agriculture. University of Toronto Press.

    Google Scholar 

  32. Dickey, T. (2018). Smart water solutions for smart cities. Springer International Publishing (pp. 197–207). [Online]. Available: https://doi.org/10.1007/978-3-319-59381-4_12

  33. Zohrabi, N., Linkous, L., Eini, R., Adhikari, S., Keegan, B., Jones, J. C., Gooden, B., Verrelli, B. C., & Abdelwahed, S. (2021). Towards sustainable food security: An interdisciplinary approach. In 2021, IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI). (pp. 463–470). IEEE.

    Google Scholar 

  34. von Braun, J., Afsana, K., Fresco,L., Hassan, M., & Torero, M. (2021). Food systems—definition, concept and application for the un food systems summit. Science Innovation, 27.

    Google Scholar 

  35. An, W., Wu, D., Ci, S., Luo, H., Adamchuk,V., & Xu, Z. (2017). Agriculture cyber-physical systems. In Cyber-physical systems. Elsevier (pp. 399–417).

    Google Scholar 

  36. Rose, D. C., & Chilvers, J. (2018). Agriculture 4.0: Broadening responsible innovation in an era of smart farming. Frontiers in Sustainable Food Systems, 2, 87.

    Article  Google Scholar 

  37. Song, B. D., & Ko, Y. D. (2016). A vehicle routing problem of both refrigerated-and general-type vehicles for perishable food products delivery. Journal of food engineering, 169, 61–71.

    Article  Google Scholar 

  38. Woods, J., Williams, A., Hughes, J. K., Black, M., & Murphy, R. (2010). Energy and the food system. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1554), 2991–3006.

    Article  Google Scholar 

  39. Muriana, C. (2017). A focus on the state of the art of food waste/losses issue and suggestions for future researches. Waste Management, 68, 557–570.

    Article  Google Scholar 

  40. Livesley, S. J., Marchionni, V., Cheung, P. K., Daly, E., & Pataki, D. E. (2021). Water smart cities increase irrigation to provide cool refuge in a climate crisis. Earth’s Future, 9(1), e2020EF001806.

    Google Scholar 

  41. Zohrabi, N., Martin, P. J., Kuzlu, M., Linkous, L., Eini, R., Morrissett, A., Zaman, M., Tantawy, A., Gueler, O., & Al Islam, M. (2021). Opencity: An open architecture testbed for smart cities. In IEEE International Smart Cities Conference (ISC2) (pp. 1–7). IEEE.

    Google Scholar 

  42. Kuzlu, M., Kalkavan, H., Gueler, O., Zohrabi, N., Martin, P. J., & Abdelwahed, S. (2022). An end to end data collection architecture for IoT devices in smart cities. In IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) (pp. 1–5). IEEE.

    Google Scholar 

  43. Wu, Y., Zhang, K., & Zhang, Y. (2021). Digital twin networks: A survey. IEEE Internet of Things Journal, 8(18), 13 789–13 804.

    Google Scholar 

  44. Karaarslan, E., & Babiker, M. (2021). Digital twin security threats and countermeasures: An introduction. In 2021 International Conference on Information Security and Cryptology (ISCTURKEY) (pp. 7–11). IEEE

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Durdu Hakan Utku .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Utku, D.H. et al. (2023). Digital Twin Applications for Smart and Connected Cities. In: Karaarslan, E., Aydin, Ö., Cali, Ü., Challenger, M. (eds) Digital Twin Driven Intelligent Systems and Emerging Metaverse. Springer, Singapore. https://doi.org/10.1007/978-981-99-0252-1_6

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-0252-1_6

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0251-4

  • Online ISBN: 978-981-99-0252-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics