AccScience Publishing / JCAU / Online First / DOI: 10.36922/JCAU025370076
REVIEW ARTICLE

The prospects and perils of smart urban development: A review of artificial intelligence implementation in sustainable city projects

Abbas M. Hassan1,2 Lamiaa Mostafa Abdrabo1 Jeong Seok Song3 Hyowon Lee4* Talal Obaid Alshammari5
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1 Department of Architectural Engineering, College of Engineering, Dhofar University, Salalah, Dhofar, Oman
2 Department of Architecture, Faculty of Engineering, Al-Azhar University, Qena, Egypt
3 Department of Architecture, Donggang University, Gwangju, Republic of Korea
4 Department of Architecture, School of Architecture, Chonnam National University, Gwangju, Republic of Korea
5 Department of Civil Engineering, College of Engineering, Jouf University, Sakaka, Aljouf, Saudi Arabia
Journal of Chinese Architecture and Urbanism, 025370076 https://doi.org/10.36922/JCAU025370076
Received: 11 September 2025 | Revised: 14 November 2025 | Accepted: 15 December 2025 | Published online: 2 January 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Urban areas now constitute the primary habitat for most of the global population, a demographic shift that has exacerbated longstanding urban challenges. In response, cities are increasingly turning to emerging information and communication technologies and artificial intelligence (AI) as potential solutions. This study provides a critical review of the predominant urban issues and examines their interconnection with contemporary smart city initiatives worldwide. Through an analysis of international case studies from Singapore, Spain, the Netherlands, and Copenhagen, this research aims to derive valuable insights and lessons to inform the development of scenarios for future sustainable urban models. The study highlights that while AI and smart technologies hold significant promise for advancing urban sustainability, their implementation faces considerable challenges. These include critical social implications, such as the erosion of privacy, alongside economic constraints and heterogeneous regulatory landscapes across national contexts. Furthermore, the analysis identifies Dutch smart urbanism initiatives as particularly noteworthy. Among the cases examined, the Dutch approach is distinguished by its pronounced emphasis on mitigating social issues and fostering public participation in the co-creation of future urban frameworks.

Keywords
Smart cities
Artificial intelligence
Mobility
Waste management
Energy management
Virtual Singapore
Internet of Things
City-Zen project
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
References

Allam, Z., & Dhunny, Z. A. (2019). On big data, artificial intelligence and smart cities. Cities, 89:80-91. https://doi.org/10.1016/j.cities.2019.01.032

 

Alshammari, T.O., Hassan, A.M., Arab, Y., Hussein, H., Khozaei, F., Saeed, M., et al. (2022) The compactness of non-compacted Urban developments: A critical review on sustainable approaches to automobility and Urban Sprawl. Sustainability, 14(18):11121. https://doi.org/10.3390/su141811121

 

Alverti, M.N., Themistocleous, K., Kyriakidis, P.C., & Hadjimitsis, D.G. (2018). A human-centric approach on the analysis of the smart city concept: The case study of Limassol city (Cyprus). Advances in Geosciences, 45:305-320. https://doi.org/10.5194/adgeo-45-305-2018

 

Alzahrani, A., Kostkova, P., Alshammari, H., Habibullah, S., & Alzahrani, A. (2025). Intelligent integration of AI and IoT for advancing ecological health, medical services, and community prosperity. Alexandria Engineering Journal, 127:522-540. https://doi.org/10.1016/j.aej.2025.05.046

 

Austin, L., & Lie, D. (2021). Data trusts and the governance of smart environments: Lessons from the failure of Sidewalk Labs’ Urban data trust. Surveillance and Society, 19(2):255261. https://doi.org/10.24908/ss.v19i2.14409

 

Awad, A.I., Furnell, S., Hassan, A.M., & Tryfonas, T. (2019). Special issue on security of IoT-enabled infrastructures in smart cities. Ad Hoc Networks, 92:101850. https://doi.org/10.1016/j.adhoc.2019.02.007

 

Bakıcı, T., Almirall, E., & Wareham, J. (2013). A smart city initiative: The case of Barcelona. Journal of the Knowledge Economy, 4(2):135-148. https://doi.org/10.1007/s13132-012-0084-9

 

Batty, M. (2018). Inventing Future Cities. United States: MIT Press. https://doi.org/10.7551/mitpress/11923.001.0001

 

Bhat, G.K., Karanth, A., Dashora, L., & Rajasekar, U. (2013). Addressing flooding in the city of Surat beyond its boundaries. Environment and Urbanization, 25(2):429-441. https://doi.org/10.1177/0956247813495002

 

Bibri, S.E., & Krogstie, J. (2017). Smart sustainable cities of the future: An extensive interdisciplinary literature review. Sustainable Cities and Society, 31:183-212. https://doi.org/10.1016/j.scs.2017.02.016

 

Bibri, S.E., & Krogstie, J. (2020). The emerging data-driven Smart City and its innovative applied solutions for sustainability: The cases of London and Barcelona. Energy Informatics, 3(1):5. https://doi.org/10.1186/s42162-020-00108-6

 

Bibri, S.E., Alexandre, A., Sharifi, A., & Krogstie, J. (2023). Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies: An integrated literature review. Energy Informatics, 6(1):9. https://doi.org/10.1186/s42162-023-00259-2

 

Biggs, E., Pellegrini, L., Locatelli, M., Accardo, D., Tagliabue, L.C., Avena, M. et al. (2022). Toward cognitive digital twins using a BIM-GIS asset management system for a diffused university. Frontiers in Built Environment, 8:959475 https://doi.org/10.3389/fbuil.2022.959475

 

C40 Cities. (2016). C40 Good Practice Guides: Copenhagen - Cloudburst Management Plan. C40. Available from: https://www.c40.org/case-studies/c40-good-practice-guides-copenhagen-cloudburst-management-plan [Last accessed on 2025 Dec 28].

 

Cavoukian, A. (2011). Privacy by Design: The 7 Foundational Principles. Information and Privacy Commissioner of Ontario, Canada. Avaialble from: https://iapp.org/media/ pdf/resource_center/pbd_implement_7found_principles. pdf [Last accessed on 2025 Dec 28].

 

Chi, Y.L., & Mak, H.W.L. (2021). From comparative and statistical assessments of liveability and health conditions of districts in Hong Kong towards future City Development. Sustainability, 13(16):8781. https://doi.org/10.3390/su13168781

 

ClimateFit HEU. (2024). Cloudburst Management Plan (Copenhagen). Available from: https://climatefit-heu.eu/wp-content/uploads/2024/07/03_cloudburst-management-plan.pdf [Last accessed on 2025 Dec 06]

 

Cominola, A., Giuliani, M., Piga, D., Castelletti, A., & Rizzoli, A.E. (2015). Benefits and challenges of using smart meters for advancing residential water demand modeling and management: A review. Environmental Modelling and Software, 72:198-214. https://doi.org/10.1016/j.envsoft.2015.07.012

 

Darby, S. (2010). Smart metering: What potential for householder engagement? Building Research and Information, 38(5):442-457. https://doi.org/10.1080/09613218.2010.492660

 

Dembski, F., Wössner, U., Letzgus, M., Ruddat, M., & Yamu, C. (2020). Urban digital twins for smart cities and citizens: The case study of Herrenberg, Germany. Sustainability, 12(6):2307. https://doi.org/10.3390/su12062307

 

Eckhardt, J., Lauhkonen, A., & Aapaoja, A. (2017). The MaaS Checklist: A Framework for Evaluating Mobility-as-a-Service. 12th European Congress on Intelligent Transportation Systems, Strasbourg. [TTL Working Paper]; 2017.

 

Egger, S.A. (2006). Determining a sustainable city model. Environmental Modelling and Software, 21(9):1235-1246. https://doi.org/10.1016/j.envsoft.2005.04.012

 

Elechi, P., Orike, S., & Ogonda Igbudu, A. (2021). Development of an improved solid waste collection system using smart sensors. World Journal of Electrical and Electronic Engineering, 1(1):51-65. https://doi.org/10.31586/wjeee.2021.151

 

Evans, R., & Gao, J. (2016). DeepMind AI Reduces Google Data Centre Cooling Bill by 40 %. Google DeepMind Blog. Available from: https://deepmind.google/blog/deepmind-ai-reduces/ google-data-centre-cooling-bill-40/ [Last accessed on 2025 Dec 09].

 

Fainstein, S.S. (2010). The Just City. New York: Cornell University Press.

 

Fan, H., Tariq, S., & Zayed, T. (2022). Acoustic leak detection approaches for water pipelines. Automation in Construction, 138:104226. https://doi.org/10.1016/j.autcon.2022.104226

 

Fang, B., Yu, J., Chen, Z., Yap, P.S., Osman, AI., Farghali, M., et al. (2023). Artificial intelligence for waste management in smart cities: A review. Environmental Chemistry Letters, 21(8):1-31. https://doi.org/10.1007/s10311-023-01604-3

 

Farhan, S.L., Hasan, S.A., Rahim, L.A.L., Ebraheem, A.K., Al-Hussaini, Z.I., Ebraheem, M.A., et al. (2025). Balancing heritage preservation and sustainable development in historic cities: A case study of Old Najaf in the context of global best practices. International Journal of Sustainable Development and Planning, 20(3):1041-1051. https://doi.org/10.18280/ijsdp.200311

 

Flynn, A., & Valverde, M. (2019). Where the sidewalk ends: The governance of waterfront toronto’s sidewalk labs deal. Windsor Yearbook of Access to Justice, Recueil annuel de Windsor d’Accès à la Justice, 36:263-283. https://doi.org/10.22329/wyaj.v36i0.6425

 

Gacu, J.G., Monjardin, C.E.F., Mangulabnan, R.G.T., Pugat, G.C.E., & Solmerin, J.G. (2025). Artificial intelligence (AI) in surface water management: A comprehensive review of methods, applications, and challenges. Water, 17(11):1707. https://doi.org/10.3390/w17111707

 

Gao, Z., Wang, S., & Gu, J. (2020). Public participation in smart-city governance: A qualitative content analysis of public comments in Urban China. Sustainability, 12(20):8605. https://doi.org/10.3390/su12208605

 

Gaur, A., Scotney, B., Parr, G., & McClean, S. (2019). Smart city architecture and its applications based on IoT. In: Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems.

 

Georgia Tech Center for Advanced Communications Policy. (2021). Bridges of the BeltLine Research Brief. Georgia Tech. Available from: https://cacp.gatech.edu/sites/default/ files/2021/02/Bridges%20of%20the%20Beltline%20 Research%20Brief.pdf [Last accessed on 2025 Dec 08].

 

Giest, S., McBride, K., Nikiforova, A., & Sikder, S.K. (2025). Digital & data-driven transformations in governance: A landscape review. Data and Policy, 7:e21. https://doi.org/10.1017/dap.2024.47

 

Green, B. (2019). The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future. United States: The MIT Press. https://doi.org/10.7551/mitpress/11555.001.0001

 

Gu, Q., Sing, M.C.P., Jefferies, M., & Kanjanabootra, S. (2025). Bridging the gap between smart cities and sustainability: Current practices and future trends. Cities, 159:105799. https://doi.org/10.1016/j.cities.2025.105799

 

Hajer, M., & Dassen, T. (2019). Smart about Cities: Visualising the Challenge for 21st Century Urbanism. Netherlands: NAI010 Publishers.

 

Hassan, A.M., & Awad A.I. (2018). Urban Transition in the Era of the internet of things: Social implications and privacy challenges. IEEE Access, 6:36428-36440. https://doi.org/10.1109/ACCESS.2018.2838339

 

Hassan, A.M., & Lee, H. (2015a). The paradox of the sustainable city: Definitions and examples. Environment, Development and Sustainability, 17:1267-1285. https://doi.org/10.1007/s10668-014-9604-z

 

Hassan, A.M., & Lee, H. (2015b). Toward the sustainable development of urban areas: An overview of global trends in trials and policies. Land Use Policy, 48:199-212 https://doi.org/10.1016/j.landusepol.2015.04.029

 

I amsterdam. (2023). How Smart Grids are Enabling Amsterdam’s Energy Transition. Available from: https://www.iamsterdam.com/en/business/how/smart/grids/are/enabling/ amsterdams/energy-transition [Last accessed on 2025 Dec 10].

 

Jain, Y., & Pandey, K. (2025). Transforming urban mobility: A systematic review of AI-based traffic optimization techniques. Archives of Computational Methods in Engineering, 32:5381-5417. https://doi.org/10.1007/s11831-025-10297-6

 

Jasim, J.A., Mutlag, A.H., Othman, N.A., Shareef, H., & Hammed, N.H. (2024). “Innovative Applications of AI and IoT in Smart Urban Infrastructure and Housing Projects”. In: 2024 International Conference on Emerging Research in Computational Science (ICERCS), Coimbatore, India, 2024. p. 1-6. https://doi.org/10.1109/ICERCS63125.2024.10894956

 

Jensen, J. S., Cashmore, M., & Späth, P. (Eds.). (2019). The politics of urban sustainability transitions: Knowledge, power and governance. NY: Routledge.

 

Joh, E.E. (2019). Policing the smart city. International Journal of Law in Context, 15(2):177-182. https://doi.org/10.1017/S1744552319000107

 

Ketzler, B., Naserentin, V., Latino, F., Zangelidis, C., Thuvander, L., & Logg, A. (2020). Digital twins for cities: A State of the art review. Built Environment, 46(4):547-573. https://doi.org/10.2148/benv.46.4.547

 

Khamis, A. (2021). Toward a people-centric smart city. In: Smart Mobility. Berkeley, CA: Apress. https://doi.org/10.1007/978-1-4842-7101-8_1

 

Kitchin, R. (2014). The real-time city? Big data and smart urbanism. GeoJournal, 79(1):1-14. https://doi.org/10.1007/s10708-013-9516-8

 

Kollar, J.M. (2022). In: Ahn, C., Ignaccolo, C., & Salazar- Miranda, A., editors. Failure to Innovate: Urban Technocracy and the Making and Unmaking of Sidewalk Labs’ Smart City’, Projections. Ch. 16. Measuring the City: The Power of Urban Metrics (MIT Press). Available from: https://projections. pubpub.org/pub/2bwwek3k [Last accessed on 2025 Dec 28].

 

Komarudin, M., Sulistiyanti, S.R., Suharso, M.I., Septama, H.D., Yulianti, T., Sophian, A., et al. (2025). Advancing precision in air quality forecasting through machine learning integration. IAES International Journal of Artificial Intelligence (IJ-AI), 14(3):2113-2122. https://doi.org/10.11591/ijai.v14.i3.pp2113-2122

 

Lakhouit, A. (2025). Revolutionizing Urban solid waste management with AI and IoT: A review of smart solutions for waste collection, sorting, and recycling. Results in Engineering, 25:104018. https://doi.org/10.1016/j.rineng.2025.104018

 

Lehmann, S. (2010). The Principles of Green Urbanism: Transforming the City for Sustainability. Earthscan: London.

 

Leong, Q.Y., Lee, V. V., Ng, W. Y., Vijayakumar, S., Lau, N. Y., Mauritzon, I., et al. (2024). Older adults’ perspectives and experiences with digital health in Singapore: Qualitative study. JMIR Human Factors, 11:e58641. https://doi.org/10.2196/58641

 

Lund, N.S.V., Borup, M., Madsen, H., Mark, O., Arnbjerg- Nielsen, K., & Mikkelsen, P.S. (2019). Integrated stormwater inflow control for sewers and green structures in Urban landscapes. Nature Sustainability, 2:1003-1010. https://doi.org/10.1038/s41893-019-0392-1

 

Mak, H.W.L. (2025). Application of Satellite Informatics in Mitigating Climatic Challenges within the Atmosphere: Selected Case Studies of Asian Cities. Available from: https://apctt.org/sites/default/files/attachment/2025/05/06_application%20of%20satellite%20informatics.pdf [Last accessed on 2025 Dec 09].

 

Mak, H.W.L., & Lam, Y.F. (2021). Comparative assessments and insights of data openness of 50 smart cities in air quality aspects. Sustainable Cities and Society, 69:102868. https://doi.org/10.1016/j.scs.2021.102868

 

Martin, J., Cantero, D., González, M., Cabrera, A., Larrañaga, M., Maltezos, E., et al. (2022). Embedded vision intelligence for the safety of smart cities. Journal of Imaging, 8(12):326. https://doi.org/10.3390/jimaging8120326

 

Mazzetto, S. (2024). A review of Urban digital twins integration, challenges, and future directions in smart city development. Sustainability, 16(19):8337. https://doi.org/10.3390/su16198337

 

McCrory, L. (2024). A feminist framework for Urban AI governance: Addressing challenges for public-private partnerships. Data and Policy, 6:e79. https://doi.org/10.1017/dap.2024.69

 

Meerow, S., Newell, J.P., & Stults, M. (2016). Defining Urban resilience: A review. Landscape and Urban Planning, 147:38-49. https://doi.org/10.1016/j.landurbplan.2015.11.011

 

Mehryar, S., Yazdanpanah, V., & Tong, J. (2024). AI and climate  resilience governance. iScience, 27(6):109812. https://doi.org/10.1016/j.isci.2024.109812

 

Meijer, A., & Thaens, M. (2020). The dark side of public innovation. Public Performance and Management Review, 44(1):136-154. https://doi.org/10.1080/15309576.2020.1782954

 

Mengelkamp, E., Gärtner, J., Rock, K., Kessler, S., Orsini, L., & Weinhardt, C. (2018). Designing microgrid energy markets: A case study: The brooklyn microgrid. Applied Energy, 210:870-880. https://doi.org/10.1016/j.apenergy.2017.06.054

 

Mersal, A.M. (2016). Sustainable Urban futures: Environmental planning for sustainable Urban development. Procedia Environmental Sciences, 34:49-61. https://doi.org/10.1016/j.proenv.2016.04.005

 

Meyers, D., Zheng, Q., Duarte, F., Ratti, C., Hemond, HF., Van Der Blom, M., et al. (2022). Initial deployment of a mobile sensing system for water quality in Urban canals. Water, 14(18):2834. https://doi.org/10.3390/w14182834

 

Miller, C., Abdelrahman, M., Chong, A., Biljecki, F., Quintana, M., Frei, M., et al. (2021). The Internet-of- Buildings (IoB) - Digital twin convergence of wearable and IoT data with GIS/BIM. Journal of Physics Conference Series, 2042(1):012041. https://doi.org/10.1088/1742-6596/2042/1/012041

 

Mohan, V., & Hellwich, O. (2023). Cross-sensor vision system for maritime object detection. Frontiers in Marine Science, 10:1112955. https://doi.org/10.3389/fmars.2023.1112955

 

Mohanty, A. (2025). Empowering smart city through smart grid communication and measurement technology. International Journal of Low-Carbon Technologies, 20(3), 404-420. https://doi.org/10.1093/ijlct/ctae224

 

Neto, A.B.P.S., Simões, C.L., & Simões, R. (2024). Optimization of municipal solid waste collection system: Systematic review with bibliometric literature analysis. Journal of Material Cycles and Waste Management, 26(5):1906-1917. https://doi.org/10.1007/s10163-024-01966-y

 

OGC Urban Digital Twin Domain Working Group. (2024). Urban Digital Twins: Integrating Infrastructure, Natural Environment and People (OGC Doc No. 24-025). Open Geospatial Consortium. Available from: https://docs.ogc. org/dp/24-025.html [Last accessed on 2025 Dec 28].

 

Park, S., Cho, K., Kim, S., Yoon, G., Choi, M.I., Park, S., & Park, S. (2021). Distributed energy IoT-based real-time virtual energy prosumer business model for distributed power resources. Sensors (Basel), 21(13):4533. https://doi.org/10.3390/s21134533

 

Pasetti, M., Rinaldi, S., & Manerba, D. (2018). A virtual power plant architecture for the demand-side management of smart prosumers. Applied Sciences, 8(3):432. https://doi.org/10.3390/app8030432

 

Peldon, D., Banihashemi, S., LeNguyen, K., & Derrible, S. (2024). Navigating Urban complexity: The transformative role of digital twins in smart city development. Sustainable Cities and Society, 111:105583. https://doi.org/10.1016/j.scs.2024.105583

 

Prata, J., Simões, C.L., & Simoes, R. (2025). Improvements to municipal solid waste collection systems using real-time monitoring. Sustainability, 17(4):1405. https://doi.org/10.3390/su17041405

 

Sacoto-Cabrera, E.J., Perez-Torres, A., Tello-Oquendo, L., & Cerrada, M. (2025). IoT, AI, and digital twins in smart cities: A systematic review for a thematic mapping and research Agenda. Smart Cities, 8(5):175. https://doi.org/10.3390/smartcities8050175

 

Sadowski, J. (2020). Too Smart: How Digital Capitalism is Extracting Data, Controlling our Lives, and Taking Over the World. United States: The MIT Press. https://doi.org/10.7551/mitpress/12240.001.0001

 

Salih, S., Abdelmaboud, A., Husain, O., Motwakel, A., Elshafie, H., Sharif, M., et al. (2025). IoT in Urban development: Insight into smart city applications, case studies, challenges, and future prospects. PeerJ Computer Science, 11:e2816. https://doi.org/10.7717/peerj-cs.2816

 

Sharifi, A., & Yamagata, Y. (2018). Resilience-oriented urban planning. In: Yamagata, Y., & Sharifi, A., editors. Resilience- Oriented Urban Planning: Theoretical and Empirical Insights. Lecture Notes in Energy, 65. Berlin: Springer, p. 3-27. https://doi.org/10.1007/978-3-319-75798-8_1

 

Sheffield, J., Wood, E.F., Pan, M., Beck, H., Coccia, G., Serrat- Capdevila, A., et al. (2018). Satellite remote sensing for water resources management: Potential for supporting sustainable development in data-poor regions. Water Resources Research, 54(12):9724-9758. https://doi.org/10.1029/2017WR022437

 

Shimizu, Y., Osaki, S., Hashimoto, T., & Karasawa, K. (2022). Social acceptance of smart city projects: Focus on the sidewalk toronto case. Frontiers Environmental Science, 10:898922. https://doi.org/10.3389/fenvs.2022.898922

 

Shirowzhan, S., Tan, W., & Sepasgozar, S.M.E. (2020). Digital twin and cyberGIS for improving connectivity and measuring the impact of infrastructure construction planning in smart cities. ISPRS International Journal of Geo-Information, 9(4):240. https://doi.org/10.3390/ijgi9040240

 

Son, T.H., Weedon, Z., Yigitcanlar, T., Sanchez, T.W, Juan, M., Mehmood, R, et al. (2023). Algorithmic urban planning for smart and sustainable development: Systematic review of the literature. Sustainable Cities and Society, 94:104562. https://doi.org/10.1016/j.scs.2023.104562

 

Townsend, A.M. (2013). Smart cities: Big data, civic hackers, and the quest for a new utopia. Stanford Social Innovation Review. California: W. W. Norton & Company. https://doi.org/10.48558/BXTE-BQ78

 

UN-Habitat. (2003). The Challenge of Slums: Global Report on Human Settlements 2003. London and Sterling, VA: Earthscan Publications.

 

Vakhnin, A., Ryzhikov, I., Brester, C., Niska, H., & Kolehmainen, M. (2024). Weather-based prediction of power consumption in district heating network: Case study in Finland. Energies, 17(12):2840. https://doi.org/10.3390/en17122840

 

Van Zoonen, L. (2022). Privacy concerns in smart cities. Government Information Quarterly, 39(1):101610. https://doi.org/10.1016/j.giq.2016.06.004

 

Wani, A.K., Rahayu, F., Ben Amor, I., Quadir, M., Murianingrum, M., Parnidi, P., et al. (2024). Environmental resilience through artificial intelligence: Innovations in monitoring and management. Environmental Science and Pollution Research International, 31(12):18379-18395. https://doi.org/10.1007/s11356-024-32404-z

 

Wei, Z., Tien, P.W., Calautit, J., Darkwa, J., Worall, M., & Boukhanouf, R. (2024). Investigation of a model predictive control (MPC) strategy for seasonal thermochemical energy storage systems in district heating networks. Applied Energy, 376(Part A):124164. https://doi.org/10.1016/j.apenergy.2024.124164

 

WGIC Council. (2024). Digital Synergy Project, Helsinki, Finland. Available from: https://wgicouncil.org/2024/02/26 [Last accessed on 2025 Dec 28].

 

White, G., Zink, A., Codecá, L., & Clarke, S. (2021). A digital twin smart city for citizen feedback. Cities, 110:103064. https://doi.org/10.1016/j.cities.2020.103064

 

Winfield, A.F., & Jirotka, M. (2018). Ethical governance is essential to building trust in robotics and artificial intelligence systems. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2133):20180085 https://doi.org/10.1098/rsta.2018.0085

 

Wray, S. (2021). Why the City of Amsterdam Developed its Own Crowd Monitoring Technology. ITU Hub. Available from: https://www.itu.int/hub/2021/10/why-the-city-of-amsterdam-developed-its-own-crowd-monitoring-technology [Last accessed on 2025 Dec 28].

 

Xu, T., Tian, Y., Cai, X., Wu, C, & Mian, Z. (2025). Air quality forecasting and rating based on machine learning algorithm and cumulative logit model: An empirical study for Lanzhou city of China. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-024-05792-y

 

Yigitcanlar, T., Desouza, K.C., Butler, L., & Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. Energies, 13(6):1473. https://doi.org/10.3390/en13061473

 

Yigitcanlar, T., Kamruzzaman, M., Foth, M., Sabatini‐Marques, J., Da Costa, E., & Ioppolo, G. (2019). Can cities become smart without being sustainable? A systematic review of the literature. Sustainable Cities and Society, 45:348-365. https://doi.org/10.1016/j.scs.2018.11.033

 

Yu, P., Lang, H., Galang, J.I., & Xu, Y. (2023). The role of digital twin in accelerating the digital transformation of smart cities: Case studies in China. In: Yu, P., Hu, X., Prakash, A, Misuko, N., & Haiyue, G., editorss. Opportunities and Challenges of Industrial IoT in 5G and 6G Networks. United States: IGI Global, p. 155-177. https://doi.org/10.4018/978-1-7998-9266-3.ch008

 

Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for smart cities. IEEE Internet of Things Journal, 1(1):22-32. https://doi.org/$10.1109/JIOT.2014.2306328$

 

Zhang, X. (2024). Smart grid with energy digitalization. In: Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems. Netherlands: Elsevier, p. 115-132. https://doi.org/10.1016/B978-0-443-13177-6.00002-3

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Journal of Chinese Architecture and Urbanism, Electronic ISSN: 2717-5626 Published by AccScience Publishing