Yang, L., Hassan, A., Arab, Y. (2025). Community-centric AI applications in Urban renewal. , 18(4), 397-402. doi: 10.30772/qjes.2025.155912.1454
Li Yang; Ahmad S. Hassan; Yasser Arab. "Community-centric AI applications in Urban renewal". , 18, 4, 2025, 397-402. doi: 10.30772/qjes.2025.155912.1454
Yang, L., Hassan, A., Arab, Y. (2025). 'Community-centric AI applications in Urban renewal', , 18(4), pp. 397-402. doi: 10.30772/qjes.2025.155912.1454
Yang, L., Hassan, A., Arab, Y. Community-centric AI applications in Urban renewal. , 2025; 18(4): 397-402. doi: 10.30772/qjes.2025.155912.1454

Community-centric AI applications in Urban renewal

Al-Qadisiyah Journal for Engineering Sciences
Volume 18, Issue 4, December 2025, Pages 397-402    PDF (6.51 M)
Document Type: Review Paper
DOI: 10.30772/qjes.2025.155912.1454
Authors
Li Yang1; Ahmad S. Hassan* 1; Yasser Arab2
1School of Building, Housing and Planning, Universiti Sains Malaysia.
2Department of Architectural Engineering, College of Engineering, Dhofar University, Sultanate of Oman.
Abstract
This study explores the transformative potential of Artificial Intelligence (AI) in enhancing community engagement within urban regeneration projects. AI’s capacity to process vast datasets, analyze trends, and predict outcomes is revolutionizing urban planning by fostering more inclusive, adaptive, and responsive urban ecosystems. Through a bibliometric literature review, we examined existing research on AI’s role in democratizing decision-making by aggregating, analyzing, and interpreting residents’ opinions and feedback. The findings demonstrate that AI effectively addresses critical urban challenges, including traffic congestion, environmental degradation, resource allocation, and public safety, thereby enabling smarter, data-driven solutions. Moreover, AI’s ability to identify community needs ensures greater resident participation and more equitable urban development. However, significant challenges remain, particularly concerning data privacy, algorithm transparency, and ethical implications. Addressing these issues requires robust policy frameworks, adaptive governance models, and clear regulatory measures to mitigate risks and promote fairness. In conclusion, while challenges exist, AI holds immense potential to contribute to the development of smarter, more resilient, sustainable, and inclusive urban environments, where community voices are prioritized and integrated effectively.
Keywords
Artificial intelligence; Community participation; Urban management; Data science; Smart Cities
References
  • REFERENCES
  • A. Ajuriaguerra and M. Abdiu, Artificial Intelligence in European Urban Governance. IGI Global scientific publishing, 2022. [Online]. Available: http://doi.org/10.4018/978-1-7998-9609-8.ch006
  • Yigitcanlar and F. Cugurullo, “The sustainability of artificial intelligence: An urbanistic viewpoint from the lens of smart and sustainable cities.” Sustainability., vol. 12, no. 20, p. 8548., 2020. [Online]. Available: https://doi.org/10.3390/su12208548
  • Allam and Z. A. Dhunny, “On big data, artificial intelligence and smart cities,” Cities, vol. 89, pp. 80–91, 2019. [Online]. Available: https://doi.org/10.1016/j.cities.2019.01.032
  • Chen, L. Zhao, Q. Kang, and F. Di, “Systematizing heterogeneous expert knowledge, scenarios and goals via a goal-reasoning artificial intelligence agent for democratic urban land use planning.” Cities., vol. 101, p. 102703, 2020. [Online]. Available: https://doi.org/10.1016/j.cities.2020.102703
  • Jiang, “Urban planning reform trend based on artificial intelligence,” Journal of Physics: Conference Series, vol. 1533, no. 3, p. 032020, apr 2020. [Online]. Available: https://dx.doi.org/10.1088/1742-6596/1533/3/032020
  • W. Sanchez, H. Shumway, T. Gordner, and T. Lim, “The prospects of artificial intelligence in urban planning.” International Journal of Urban Sciences, vol. 27, no. 2, 2022. [Online]. Available: https://doi.org/10.1080/12265934.2022.2102538
  • Marinakis, T. Koutsellis, A. Nikas, and H. Doukas, “Ai and data democratisation for intelligent energy management. energies,”.Qualitative Research, vol. 14, no. 14, p. 4341, 2021. [Online]. Available: https://doi.org/10.3390/en14144341
  • J. Duan, Y. and Y. K. Dwivedi, “Artificial intelligence for decision making in the era of big data - evolution, challenges and research agenda.” International Journal of Information Management, vol. 48, no. c, pp. 63–71., 2019. [Online]. Available: https://doi.org/10.1016/j.ijinfomgt.2019.01.021
  • Varshney, R. A. Khan, U. Khan, and R. Verma, “Approaches of artificial intelligence and machine learning in smart cities: Critical review,” IOP Conference Series: Materials Science and Engineerin, no. 1, p. p. 012019, 2021. [Online]. Available: https://doi.org/10.1088/1757-899x/1022/1/012019
  • Quan, J. Park, A. Economou, and S. Lee, “Artificial intelligence-aided design: Smart design for sustainable city development,” Environment and Planning B and Design. Urban Studies., vol. 46„ no. 8, pp. 1581–1599., 2019. [Online]. Available: http://doi.org/10.1177/2399808319867946
  • Wolniak and K. Stecuła, “Artificial intelligence in smart cities—applications, barriers, and future directions: A review,” Smart Cities, vol. 7, no. 3, pp. 1346–1389, 2024. [Online]. Available: https://www.mdpi.com/2624-6511/7/3/57
  • Yigitcanlar, N. Kankanamge, M. Regona, A. Ruiz Maldonado, B. Rowan, A. J. Ryu, K. Desouza, J. Corchado, R. Mehmood, and R. Li, “Artificial intelligence technologies and related urban planning and development concepts: How are they perceived and utilized in australia?” Journal of Open Innovation: Technology, Market, and Complexity., vol. 6, no. 4, p. 187, 2020. [Online]. Available: https://doi.org/10.3390/joitmc6040187
  • Do Alfuqhar and M. Aysu, “Sustainable urban renewal of the old city of mosul.” Al-Rafidain Engineering Journal, vol. 27, no. 2, p. 21–27, 2022. [Online]. Available: http://doi.org/10.33899/rengj.2022.132545.1147
  • Wagner and W. D. de Vries, “Comparative review of methods supporting decision-making in urban development and land management,” Land., vol. 8, no. 8, p. 123, 2019. [Online]. Available: https://doi.org/10.3390/land8080123
  • Moumen, J. Abouchabaka, and N. Rafalia, “Enhancing urban mobility: integration of iot road traffic data and artificial intelligence in smart city environment,” Indonesian Journal of Electrical Engineering and Computer Science., vol. 32, no. 2, pp. 985–993, 2023. [Online]. Available: http://doi.org/10.11591/ijeecs.v32.i2.pp985-993
  • Xiang, Q. Li, S. Khan, and O. Khalaf, “Urban water resource management for sustainable environment planning using artificial intelligence techniques.” Environmental Impact Assessment Review., vol. 86„ p. 106515, 2021. [Online]. Available: http://doi.org/10.1016/j.eiar.2020.106515
  • Peng, K. Lu, Y. Liu, and W. Zhai, “The pathway of urban planning ai: From planning support to plan-making.” Journal of Planning Education and Research, vol. 44, no. 4, 2023. [Online]. Available: https://doi.org/10.1177/0739456X231180568
  • Wang, C.-T. Lu, X. Ye, T. Yigitcanlar, and Y. Fu, “Generative ai meets future cities: Towards an era of autonomous urban intelligence,” ArXiv,, 2023. [Online]. Available: https://doi.org/10.48550/arXiv.2304.03892
  • Qian, L. Mao, X. Liang, Y. Ding, J. Gao, X. Wei, and J. Li, “Ai agent as urban planner: Steering stakeholder dynamics in urban planning via consensus-based multi-agent reinforcement learning,” ParXiv preprint arXiv:2310.16772, no. 2, pp. 383–392, 2023. [Online]. Available: https://doi.org/10.48550/arXiv.2310.16772
  • Kramers, M. H¨ojer, N. L¨ovehagen, and J. Wangel, “Smart sustainable cities – exploring ict solutions for reduced energy use in cities,” Environmental Modelling Software, vol. 56, pp. 52–62, 2014, thematic issue on Modelling and evaluating the sustainability of smart solutions. [Online]. Available: https://doi.org/10.1016/j.envsoft.2013.12.019
  • Cugurullo, “Urban artificial intelligence: From automation to autonomy in the smart city.” JFrontiers in Sustainable Cities., vol. 2, no. 38, 2020. [Online]. Available: https://doi.org/10.3389/frsc.2020.00038
  • Jiang, Y. Xiao, and H. Cao, “Co-creating for locality and sustainability: Design-driven community regeneration strategy in shanghai’s old residential context.” Sustainability., vol. 12, no. 7, p. 2997, 2020. [Online]. Available: https://doi.org/10.3390/su12072997
  • Zhang, K. Yue, and C. Fang, “A game-theoretic framework for ai governance,” ArXiv., vol. 8, 2023. [Online]. Available: https://doi.org/10.48550/arXiv.2305.14865
  • F. Bari, I. Ahmed, R. Ahamed, T. A. Zihan, S. Sharmin, A. H. Pranto, and M. R. Islam, “Potential use of artificial intelligence (ai) in disaster risk and emergency health management: A critical appraisal on environmental health.” Environmental Health Insights., vol. 17, 2023. [Online]. Available: https://doi.org/10.1177/11786302231217808
  • Ahmad, M. Maabreh, K. K. Ghaly, M., J. Qadir, and A. Al-Fuqaha, “Developing future human-centered smart cities: Critical analysis of smart city security, data management, and ethical challenges.” Computer Science Review, vol. 43, no. 1, 2022. [Online]. Available: https://doi.org/10.1016/j.cosrev.2021.100452
  • Song, “Research on urban monitoring network management platform based on ai data stream processing.” Frontiers in Computing and Intelligent Systems, vol. 4, no. 3, pp. 121–124, 2023. [Online]. Available: http://doi.org/10.54097/fcis.v4i3.11239
  • G. Baek and H.-A. Kwon, “Participatory planning through flexible approach: Public community facilities in seoul’s urban regeneration project.” Sustainability., vol. 12, no. 24, p. 10435, 2020. [Online]. Available: https://doi.org/10.3390/su122410435
  • Savini, “The endowment of community participation: Institutional settings in two urban regeneration projects,” International Journal of Urban and Regional Research., vol. 35, no. 5, pp. 949–968, 2010. [Online]. Available: https://doi.org/10.1111/j.1468-2427.2010.00997.x
  • Maginn, “Towards more effective community participation in urban\ regeneration: the potential of collaborative planning and applied ethnography,” .Qualitative Research, vol. 7, no. 1, pp. 25–43, 2007. [Online]. Available: http://doi.org/10.1177/1468794106068020
  • Meniku, “Promoting community participation in peri-urban infrastructures.” .J Archit Des, vol. 10025., no. 2, pp. 383–392, 2016. [Online]. Available: http://doi.org/10.3889/seejad.2016.10025
  • A. Nematollahi, S. Shahbazi, and N. Nabian, “Computer vision and audition in urban analysis using the remorph framework.” Springer, no. 2, pp. 13–39, 2019. [Online]. Available: http://doi.org/10.1007/978-981-13-3543-3 2
  • Yigitcanlar, K. Desouza, L. Butler, and F. Roozkhosh, “Contributions and risks of artificial intelligence (ai) in building smarter cities: Insights from a systematic review of the literature.” Energies., vol. 13, no. 6, p. 1473, 2020. [Online]. Available: https://doi.org/10.3390/en13061473
  • Pollock and J. Sharp, “Real participation or the tyranny of participatory practice? public art and community involvement in the regeneration of the raploch, scotland,” Urban Studies., vol. 49, no. 14, pp. 3063–3079, 2012. [Online]. Available: http://doi.org/10.1177/0042098012439112
  • K. Abid, N. Sulaiman, N. Chan, S., M. U., Abid, H. Han, A. Ariza-Montes, and A. Vega-Mu˜noz, “Toward an integrated disaster management approach: How artificial intelligence can boost disaster management,” Sustainability., vol. 13, no. 22, p. 2560, November 2021. [Online]. Available: https://doi.org/10.3390/su132212560
  • Ferilli, P. Sacco, and G. T. Blessi, “Beyond the rhetoric of participation: New challenges and prospects for inclusive urban regeneration. city,” City, Culture and Society 7 (2016) 95e100, vol. 7, pp. 195–100, 2016. [Online]. Available: http://dx.doi.org/10.1016/j.ccs.2015.09.001
  • Pontrandolfi and F. Scorza, “Sustainable urban regeneration policy making: inclusive participation practice.” International Conference on Computational Science and Its Applications- . July 4-7, Proceedings, Part III 16, vol. 9788, no. 2, pp. 552–560, 2016. [Online]. Available: http://doi.org/10.1007/978-3-319-42111-7 44
  • Cath, “Governing artificial intelligence: ethical, legal and technical opportunities and challenges.” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences,, vol. 376, p. 2133, octo 2018. [Online]. Available: https://doi.org/10.1098/rsta.2018.0080
  • Coeckelbergh, “Artificial intelligence: Some ethical issues and regulatory challenges.” Technology and regulation, vol. 1, no. 2019, pp. 31–34, 2019. [Online]. Available: https://doi.org/10.26116/techreg.2019.003
  • Agarwal and M. J. Nene, “A five-layer framework for ai governance: integrating regulation, standards, and certification,” Transforming Government: People, Process and Policy, vol. 19, no. 3, pp. 535–555, 2025.
  • Gianni, S. Lehtinen, and M. P. Nieminen, “Governance of responsible ai: From ethical guidelines to cooperative policies.” Frontiers in Computer Science., vol. 4, no. 10, MAy 2022. [Online]. Available: https://doi.org/10.3389/fcomp.2022.873437
  • A. Khan, S. Badshah, P. Liang, M. Waseem, B. Khan, A. Ahmad, and M. A. Akbar, “Ethics of ai: A systematic literature review of principles and challenges.” .In Proceedings of the 26th International Conference on Evaluation and Assessment in Software Engineering, no. 2, pp. 383–392, 2022 june. [Online]. Available: http://doi.org/10.1145/3530019.3531329
  • Reed and I. Ng, “Data trusts as an ai governance mechanism,” Property Protection (Topic), vol. 46„ p. 21, 2019. [Online]. Available: http://dx.doi.org/10.2139/ssrn.3334527
  • Sigfrids, M. P. Nieminen, J. Leikas, and P. Pikkuaho, “How should public administrations foster the ethical development and use of artificial intelligence? a review of proposals for developing governance of ai,” Frontiers in Human Dynamics., vol. 4, p. 858108, 2022. [Online]. Available: https://doi.org/10.3389/fhumd.2022.858108
  • H. Vieweg, “Ai and the ethical challenge.” in book ,AI for the Good.., no. 2, pp. 143–157, 2021. [Online]. Available: http://doi.org/10.1007/978-3-030-66913-3 7
  • Green and A. Clayton, “Ethics and ai innovation,” The International Review of Information Ethics, vol. 29, 2021. [Online]. Available: https://doi.org/10.29173/irie417
  • Mu˜noz-Hermoso, F. J. Dom´ınguez-Mayo, A. C. i Mart´ınez, and D. Benavides, “A conceptual framework for smart governance systems implementation,” International Journal of Electronic https://doi.org/10.4018/IJEGR.376170
  • Schneider, R. Abraham, and C. Meske, “Ai governance for businesses.” ArXiv.2011.10672, vol. 27, p. ., 2020. [Online]. Available: https://doi.org/10.48550/arXiv.2011.10672
  • Choung, P. David, and J. S. Seberger, “A multilevel framework for ai governance.” arXiv preprint arXiv:2307.03198, no. 7, 2023. [Online]. Available: https://doi.org/10.48550/arXiv.2307.03198
  • G. R. d. Almeida, C. D. dos Santos, and J. S. Farias, “Artificial intelligence regulation: a framework for governance.” Ethics and Information Technology., vol. 23, no. 1, 2021. [Online]. Available: https://link.springer.com/article/10.1007/s10676-021-09593-z
  • Sepasspour, “A reality check and a way forward for the global governance of artificial intelligence.” Bulletin of the Atomic Scientists, vol. 79, no. 5, pp. 304–315, 2023. [Online]. Available: http://doi.org/10.1080/00963402.2023.2245249
  • Szpilko, F. J. Naharro, N. E. L˘az˘aroiu, G., and A. Torre Gallegos, “Artificial intelligence in the smart city — a literature review,” Engineering Management in Production and Services., vol. 15, no. 4, pp. 53–75, 2023. [Online]. Available: https://doi.org/10.2478/emj-2023-0028
  • Liao and M. Liu, “Critical barriers and countermeasures to urban regeneration from the stakeholder perspective: a literature review,” Front. Sustain. Cities, vol. 5, no. 2, 2023. [Online]. Available: https://doi.org/10.3389/frsc.2023.1115648
  • Stecuła, R. Wolniak, and W. Grebski, “Ai-driven urban energy solutions— from individuals to society: A review.” Energies., vol. 16, no. 24, p. 7988, 2023. [Online]. Available: https://doi.org/10.3390/en16247988
  • K. Singh, P. Singh, L. J. Karmakar, M., and P. Mayr, “The journal coverage of web of science, scopus and dimensions: A comparative analysis.” Scientometrics,, vol. 126, no. 2, pp. 5113–5142, 2021. [Online]. Available: http://doi.org/10.1007/s11192-021-03948-5
  • Baas, M. Schotten, A. Plume, G. Cote, and R. Karimi, “Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies.” Quantitative Science Studies, vol. 1, no. 1, pp. 377–386, 2020. [Online]. Available: https://doi.org/10.1162/qss a 00019
  • Archambault, D. Campbell, Y. Gingras, and V. Lariviere, “Comparing bibliometric statistics obtained from the web of science and scopus,” Journal of the American Society for Information Science and Technology, vol. 60, no. 7, pp. 1320–1326, 2009. [Online]. Available: https://doi.org/10.1002/asi.21062
 

Statistics
Article View: 280
PDF Download: 268


Journal Management System. Powered by iJournalPro.com