AI-Driven Predictive Analytics for Smart Cities and Urban ‎Planning - Agarwal , Ankita; Patil , Dr. Shashikant; Sahu , Dr. Prabhat Ku.; Jeny , Evelyn; Babu , Dushyanth V.; Verma , Ashish; Parmar, Yuvraj (International Journal of Basic and Applied Sciences, 2025)
In recent years, artificial intelligence (AI) has emerged as a primary option for tackling the economic, social, environmental, and governance ‎concerns confronting cities. AI’s advanced capabilities can substantially assist local governments in attaining sustainable urban ‎development. Nonetheless, the application of AI in urban planning remains a relatively uncharted territory, particularly in bridging theoretical ‎concepts with practical implementation. This paper provides a comprehensive examination of the several facets of urban planning in which ‎AI technologies are being investigated or actively utilized, and it explores how these technologies might facilitate or enhance smart and ‎sustainable development. This research employs a systematic literature review following the PRISMA procedure. The principal findings are: ‎‎(a) Early adopters’ real-world applications of AI in urban planning are facilitating broader acceptance by local governments; (b) The ‎expansion of AI utilisation in urban planning necessitates collaboration and partnerships among essential stakeholders; (c) Big data is ‎imperative for the effective application of AI in urban planning; and (d) The integration of artificial and human intelligence is essential for ‎addressing urbanisation challenges and attaining smart, sustainable development. These insights emphasize the necessity to improve ‎planning procedures utilizing sophisticated data and analytical methodologies‎.