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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67810
Volume:
10 |
10 |
Oct 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science
S.A College of Arts & Science
Department of Computer Science
S.A College of Arts & Science
Department of Computer Science
S.A College of Arts & Science
Rapid advances in Artificial Intelligence (AI) are creating new opportunities to address environmental challenges while improving the way urban areas are planned, managed, and experienced. Technologies such as machine learning, computer vision, and natural language processing can support energy optimization, pollution control, waste processing, water management, and efficient use of urban resources. This chapter presents the role of AI in promoting environmental sustainability within smart-city environments, with emphasis on predictive analysis, real-time monitoring, intelligent decision support, and data-driven urban management. It further discusses AI applications in transportation, infrastructure, buildings, public services, and civic engagement. Along with these opportunities, the chapter considers important concerns related to privacy, cybersecurity, algorithmic bias, inclusiveness, energy consumption, and governance. Finally, emerging directions such as federated learning, edge AI, green AI, and climate-oriented urban modelling are discussed as approaches for developing resilient and sustainable cities.
KEYWORDS
Artificial Intelligence can contribute significantly to the development of sustainable and resilient smart cities by supporting intelligent monitoring, resource optimization, environmental prediction, efficient mobility, and responsive public services. Its value is particularly evident when large and continuously changing datasets must be analysed to support timely urban decisions. Applications in energy, transportation, waste, water, buildings, and environmental monitoring demonstrate the broad scope of AI for sustainable urban development [2, 6, 8, 9, 10]. At the same time, successful deployment depends on responsible system design and governance. Privacy and cybersecurity, fairness and inclusion, computational energy requirements, transparency, and institutional accountability must be considered alongside technical performance. Future smart-city initiatives can benefit from approaches such as federated learning, edge AI, green AI, and climate-oriented modelling. A balanced integration of these technologies can help cities pursue improved environmental performance while supporting resilient and people-centred urban development.
[1] Yim, I. H. Y., & Su, J. (2025). Artificial intelligence (AI) learning tools in K-12 education: A scoping review. Journal of Computers in Education, 12(1), 93–131. [2] Wolniak, R., & Stecuła, K. (2024). Artificial Intelligence in Smart Cities—Applications, Barriers, and Future Directions: A Review. Smart Cities, 7(3), 1346–1389. [3] ZenRobotics. (2020). Smart Recycling with AI. https://www.zenrobotics.com [4] Sidewalk Labs. (2021). Digital Innovation for Sustainable Urban Design. https://www.sidewalklabs.com [5] Pluto AI. (n.d.). AI for Smart Water Infrastructure. https://www.pluto.ai [6] Uriarte-Gallastegi, N., Arana-Landín, G., Landeta-Manzano, B., & Laskurain-Iturbe, I. (2024). The role of AI in improving environmental sustainability: a focus on energy management. Energies, 17(3), 649. [7] Floridi, L., et al. (2018). AI4People—An Ethical Framework for a Good AI Society. Minds and Machines, 28(4), 689–707. [8] Batty, M. (2018). Artificial Intelligence and Smart Cities. Environment and Planning B: Urban Analytics and City Science, 45(1), 3–6. [9] Gundeti, R., Vuppala, K., & Kasireddy, V. (2024). The future of AI and environmental sustainability: Challenges and opportunities. Exploring Ethical Dimensions of Environmental Sustainability and Use of AI, 346–371. [10] Alahi, M. E. E., Sukkuea, A., Tina, F. W., Nag, A., Kurdthongmee, W., Suwannarat, K., & Mukhopadhyay, S. C. (2023). Integration of IoT-enabled technologies and artificial intelligence (AI) for smart city scenario: recent advancements and future trends. Sensors, 23(11), 5206.
Publication Date
10/12/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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