Shaping the Future of Cities by AI Applications in Sustainable Urban Systems—Unlocking the Potential of AI, Generative AI and Machine Learning

Dear Colleagues,

The Paris Agreement [1], signed in 2015, set the ambitious goal of limiting global warming to well below 2 degrees Celsius above pre-industrial levels, with an aim to limit warming to 1.5 degrees Celsius. Achieving this target requires the rapid and far-reaching transition to a low-carbon economy, with urban areas playing a critical role.

Urban areas are major contributors to greenhouse gas emissions (GHGs), and they are also particularly vulnerable to the impacts of climate change. To address these challenges, innovative solutions and a transformative approach to urban planning and management are urgently needed. 

Artificial intelligence (AI), including generative AI, large language models (LLMs), and machine learning, offers unprecedented opportunities to optimise urban systems, enhance sustainability, and accelerate the transition to a net-zero future [2–5]. These technologies can be applied as follows: 

• Improving energy efficiency: Optimise energy consumption in buildings, transportation, and infrastructure through predictive modelling, demand-side management, and the integration of renewable energy sources. 
• Enhancing resource management: Optimise water usage, waste management, and resource allocation through AI-powered data analysis and predictive modelling. 
• Reducing emissions: Develop and deploy AI-powered solutions for clean transportation, such as optimising public transport routes, predicting traffic flow, and promoting electric vehicles. 
• Increasing resilience: Improve urban resilience to climate change impacts, such as extreme weather events, through predictive modelling, early warning systems, and adaptive infrastructure. 
• Promoting sustainable lifestyles: Engage citizens in sustainability initiatives, encourage sustainable consumption patterns, and improve quality of life through AI-powered tools and platforms. 

By leveraging the power of AI, we can unlock new possibilities for creating sustainable and resilient urban environments that contribute to the ambitious goals of the Paris Agreement. Thus, this call for papers seeks original research papers, case studies, and innovative applications that explore the use of AI and related technologies to advance sustainable urban development, with a focus on the following topics: 

• Green Transportation: Optimising public transport routes, predicting traffic flow, promoting electric vehicles and micro-mobility, and developing intelligent transportation systems. 
• Green Buildings: Designing and operating energy-efficient buildings, optimising building management systems, and promoting renewable energy integration. 
• Smart Cities: Developing intelligent infrastructure, enhancing urban resilience, and optimising resource management (water, energy, waste). 
• Smart Grids: Optimising energy distribution, integrating renewable energy sources, and improving grid stability and efficiency. 
• Smart Living: Promoting sustainable lifestyles, encouraging citizen engagement in sustainability initiatives, and improving quality of life. 
• Smart Business Operations: Enabling businesses to adopt sustainable practices, reduce their environmental impact, and contribute to the net-zero transition. 

Specific areas of interest are as follows: 

• AI-powered solutions for renewable energy integration and grid optimisation. 
• Machine learning for predicting and mitigating climate change impacts on urban areas. 
• Generative AI for designing sustainable urban infrastructure and buildings. 
• LLMs for promoting sustainable behaviours and engaging citizens in climate action. 
• The ethical and societal implications of AI applications in urban sustainability. 
• Case studies demonstrating successful AI-driven solutions for sustainable urban development. 

References: 
[1] UNFCCC (n.d.). Paris Agreement. Available at  https://unfccc.int/process-and-meetings/the-
paris-agreement. 
[2] Xu, F. et al. (2023). Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment. Available at https://arxiv.org/html/2312.11813v1. 
[3]  Huang, J. et al. (2025). Generative Spatial Artificial Intelligence for Sustainable Smart Cities: A Pioneering Large Flow Model for Urban Digital Twin. Environmental Science and Ecotechnology. Available online at https://www.sciencedirect.com/science/article/pii/S2666498425000043. 
[4]  Ullah, A. et al. (2024).  The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions. Available at https://arxiv.org/pdf/2402.14596. 
[5] Li, J. et al. (2024). The Use of Social Media in Sustainable Green Lifestyle Adoption: Social Media Influencers and Value Co-Creation. Sustainability, 16(3), 1133. Available at  https://www.mdpi.com/2071-1050/16/3/1133.

Dr. Stuart So
Dr. Dickson K. W. Chiu
Guest Editors

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