In recent years, the concept of smart cities has become increasingly important in the pursuit of sustainable development goals. In general, common urban challenges have been addressed through smart-city services, and new perspectives for more sustainable cities have emerged. To realize the full potential of such smart urban environments, geospatial approaches have been used as a focal point, offering a plethora of applications that contribute to a better understanding of urban challenges and innovation potentials. Nevertheless, although significant progress has been made, different problems may arise when the available technologies and resources are not understood or even when their potentialities are not properly capitalized. This article reviews the state of the art in the field, highlighting success cases and remaining challenges in exploiting geospatial data-driven strategies, particularly when leveraging geographic information systems, satellites, and distributed sensors to produce and process geospatial data and datasets in urban scenarios. Moreover, a more organized perspective of the area is provided in this article, as well as future development trends, supporting new research efforts in this area when empowering smart cities for a more sustainable future.

The urbanisation of the last century has created a significant demand for urban areas to deliver public services that are efficient, sustainable, and adaptable. This demand is further amplified by the anticipated impacts of climate change and the complexities introduced by rapidly expanding urban populations. In this scenario, smart city initiatives have emerged as a pivotal strategy to address these challenges, leveraging innovative technologies and paradigms such as Internet of Things, Artificial Intelligence, and Data Science to improve the quality of urban life in a more sustainable way. Recently, research efforts in these domains have focused on creating systems that can adapt and respond to changing conditions, enabling greater adaptivity and responsiveness to the needs of urban landscapes. Therefore, this article provides a comprehensive survey of adaptive urban services within a smart city context. Through analyses of recent literature, we investigate the technological foundations that enable the adaptivity of urban services and explore their applications in various urban scenarios, including energy, mobility, emergency management, public safety, and waste management. This article also highlights the benefits of adopting adaptive urban services, such as improved traffic management, resilient emergency management, and enhanced citizen engagement, bringing an important contribution to this broad research area. Finally, we provide a discussion on current technology enablers and challenges and present an overview for future research directions on adaptive urban systems at the forefront of transforming cities into more intelligent ecosystems.

The smart-city revolution has been promoted as the next step in urban development, leveraging technology to achieve enhanced development standards amid the increasingly complex challenges of urbanization. However, despite the implementation of more efficient urban services, issues regarding their tangible effects and impact on people’s lives remain unresolved. In this context, the concept of intelligent cities is seen as a necessary evolution of the smart-city paradigm, positioning human factors as the driving forces behind urban technological evolution. This integrative concept embodies advanced technology to enhance essential urban functions, with sustainability, equity, and resilience as macro-development goals. This study reviews the multifaceted dimensions of intelligent cities, from designing and deploying smart infrastructure to implementing citizen-centric decision-making processes. Additionally, it critically examines the digital divide and highlights the importance of equitable development policies as essential for enabling transformative urban change. By linking technological advancement to social issues, this article provides practical insights and case studies from the cities of Helsinki, Barcelona, and Buenos Aires, demonstrating that smart-city initiatives are still failing to bridge the equity service distribution gap. This comprehensive assessment approach ultimately serves as a reference for future evaluations of intelligent urban transformations.

This paper presents a novel information generation methodology to support safer cycling patterns in urban environments, leveraging for that Large Language Models (LLMs), AI-based agents, and open geospatial data. By processing multiple files containing previously computed urban risk levels and existing mobility infrastructure, which are generated by exploiting open data sources, our method exploits multi-layer data preprocessing procedures and prompt engineering to create easy-to-use, user-friendly assistive systems that are able to provide useful information concerning cycling safety. Through a well-defined processing pipeline based on Data Ingestion and Preparation, Agents Orchestration, and Decision Execution methodological steps, our method shows how to integrate open-source tools and datasets, ensuring reproducibility and accessibility for urban planners and cyclists. Moreover, an AI agent is also provided, which fully implements our method and acts as a proof-of-concept implementation. This paper demonstrates the effectiveness of our method in enhancing cycling safety and urban mobility planning. • A novel method that combines LLMs and AI agents is defined to enhance the processing of multi-domain open geospatial data, potentially promoting cycling safety. • It integrates urban risk data and cycling infrastructure for a more comprehensive understanding of cycling resources, which become accessible by textual or audio prompts.