From transport to smart grids: Big data analytics reshapes urban planning priorities

Smart cities have become one of the fastest-growing fields in global research, with big data analytics playing a decisive role in reshaping how urban planning is studied and implemented. A new bibliometric review tracks a decade of scientific work in this field, providing a detailed map of emerging trends, collaboration networks, and research gaps.

The study, titled A Decade of Studies in Smart Cities and Urban Planning Through Big Data Analytics and published in Systems examines 191 research articles indexed in Web of Science between 2015 and 2024, applying bibliometric and topic modeling techniques to reveal how scholarship on smart cities has developed, which areas dominate the field, and where future progress will depend on deeper integration and policy innovation.

How has smart city research evolved in the last decade?

The review shows that research into smart cities and urban planning through big data analytics has grown consistently, with an annual scientific growth rate of just over ten percent. Most of this research has been highly collaborative: only a fraction of papers were written by a single author, while the overwhelming majority involved teams of three to four co-authors. This pattern reflects the interdisciplinary nature of the field, which spans computer science, urban studies, engineering, and sustainability.

The analysis highlights that citations peaked in 2016, largely due to a series of foundational papers on big data, the Internet of Things, and urban analytics that continue to shape the direction of subsequent studies. While the number of citations has declined in more recent years, the authors stress this is partly a recency effect, since newer studies have not had enough time to accumulate widespread recognition.

Certain journals stand out as leading outlets for this research. IEEE Access and Sustainable Cities and Society have published the largest number of relevant articles, each accounting for a significant share of the literature. In terms of geographical contribution, China, India, and Korea dominate output, while institutions such as King Abdulaziz University and Kyungpook National University emerge as the most active academic centers. Together, these patterns confirm the global nature of smart city research, with Asia taking a particularly strong lead in both volume and institutional engagement.

What are the dominant and emerging themes in smart city research?

The authors applied advanced topic modeling techniques to classify and visualize thematic clusters. The results reveal three broad categories of themes shaping the field.

First are the motor themes, which include networks, authentication schemes, edge computing, cloud services, the Internet of Things, and urban applications in health and transport. These themes are central to the field, driving much of its technological development and providing the backbone for innovation in smart infrastructure.

Second are the basic themes, where intelligent transportation systems, smart grids, and questions of integration and societal impact appear. These themes represent areas that are foundational but require deeper research efforts to reach the same level of maturity as the technological core.

Finally, the analysis identifies emerging and declining themes. Topics such as datafication, climate change, Industry 4.0, deep learning, and traffic-flow prediction are positioned as areas gaining momentum, while others risk fading if not integrated into broader research efforts. The topic modeling confirms that the dominant intellectual cluster, representing over 80 percent of the literature, remains anchored around the triad of smart cities, urban management, and big data analytics.

This division of themes underscores that while the technological backbone of smart cities is advancing quickly, domains such as transport integration, energy systems, and sustainability require more systematic and long-term research. The study calls attention to this imbalance, urging scholars and policymakers to bridge the gap between technical infrastructure and real-world urban challenges.

Where should future research and policy interventions focus?

While the review confirms the steady growth of scholarship, it also identifies significant limitations that risk slowing progress. Chief among them is the reliance on a single database, which may exclude valuable studies published in other outlets. The authors recommend expanding data sources to build more inclusive and comprehensive bibliometric analyses.

Another concern is that the bulk of smart city research remains technology-centric, with relatively less attention paid to integration with urban governance, citizen engagement, and sustainable planning. Addressing this gap will require more interdisciplinary collaboration between data scientists, urban planners, policymakers, and social scientists.

The study also highlights the importance of international collaboration, which already accounts for the vast majority of research but remains uneven across regions. Strengthening cross-border networks could accelerate the transfer of best practices and help standardize approaches to issues such as data governance, privacy, and cybersecurity.

Furthermore, the authors highlight the role of explainable artificial intelligence, digital twins, and federated learning in making urban systems more transparent, secure, and efficient. They also stress that policy frameworks must evolve alongside technological development, ensuring that innovations in data analytics translate into equitable and sustainable urban outcomes.