Smart cities and urban planning have succeeded in gathering the attention of researchers worldwide, especially in the last decade, as a result of a series of technological, social and economic developments that have shaped the need for evolution from the traditional way in which the cities were viewed. Technology has been incorporated in many sectors associated with smart cities, such as communications, transportation, energy, and water, resulting in increasing people’s quality of life and satisfying the needs of a society in continuous change. Furthermore, with the rise in machine learning (ML) and artificial intelligence (AI), as well as Geographic Information Systems (GIS), the applications of big data analytics in the context of smart cities and urban planning have diversified, covering a wide range of applications starting with traffic management, environmental monitoring, public safety, and adjusting power distribution based on consumption patterns. In this context, the present paper brings to the fore the papers written in the 2015–2024 period and indexed in Clarivate Analytics’ Web of Science Core Collection and analyzes them from a bibliometric point of view. As a result, an annual growth rate of 10.72% has been observed, showing an increased interest from the scientific community in this area. Through the use of specific bibliometric analyses, key themes, trends, prominent authors and institutions, preferred journals, and collaboration networks among authors, data are extracted and discussed in depth. Thematic maps and topic discovery through Latent Dirichlet Allocation (LDA) and doubled by a BERTopic analysis, n-gram analysis, factorial analysis, and a review of the most cited papers complete the picture on the research carried on in the last decade in this area. The importance of big data analytics in the area of urban planning and smart cities is underlined, resulting in an increase in their ability to enhance urban living by providing personalized and efficient solutions to everyday life situations.
Dobre et al. (Fri,) studied this question.