Smart cities and the IoT: an in-depth analysis of global research trends and future directions

Abstract

Abstract Extensive scientific investigation is necessary because every government wants to construct smart cities. This is why examining how researchers approach this area of study is critical. This study investigates global research trends in smart cities and the Internet of Things (IoT) by analyzing 14,309 articles from the Scopus database (2010–2024). Using text mining and latent semantic analysis (LSA) via the KNIME tool, the research identifies key areas and trends in smart city development. The k-means clustering algorithm predicts future research directions, highlighting the most active countries, influential authors, and significant sources in the field. The results underscore the need for additional research in sectors where IoT applications for smart cities are still in their early stages. This analysis also offers insights into fostering international collaborations among institutions and researchers. The findings suggest that future research should focus on developing secure, scalable solutions to address challenges across various industries. Overall, this study provides a comprehensive overview of smart city research, offering valuable guidance for researchers and policymakers aiming to advance the integration of IoT technologies into urban environments.

Keywords

• Smart cities
• IoT
• Latent semantic analysis (LSA)
• Scopus
• Data mining
• Natural language processing