The Application of Internet of Behavior in Smart City Management: A State-of-the-Art Review and Future Perspectives

Source abstract

Smart city development implies a transformation of urban environments by employing cutting-edge technologies, such as Artificial Intelligence (AI), Internet of Things (IoT), data analytics, and Internet of Behavior (IoB). Among these, IoB offers powerful tools for understanding and influencing human behavior in urban systems. This study presents a Systematic Literature Review (SLR) on IoB applications across six major smart city sectors: (1) healthcare; (2) transportation; (3) retail and marketing; (4) education; (5) tourism; and (6) the environment to provide a comprehensive understanding of applications and gaps. While previous studies examined city domains individually, this article introduces a cross-sectoral classification framework that maps IoB use cases to four core city management functions. The framework supports urban planners, policymakers, and engineers in identifying opportunities to integrate behavioral data into more efficient city management practices. A total of 27 studies published from 2020 to 2025 were systematically selected from eight academic databases. The analysis highlights methodological trends, particularly Machine Learning (ML) and Deep Learning (DL), and examines ongoing challenges, including security, scalability, privacy, and ethical governance. Overall, this SLR identifies limitations of IoB across smart city sectors and underscores the need to integrate IoB-based systems with infrastructure, regulatory frameworks, and interdisciplinary design principles.