Bibliometric Study of IoT in Security and Monitoring Systems

This study presents a bibliometric analysis of research trends on the Internet of Things in security and monitoring systems using publications indexed in the Scopus database. The objective is to map the intellectual structure, thematic evolution, and collaboration patterns that shape the development of this research field. Bibliographic data were analyzed using VOSviewer to visualize keyword co-occurrence, temporal trends, density distribution, co-authorship networks, institutional collaboration, and country partnerships. The findings indicate that the internet of things serves as the central research hub, closely linked with machine learning, cybersecurity, authentication, and monitoring system architectures. Temporal analysis shows a transition from foundational intrusion detection and network security topics toward intelligent, application-oriented solutions supported by blockchain and data privacy frameworks. Density mapping highlights the convergence of AI-driven analytics with real-time monitoring environments, while collaboration analysis reveals strong research contributions from India and expanding global partnerships involving the United States, United Kingdom, China, and European countries. The results suggest that the field is evolving toward adaptive and context-aware security frameworks embedded within domain-specific monitoring applications such as healthcare and smart agriculture. This study contributes by providing a comprehensive overview of the knowledge structure and future research directions in IoT-based security and monitoring systems.