## 2 Methodology
### Cluster Analyses  
The quantification of cluster analysis offers a thorough examination of the research environment related to IoT-enabled smart buildings. The investigation included 1146 journals, concentrating on the leading contributors in this field, determined by citation metrics. The PRISMA protocol is used to search the parameters. The following keywords are used for getting the database: Internet of things, smart building, sensors, energy management, and smart home technologies. This citation-based assessment facilitated the identification of pivotal publications that have profoundly influenced the discourse in IoT-enabled smart building research. A comprehensive keyword analysis was conducted with citation analysis, resulting in 7222 distinct terms linked to the relevant literature. Of these, 770 keywords satisfied the established relevance level, indicating a considerable diversity in study areas, including energy efficiency, automation, and sustainability in smart buildings. The substantial quantity of keywords indicates a dynamic and developing area of research, emphasizing the multidisciplinary characteristics of IoT applications in building management. Furthermore, the geographical distribution of contributions to research on IoT-implemented smart buildings was examined, indicating participation from 92 nations. Of these, 46 nations achieved the criteria for significant contributions, demonstrating a worldwide interest and investment in smart building technology. This study highlights the collaborative essence of research in this domain, as it incorporates unique viewpoints and skills from several places. The organizational landscape was evaluated, revealing 1046 entities actively involved in research on IoT-enabled smart buildings. Twenty-six organizations surpassed the threshold for significant research contributions, signifying a focused effort by specific entities to enhance knowledge and innovation in this domain. This comprehensive research underscores the significant cooperation and involvement across academic, governmental, and industrial sectors in the development of smart building solutions using IoT technology. The IoT is revolutionizing several industries via the integration of modern technologies such as machine learning (ML), artificial intelligence (AI), and embedded systems, while also tackling issues related to data privacy and security [19]. In smart homes, the IoT interlinks devices such as thermostats, lighting systems, and security cameras, facilitating effortless management and automation. Artificial intelligence and machine learning improve user experiences by analyzing preferences and managing energy use. In agriculture, IoT sensors assess soil moisture, temperature, and crop health, use machine learning to forecast irrigation requirements, and enhance yields [20]. Autonomous drones do activities such as sowing and pest management with accuracy. Fog computing enhances IoT by facilitating data processing near the source, hence minimizing latency for essential applications such as industrial automation and healthcare [21]. Figure 3 depicts a smart building using IoT technology, highlighting the amalgamation of diverse systems, including energy management, security frameworks, and temperature regulation, which collaboratively improve efficiency and comfort. Nevertheless, the IoT encounters substantial obstacles regarding data privacy and security [22]. The proliferation of billions of linked devices heightens the potential of cyber assaults. AI-driven security procedures facilitate the monitoring of device activity and the identification of abnormalities, while encryption and authentication techniques safeguard important information [23]. Moreover, IoT is intricately linked with embedded systems, allowing real-time monitoring and predictive maintenance in industrial environments, as well as health monitoring via wearables [24].