## 2 Research Methodology  
This research methodology presents a structured approach to conducting a scientometric analysis and classifying research pillars in a specific domain, as in Figure 3. The process begins with the identification of basic keywords relevant to the study (Building Environment, AI, Digital twins, and IoTs), which are then used to search academic databases such as Scopus and Web of Science (WoS). The search focuses on titles, abstracts, and keywords of publications. The initial set of papers is then subjected to inclusion and exclusion criteria to filter out irrelevant studies, resulting in a refined sample. After removing duplicates, the final sample of papers is obtained. Full-text scanning is performed on the final sample to gather detailed insights for further analysis.  
The methodology is divided into two main branches: the scientometric analysis and the identification of research pillars. The scientometric analysis involves examining annual research trends, country-specific contributions, leading researchers, the involvement of various disciplines, and keyword frequency. This analysis provides a quantitative view of the research landscape. Simultaneously, the research pillars are developed through brain-storming and focus on applications-based classification, sustainability-based classification, and the identification of limitations and directions for future research. Together, these two branches guide a comprehensive understanding of the research domain, contributing to the development of insights into current trends, knowledge gaps, and future research opportunities. This study combines quantitative scientometric analysis by evaluating metrics like publication growth, citation patterns, and keyword trends with qualitative analysis of influential studies to interpret emerging themes, research gaps, and interdisciplinary connections. By integrating both approaches, it provides a holistic view of the field, linking statistical trends to contextual insights. This enables a deeper understanding of the impact and potential of technologies like AI, Digital Twins, and IoT in sustainable environments.  
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is a guideline designed to improve the transparency and quality of reporting in systematic  
Figure 3: Research Methodology.  
reviews and meta-analyses. It provides a structured checklist and flow diagram to ensure comprehensive and standardized documentation of the review process [27; 34]. Figure 4 outlines a detailed process for identifying and refining a sample of research papers for a systematic review. Initially, 237 papers were identified based on keyword searches. These papers were then screened against predefined inclusion and exclusion criteria. The inclusion criteria limited the selection to papers published between 2018 and 2024 in English, which resulted in the exclusion of 29 papers. The remaining 208 papers underwent further screening based on exclusion criteria, which eliminated non-peer-reviewed publications, such as conference proceedings, book chapters, and non-research articles, leaving only peer-reviewed research articles and review papers. This step excluded an additional 83 papers, leading to a final sample of 125 papers. The method ensures a focused, high-quality dataset by prioritizing relevant, recent, and peer-reviewed research for the analysis.