AI-enabled integrated, physics-informed and life-cycle-aware decision systems for net-zero buildings
Description
This dataset contains the bibliometric records and synthesized thematic data supporting the systematic review titled “AI-enabled integrated, physics-informed and life-cycle-aware decision systems for net-zero buildings.” The data facilitates transparency and reproducibility of the findings reported in the article. Content: The dataset comprises the records of 5,977 publications retrieved and analyzed according to the PRISMA 2020 guidelines. The data includes: Bibliographic Metadata: (e.g., [List items like: DOI, title, abstract, year, journal name]) for the 5,977 identified records. Analysis File: The [Excel/CSV] file containing the classification, coding, and thematic categorization based on the proposed four-tier AI-Appropriateness framework. Methodology: The data collection followed a rigorous PRISMA 2020 workflow to map the intellectual structure of AI applications in net-zero buildings. The records were filtered and curated to identify knowledge gaps, physics-adjacency trends, and life-cycle outcomes as detailed in the manuscript. Usage: This dataset is intended for researchers, practitioners, and policymakers interested in the digital transformation of the built environment. It provides a comprehensive baseline for future studies on AI-driven decision-making in sustainable construction.