AI-Driven Green Building Technology Innovation: Knowledge Structure, Evolution Trends, Research Paradigms and Future Prospects

The rapidly evolving domain of artificial intelligence (AI) is significantly influencing the green building (GB) sector, acting as a catalyst for green building technology innovation (GBTI). Notably, unlike AI applications in green buildings (AI-in-GB), AI-driven GBTI positions AI as the central force, promoting and leading novel technological breakthroughs. Although research has been conducted in AI-in-GB, there remains a lack of in-depth analysis on AI-driven GBTI advancements. To address this gap, this study comprehensively reviews the existing research in AI-driven GBTI, systematically organizing and analyzing the knowledge structure, thematic evolution, research paradigms, and potential future research directions. This study conducts bibliometric analyses on 151 research publications sourced from Scopus using VOSviewer and CiteSpace, capturing the temporal characteristics, research hotspots, and frontiers of research in this area. Additionally, based on dynamic topic modeling, this study analyzes 86 representative articles, identifying three key research themes and their evolution trends, systematically elucidating the knowledge framework within the field. Through further discussion, this study reveals four core research paradigms and proposes three potential future research directions, providing theoretical support and guidance for its continued development. This study is the first to focus on AI-driven GBTI, contributing to a comprehensive understanding and expanding the knowledge domain of GBTI.