MAPPING ARTIFICIAL INTELLIGENCE RESEARCH IN CONSTRUCTION SAFETY: A BIBLIOMETRIC ANALYSIS OF TRENDS, THEMES AND EMERGING RESEARCH FRONTS

Abstract This study conducts a comprehensive bibliometric analysis of research on artificial intelligence (AI) applications in construction safety, focusing on publications from 2022 to 2026. Utilizing the Web of Science Core Collection as the primary data source, relevant documents were identified and analyzed to map recent trends, thematic developments, and emerging research fronts. The methodology included quantitative assessment of annual publication output, article types, and research area distribution, as well as co-occurrence analysis of keywords. The results reveal a rapid growth in scholarly output during this five-year period, with research articles dominating the publication landscape, supplemented by review papers and conference proceedings. The interdisciplinary nature of the field is evident through substantial contributions from engineering, computer science, and construction technology domains. Keyword analysis highlights prevailing themes such as machine learning, risk assessment, and real-time monitoring, alongside the emergence of topics like computer vision and predictive analytics. The findings underline the accelerating evolution of AI-driven safety research and the increasing integration of advanced computational tools in construction practice. This analysis offers valuable insights for researchers, industry practitioners, and policymakers aiming to enhance construction safety through artificial intelligence.