Artificial Intelligence in Aviation Safety: Systematic Review and Biometric Analysis - Gülay Demir; Sarbast Moslem; Szabolcs Duleba (International Journal of Computational Intelligence Systems)
Abstract This study aims to offer aviation safety researchers, practitioners, and decision-makers a comprehensive exploration of integrating advanced technologies, such as artificial intelligence and machine learning, to inform and fortify future safety strategies. Focusing on systematic and bibliometric perspectives, the paper reviewed 224 articles in the Scopus database from 2004 to 2024 (January). Key findings highlight China’s notable contributions to aviation safety research, underscoring its leadership in international collaboration. The techniques employed encompass machine learning, time series models, deep learning, AI, neurophysiological modeling, and optimization algorithms. The analysis discerns prominent research trends, including aviation accident analysis, pilot behavior, aviation safety measures, and endeavors to enhance safety standards. The aviation industry’s steadfast commitment to safety, efficiency, and technological innovation is evident. By uncovering the main structures, foci, and trends in aviation safety research, this study equips researchers and practitioners with crucial insights into ongoing endeavors and potential future developments, fostering a more profound understanding of aviation safety.