Applications of artificial intelligence in air operations: A systematic review
Cristian Lozano Tafur, Rosa Gabriela Camero, Didier Aldana Rodríguez, Juan Carlos Daza Rincón, Edwin Rativa Saenz
Abstract
• AI enhances efficiency in air traffic management and aircraft performance. • Machine learning improves trajectory prediction and conflict resolution. • Data integration optimizes safety and decision-making in air operations. • AI applications focus on sustainability and reducing operational risks. • Challenges remain in integrating real-time dynamic data for critical operations. This systematic review evaluates the applications of artificial intelligence (AI) in air operations, following the PRISMA 2020 methodology. The primary objective is to identify and analyze key areas in air operations where AI and machine learning have demonstrated significant impact. Inclusion criteria encompass studies published between 2008 and 2023, in any language, related to the application of AI algorithms in air operations. The search was conducted in databases such as Scopus and Web of Science on May 1, 2024. A total of 120 studies were included, highlighting their diversity and relevance in areas such as aircraft trajectory prediction, air traffic management, and aircraft performance optimization, among others. The main findings indicate that the use of AI in trajectory prediction and air traffic management has significantly improved operational efficiency and safety. However, the studies also point out limitations related to data variability and challenges in integrating multiple information sources. The conclusions suggest that, despite these limitations, AI holds considerable potential to transform air operations, recommending a greater focus on research and development in this field.