Leveraging artificial intelligence to improve data configuration & accuracy in modern flight management systems

Abstract

Verbatim from Embry-Riddle Scholarly Commons. Not paraphrased, not summarized.

AI (Artificial intelligence) can automate the process of generating optimized flight routes using real-time data, such as AIRAC (Aeronautical Information Regulation and Control), significantly reducing the time needed for flight management tasks. While AIRAC data typically takes up to 28 days to refresh, AI could condense this process to just minutes, enhancing operational efficiency and ensuring pilots have timely and accurate flight information. The research includes practical experiments, prototype code, and visual case studies to demonstrate AI's role in optimizing FMS functions while addressing issues related to data input errors and human intervention. Key findings from trials show the algorithm's effectiveness in calculating parameters like weather conditions and fuel predictions using real-time data from APIs. While the research emphasizes the simplicity of the AI model used, it also stresses the need for further investment to develop more advanced AI systems for aviation.

Author

• Chittayil, Sreeram Embry-Riddle Aeronautical University

Keywords

• Artificial intelligence
• Machine learning
• flight analytics
• Flight optimization
• Dynamics management
• Aviation
• Management and Operations
• Navigation, Guidance, Control and Dynamics