Abstract
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.
Acknowledgements
1.I would like to thank Dr. Anju A. Jacobs for her assistance and contributions in the process of this research paper. Helping me gather data and other valuable insights (including an interview). This includes valuable information on current research projects, similar to this paper, that assisted me in the writing of this paper.
2. I would also like to thank Dr. Deepak Mishra for providing the opportunity for an interview and helping me gain valuable information.
Scholarly Commons Citation
Chittayil, S.
(2024).
Leveraging artificial intelligence to improve data configuration & accuracy in modern flight management systems.
International Journal of Aviation, Aeronautics, and Aerospace,
11(4).
DOI: https://doi.org/10.58940/2374-6793.1935
