International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 12

India | Computer Science amp; Engineering | Volume 14 Issue 6, June 2025 | Pages: 1298 - 1303


Automation of Aviation Digital Records using AI / ML

Prabhat Dubey, Ayan Rajput

Abstract: The aviation industry relies heavily on accurate, up-to-date digital records to ensure regulatory compliance and aircraft safety. With the growing volume and complexity of documentation-ranging from Work Orders (WO), Engineering Orders (EO), Service Bulletins (SB), Task Cards, Certificates, and regulatory records such as ESSA and FAA directives-manual tracking and verification of Airworthiness Directive (AD) status is increasingly inefficient and error-prone. This paper presents an AI/ML-driven automation framework that leverages Artificial Intelligence, Machine Learning, Natural Language Processing, and Generative AI Models to extract relevant keywords and entities from heterogeneous document types. By implementing intelligent keyword extraction techniques, our system enables automated identification, classification, and cross referencing of AD-related information within large-scale Digital Records Management systems. This not only streamlines compliance workflows but also improves data consistency across maintenance operations. Our approach significantly enhances the tracking and validation of critical records in Aircraft Maintenance, offering a scalable solution for next-generation aviation safety and documentation practices.

Keywords: Artificial Intelligence, Machine Learning (ML), Natural Language Processing (NLP), Generative AI Models, Keyword Extraction, Digital Records Management, Automation



Rate This Article!



Received Comments

No approved comments available.


Top