Implementation of Artificial Intelligence (AI) in global Electronic Pilot Licenses

Abstract

ICAO Annex 1 Chapter 5 specifies that Civil Aviation Authorities “shall use first quality paper or any other kind of appropriate material, including plastic cards, where all data stated in Section 5.1.1.2 of the Annex of reference shall be available.” With the advancement of technology in the digital world, the shift to electronic personnel licensing has been at the forefront of the aviation industry. As of March 2023, ICAO has launched an electronic verification toolset for pilots, EPL (Electronic Pilot Licensing), to allow States to give the option of issuing electronic licenses through a standardized template (Uniting Aviation, 2023). The countries currently known that are participating in electronic pilot licensing are China, Brazil, and Australia. There are several challenges regarding e-licensing, such as license eligibility and verification, the ability to function online and offline, and license standardization worldwide (ICAO TV, 2021). Current interim solutions are automated digital verification by scanning a QR code, a manual query search on an ICAO website, and a visual inspection by inspectors using EPL verification job aids (ICAO, n.d.). However, these solutions are temporary, as there continue to be barriers to streamlining the electronic verification process of pilot licenses, especially when international operations validity is considered.Hence, the presented research focuses on the challenge of tying the e-license to a mobile platform – an application that can be used for license verification and authentication that crew members can carry around portably. The proposed Ai application is in accordance with standards outlined by the International Organization for Standardization, ISO/IEC 18013-5:2021 (ISO, 2021). A high standardization, security, and privacy level are vital to successful implementation. The Purdue CREATE research team provides an AI solution following the EASA recommendation, a lean / 6 Sigma approach in manpower planning.

Keywords: ArtIficial Intelligence, Machine Learning, EASA, FAA, ICAO, Biometrics, Electronic Pilot Licenses

DOI: 10.54941/ahfe1004541