Natural Language Processing for Automated Classification and Analysis of Aviation Safety Reports

The aviation industry connects people, markets, and cultures around the world and aviation is the key to ensuring that air transport continues to play a major role in driving sustainable economic and social development. The International Air Transport Association (IATA), as the trade association for the world’s airlines, representing some 280 airlines or 83% of total traffic, established one of its strategic objective to continuously improve safety and security performance and achieve year over year reduction of the 5-year accident rate from 2019-2035.
This project is to support effective risk identification by applying Natural Language Processor technologies in classifying accident and incident report into global harmonized classification system. This will support efficient and effective data-driven safety risk analysis, supporting global aviation safety community and return socioeconomic benefits of safe and reliable air transport to public.

Faculty Supervisor:

Philippe Langlais

Student:

Partner:

International Air Transport Association

Discipline:

Computer science

Sector:

Other services (except public administration); Professional, scientific and technical services; Transportation and warehousing

University:

Université de Montréal

Program: