This project aims to create a data- and technology-driven and competency-based training framework for pilot and cabin crew training. 

The team will use eye tracking technology to develop a data-driven and competency-based training framework which will provide an objective approach to training, potentially reduce the number of required hours in flight simulators, and reduce training cost.

This technology aims to objectively measure performance, provide personalized training and reduce cost by giving SIA ability to transport and replicate this training beyond a centralized location.

In order to provide a high-quality flight experience, it is necessary to plan the optimal schedule for the crew and to provide immediate feedback post-flight.  Current scheduling and roster solutions use a deterministic and blanket strategy whereby all crew are treated equal.  Existing algorithms optimize based on constraints without the consideration of crew preferences and performance.  As a result, the team propose an intelligent scheduling system which takes into account individual-level factors including preferences and performance. 

The use of AR and VR will help to complement existing training programs for new cadets as well as routine refresher courses for existing flight and cabin crew by providing greater flexibility in where they can train, and the types of scenarios and situations which can be simulated beyond existing methods.

In this project, proven causal inference techniques will be used to identify environmental factors and people attributes that contribute to positive training and flight outcomes. Combining the insights of our models with the existing rostering data from Jeppesen and call center enquiries, an optimal scheduling algorithms will be designed to simultaneously satisfy the preferences of the crew and achieve optimal flight outcomes.