Hand and Eye-Tracking Feature Extraction for Biometric Machine Learning of Flight Simulator Operation

Our project seeks funding through the MITACS Globalink internship to introduce a revolutionary approach to pilot training by integrating virtual flight simulation and biometric machine learning. Dr. Michael Barnett-Cowan leads this cross-disciplinary initiative, utilizing his expertise in flight simulation and motion sickness to develop a sustainable, inclusive, and cost-effective flight training system. At the core of this project is the utilization of motion capture technology to analyze pilot behaviour during flight simulator operation. The collected data will be organized and analyzed by an intern, using semi-supervised machine learning algorithms. These algorithms aim to create predictive models of pilot behaviour, with the ultimate goal of enhancing training and assessment objectivity and efficiency. This work will help to address the environmental and accessibility challenges in the aeronautics industry. This project not only promises to improve the quality of pilot training but also significantly contributes to making aeronautics more sustainable. It exemplifies a collaborative effort to solve complex problems in aviation, aerospace, and space sectors, transcending the capabilities of any single institution. Through this initiative, we aspire to set new standards in flight training, prioritizing inclusivity, environmental consciousness, and adaptability to the industry’s evolving needs.

Faculty Supervisor:

Michael Barnett-Cowan

Student:

Partner:

National University of Kyiv-Mohyla Academy

Discipline:

Life Sciences

Sector:

Aerospace; Artificial Intelligence; Sustainability & the Environment

University:

University of Waterloo

Program: