Challenge Question
How can we better understand pilot attention and fatigue data to reduce commercial aviation fatalities?
Project Source: Kaggle, through Lassonde
Project Summary
Kaggle, in partnership with Booz Allen Hamilton, is seeking a solution to attention and fatigue issues among airline pilots. Booz Allen Hamilton specializes in consulting, analytics, digital solutions, engineering, and cyber, with industries ranging from defense to health to energy to international development. Booz Allen has been working to reduce aircraft fatalities for business, government, and military leaders for over 100 years. This project seeks to reduce commercial aviation fatalities by better understanding pilot attention and fatigue data. Most flight-related fatalities stem from a loss of “airplane state awareness,” or ineffective attention management on the part of pilots who may be distracted, sleepy, or in other dangerous cognitive states. Using data acquired from actual pilots in test situations, the research team will build a model to detect troubling events from aircrews' physiological data. Models should be able to run calculations in real time to monitor the cognitive states of pilots and alert pilots when they enter a troubling state, preventing accidents and saving lives. Interested students might have skills in data science, mechanics, electronics development, and software development, and they may have interest in aviation, safety, or health-related fields. This challenge originated from the Kaggle website, and team members will be working with a York University mentor rather than a mentor from the organization.
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Organizational Profile
Kaggle is an online data science and machine learning community that also serves as a repository of code and data. Users can find and publish high-quality data sets, write code and build models, ask questions and collaborate, and take data science and machine learning courses through the website. Kaggle also runs competitions, where users have the opportunity to apply their knowledge to real-world machine learning problems and solve a number of complex global challenges.
Project Source Website
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Additional Resources
Key Words
- Aviation
- Accident Prevention
- Health and Safety
- Monitoring Device
- Data Science