Exploring a technology-driven approach to improve fatigue data collection in aviation, indicating potential for greater safety.
Introduction: Current fatigue reporting procedures in aviation have significant limitations in providing a comprehensive understanding of fatigue risk exposure for airline operators. They also fail to generate sufficient data to refine bio-mathematical fatigue models. Three key shortcomings of traditional fatigue reporting systems include: 1. Time-consuming process – Filling out a fatigue report takes ~10–15 minutes, a considerable burden for an already exhausted pilot leading to significant under-reporting. 2. One-sided data – Reports are only submitted when fatigue is experienced, preventing insights into working patterns that pilots tolerate well. 3. Inconsistent reporting frequency – Submission rates are highly sensitive to external factors, such as reminders from management, labor disputes, or industry-wide disruptions (e.g., COVID-19). This study explored a scalable, technology-driven approach to complement traditional fatigue reporting by introducing a high-volume, representative data stream that serves as a proxy for overall fatigue risk exposure.
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Klemets et al. (2025) studied this question.
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