Presentation
A Knowledge-Based Recommender System for Personalized Fatigue Mitigation Strategies in Offshore Workers
DescriptionThis study presents a personalized fatigue mitigation recommendation system designed to support fatigue risk management in offshore oil and gas extraction (OGE) operations. Fatigue is a major safety concern in high-risk industries and can result from insufficient sleep, prolonged mental workload, and sustained physical exertion. While existing fatigue management approaches often focus on scheduling or generic interventions, they rarely provide personalized recommendations tailored to a worker’s current fatigue condition.
The proposed system integrates research evidence and offshore expert consensus within a multi-criteria decision-making framework to generate individualized fatigue mitigation strategies. The framework considers four fatigue-related indicators: mental exhaustion, physical exertion, perceived sleepiness, and sleep loss.
The recommendation system was applied to a real-world offshore fatigue dataset containing over 1,800 fatigue records collected from workers on offshore drillships in the Gulf of Mexico. Results demonstrated the feasibility of generating context-aware and personalized recommendations across a wide range of fatigue states. This work contributes a practical and human-centered decision-support approach for improving worker safety, health, and operational performance in high-risk environments.
The proposed system integrates research evidence and offshore expert consensus within a multi-criteria decision-making framework to generate individualized fatigue mitigation strategies. The framework considers four fatigue-related indicators: mental exhaustion, physical exertion, perceived sleepiness, and sleep loss.
The recommendation system was applied to a real-world offshore fatigue dataset containing over 1,800 fatigue records collected from workers on offshore drillships in the Gulf of Mexico. Results demonstrated the feasibility of generating context-aware and personalized recommendations across a wide range of fatigue states. This work contributes a practical and human-centered decision-support approach for improving worker safety, health, and operational performance in high-risk environments.
Event Type
Lecture
TimeTuesday, October 20th11:20am - 11:40am PDT
Location
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