Dynamic Operator Work Alternation via Physiological Monitoring
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Solution Overview
Problem
Current on-duty/off-duty work alternation planning systems do not account for individual characteristics and real-time states of team members, particularly under non-normal conditions such as illness, suboptimal sleep, or fatigue, leading to inefficient and potentially unsafe work transitions.
Innovation Solution
A system utilizing sensors to monitor the fatigue state of on-duty operators and rest state of off-duty operators, generating alerts for operational control transfers when thresholds are exceeded, allowing for dynamic adjustment of work periods based on real-time physiological data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-planned work alternation with fixed intervals is used, then scheduling simplicity is improved, but adaptability to individual characteristics and real-time states deteriorates
Solution Approach 1:
The system transitions from static pre-planned schedules to dynamic real-time adjustment based on monitored physiological states. The work alternation timing is continuously adapted according to real-time fatigue and rest state measurements, allowing the schedule to flex dynamically rather than following fixed intervals.
Solution Approach 2:
The system implements continuous feedback loops where physiological sensors monitor operator states and feed this information back to the scheduling system. This feedback mechanism enables automatic adjustment of work alternation timing based on actual operator conditions rather than predetermined schedules.
2Productivity
If fixed work alternation intervals are used, then planning efficiency is improved, but reliability of safe operation deteriorates
Solution Approach 1:
Real-time physiological feedback from sensors enables the system to automatically adjust work alternation timing to maintain safe operation levels. The feedback loop monitors fatigue accumulation and rest recovery, triggering alerts when safety thresholds are approached, thereby maintaining reliability without sacrificing planning efficiency.
Solution Approach 2:
The system enables operators to self-monitor their own physiological states through wearable sensors, allowing them to autonomously detect when they need rest or are ready to return to duty. This self-service approach maintains safety by empowering operators to manage their own fatigue levels.
3Adaptability or versatility
If real-time physiological monitoring is implemented, then adaptability to individual states is improved, but device complexity increases
Solution Approach 1:
Wearable physiological sensors serve as intermediaries between the operator's body and the scheduling system. These sensors continuously measure physiological parameters and transmit data to the monitoring system, enabling real-time adaptability without requiring complex direct integration with the operator's biology.
Solution Approach 2:
The system replaces complex manual assessment of operator states with automated electronic sensing and data processing. Physiological monitoring devices automatically detect and transmit fatigue and rest state information, eliminating the need for manual evaluation and reducing overall system complexity despite adding monitoring capabilities.
4Reliability
If frequent work alternations are used, then fatigue management is improved, but productivity deteriorates
Solution Approach 1:
The system dynamically determines optimal work alternation timing based on real-time physiological states rather than using fixed frequent intervals. By monitoring actual fatigue accumulation and rest recovery rates, the system extends on-duty periods when operators are performing well and triggers earlier switches when fatigue indicators appear, optimizing both fatigue management and productivity.
Solution Approach 2:
The system changes the parameter of work alternation timing based on physiological measurements. Instead of fixed time intervals, the alternation timing is adjusted as a variable parameter that responds to measured fatigue and rest states, allowing flexible optimization of both safety and productivity.
Data Source
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AI summary
A system and method for alerting an on-duty operator of the need to transfer operational control to an off-duty operator includes processing first and second physiological and activity data from the on-duty operator and the off-duty operator, respectively. The processor compares the fatigue state of the on-duty operator to a predetermined fatigue state threshold, and the rest state of the off-duty operator to a predetermined rest state threshold. The processor will generate an alert signal indicating that the on-duty operator should transfer operational control to the off-duty operator when (i) the fatigue state of the on-duty operator exceeds the predetermined fatigue state threshold or (ii) the rest state of the off-duty operator exceeds the predetermined rest state threshold.