Sensor-Based Crew Skill Detection for Real-Time Training Feedback
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Solution Overview
Problem
The workload on instructors who need to train multiple crew members is significant due to the lack of efficient systems for identifying and addressing skill improvement needs in real-time.
Innovation Solution
An improvement item detection apparatus that acquires sensor information from crew members and vehicles, detects areas requiring improvement, selects appropriate transmission destinations for caution information, and transmits this information to reduce the instructor's workload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual monitoring and instruction by instructors is used, then crew member skills can be evaluated and improved, but the workload on instructors becomes significant when the number of crew members is large
Solution Approach 1:
The system enables self-service by having crew members wear sensors that automatically monitor their own operational parameters. The sensors collect data on driving behavior, operational metrics, and safety-related actions, eliminating the need for instructors to manually observe and record each crew member's performance. This automated self-monitoring approach maintains evaluation accuracy while dramatically reducing instructor workload.
Solution Approach 2:
The patent replaces the mechanical system of manual observation and evaluation with an automated sensor-based monitoring system. Sensors collect operational data, processors analyze the information against predefined criteria, and results are automatically transmitted to instructors. This substitution transforms manual labor into automated electronic monitoring, resolving the contradiction between evaluation precision and instructor productivity.
2Reliability
If comprehensive monitoring of crew members is implemented, then skill improvement can be detected, but the complexity of the monitoring system increases
Solution Approach 1:
The monitoring system is segmented into distinct functional modules: sensors for data collection, processors for analysis, communication units for transmission, and display devices for presentation. Each module performs a specific function, making the overall complex system manageable through modular design. This segmentation allows comprehensive monitoring while keeping individual components relatively simple and maintainable.
Solution Approach 2:
The system employs multi-functional sensors that can detect multiple types of operational parameters simultaneously (e.g., acceleration, position, operational status). This universality reduces the total number of separate devices needed, as single sensors perform multiple measurement functions, thereby detecting skill improvements comprehensively without proportionally increasing system complexity.
3Productivity
If real-time feedback is provided to crew members, then learning efficiency improves, but the amount of information to be processed increases
Solution Approach 1:
The system extracts only the most relevant and actionable information from the vast amount of sensor data. The processor identifies specific skill improvement indicators and extracts key metrics that are transmitted to instructors and crew members. This extraction approach provides real-time feedback for efficient learning while filtering out redundant information, thus reducing the information processing load on both the system and users.
Solution Approach 2:
The system implements structured feedback mechanisms where processed information is transmitted to crew members through display devices or communication units. The feedback is delivered in a standardized format that highlights specific improvement areas, enabling efficient learning without overwhelming users with raw data. This organized feedback loop maintains high training efficiency while managing information processing through systematic presentation.
Data Source
AI summary
An acquisition unit (210) acquires sensor information and crew member identification information from a crew member terminal (10). A detection unit (220) detects an improvement-requiring item by processing the sensor information. The improvement-requiring item is an item that needs to be improved by the crew member. A selection unit (230) selects a transmission destination of caution information by using information on the improvement-requiring item. For example, the selection unit (230) selects the transmission destination, for example, by using a type of the detected improvement-requiring item. A transmission unit (240) transmits the caution information to the transmission destination selected by the selection unit (230). The caution information is information indicating that the improvement-requiring item is detected.