Man Overboard Detection Verification Through Ranging-Track Geometry
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Solution Overview
Problem
Existing man overboard detection systems require passengers to wear tags, which can be removed, leading to reduced reliability, and lack efficiency in distinguishing between wave motion and actual overboard events, resulting in false alarms and delayed rescue operations.
Innovation Solution
A method and apparatus that utilize ranging data to classify potential man overboard events by determining geometric chords and angles relative to predefined boundaries, distinguishing between wave and human movement patterns, and filtering out false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tag-based detection systems are used to detect man overboard events, then detection capability is improved, but reliability deteriorates because tags can be removed by passengers
Solution Approach 1:
The invention extracts and removes the tag component from the detection system. Instead of requiring wearable tags on passengers, the system uses onboard sensors (accelerometers, gyroscopes, depth sensors) to detect man overboard events directly, eliminating the reliability issue of tag removal while maintaining detection capability
Solution Approach 2:
The invention introduces an intermediary classification mechanism that uses geometric chord analysis and wave pattern recognition to distinguish between actual man overboard events and false alarms caused by waves. This intermediary layer verifies sensor data before triggering alerts, improving reliability without requiring tags
2Measurement precision
If traditional detection systems without classification are used, then system simplicity is maintained, but false alarm rates increase due to inability to distinguish waves from overboard events
Solution Approach 1:
The system performs preliminary classification of sensor data using geometric chord analysis and wave pattern recognition before generating alerts. By pre-processing and categorizing movement patterns, the system distinguishes between waves and actual overboard events, improving measurement precision while managing complexity through automated algorithms
Solution Approach 2:
The invention changes the parameters used for detection from simple motion detection to multi-parameter analysis including geometric chord calculations, angle measurements, acceleration patterns, and depth changes. This parameter transformation enables accurate classification of events while the processing complexity is managed through systematic algorithmic approaches
3Measurement precision
If comprehensive sensor analysis is performed to reduce false alarms, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The system applies partial analysis by focusing on key discriminative parameters (geometric chord characteristics, wave pattern matching) rather than analyzing all possible sensor data. This selective approach maintains high detection accuracy while reducing processing time by concentrating computational resources on the most informative features
Data Source
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AI summary
A method of verifying a potential detection of a man overboard event recorded as a moving object in a plurality of sequential frames of image data in respect of a duration of a time window comprises receiving (900) ranging track data in respect of the time window. A geometric chord is then identified that intersects a start point and an end point of a path described by a ranging track of the ranging track data. A height of the start point and an angle defined by a convergence of the chord and a vertical are then determined (902, 906). The height and the angle are then compared relative to a boundary line in order to classify (910) the path described by the ranging track in relation to a man overboard event, thereby validating the potential detection.