Anchor Chain Video Monitoring for Real-Time Drag Risk Detection
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Solution Overview
Problem
Conventional anchor watchstanders on maritime vessels are unable to detect anchor dragging in real-time, leading to potential vessel grounding or collision risks due to insufficient monitoring frequency and reliance on human observation.
Innovation Solution
An autonomous anchor monitoring system with a camera system and computer vision model that analyzes video feeds to determine drag and collision risk scores, replacing human watchstanders and providing early warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a human watchstander monitors the anchor at predetermined intervals (e.g., every 15 minutes to once per hour), then the monitoring process is simple and requires minimal equipment, but the detection of anchor dragging is delayed and insufficient to prevent vessel grounding or collision
Solution Approach 1:
The patent replaces the mechanical human observation system with an automated computer vision system using cameras and AI algorithms. The system continuously captures images of the anchor chain and uses machine learning models to detect changes in chain angle and configuration, enabling real-time monitoring without human intervention and eliminating detection delays.
Solution Approach 2:
The patent implements continuous automated monitoring of the anchor chain through a computer vision system that operates without interruption. Unlike periodic human checks, the system maintains constant surveillance by continuously capturing images and analyzing chain position, ensuring immediate detection of any anchor dragging conditions.
2Reliability
If automated camera systems are used to continuously monitor the anchor chain, then real-time detection of anchor dragging is achieved, but the system complexity and cost increase significantly
Solution Approach 1:
The patent uses optical copying through camera systems to create visual representations of the anchor chain, replacing the need for direct physical measurement or complex sensor arrays. The computer vision system captures images that serve as copies of the chain's physical state, which are then analyzed by AI algorithms to detect dragging conditions.
Solution Approach 2:
The patent employs a multi-functional integrated system where a single camera platform performs multiple functions: capturing images of the anchor chain, providing live video feeds to bridges, storing historical data, and feeding information to AI algorithms for automated analysis. This consolidates what could be multiple separate systems into one unified solution.
3Illumination intensity
If the lens spins at high speed (900 RPM or more) to remove moisture, then the camera maintains clear visibility in wet conditions, but the mechanical complexity and energy consumption increase
Solution Approach 1:
The patent uses periodic rotational action of the lens at high speed (900 RPM or more) to甩 off moisture through centrifugal force. The lens rotates in periodic cycles, creating conditions that prevent moisture accumulation while maintaining optical clarity during the monitoring process.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system reduces the workload on vessel crew, minimizes fuel consumption, and prevents vessel damage by detecting anchor dragging and unauthorized access, while ensuring timely adjustments to maintain position.
Implementation Method 1
The lens may be configured to spin at 900 revolutions per minute (RPM) or more, facilitated by the motor, the first gear, and the second gear, to remove moisture from the lens
Data Source
AI summary
In some embodiments, a monitoring system may include an enclosure defining a void. The enclosure may be configured to be mounted to a floating vessel. The monitoring system may also include a camera system disposed within the void and coupled to the enclosure. The camera system may be configured to transmit a video feed of an anchor chain to at least a first computing device. The first computing device may be configured to analyze the video feed to determine a drag risk score with a computer vision model based at least in part on an angle of the anchor chain. The first computing device may be configured to determine a collision risk score. Other systems and methods are also disclosed.