Aquaculture Synchronization Verification via Optical Filtering

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Solution Overview

Problem

In aquaculture environments, synchronization between illumination and imaging devices is challenging due to electrical disturbances, faulty connections, and incorrect configurations, leading to inaccurate parasite detection as a result of improper illumination frequencies.

Innovation Solution

A framework that uses filters on cameras to verify synchronization by analyzing image intensity, ensuring that images are captured with light within specific frequency ranges, and generates indicators for proper or improper synchronization, thereby preventing spurious identifications and improving parasite detection accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If synchronization verification using filters and image intensity analysis is implemented, then parasite detection accuracy is improved, but device complexity increases

Engineering Contradiction:
Improveparasite detection accuracyVSAvoidsynchronization verification system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces filter images as an intermediary verification mechanism. Instead of directly verifying synchronization between illumination and capture devices, the system captures images through frequency-selective filters and analyzes their intensity. These filter images serve as mediators that indirectly confirm whether the illumination frequency matches the expected range, thereby verifying synchronization without requiring direct communication between controllers.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces direct mechanical/electrical synchronization verification with an optical-based verification method. Instead of checking synchronization signals or timing circuits, the system uses optical filters and image intensity analysis to verify that illumination occurred at the correct frequency. This substitution of mechanical verification with optical measurement simplifies the verification process while improving reliability.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If multiple filters are used to verify synchronization across different frequency ranges, then synchronization verification reliability is improved, but device complexity increases

Engineering Contradiction:
Improvesynchronization verification reliabilityVSAvoidnumber of filters and processing steps
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent divides the verification process into segmented frequency ranges by using multiple filters, each targeting a specific frequency band. Instead of attempting to verify all frequencies simultaneously, the system segments the spectrum and verifies each segment independently. This segmentation allows reliable verification across broad frequency ranges while keeping each individual filter and its processing simple and manageable.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies partial verification by selecting only the critical frequency ranges that need to be monitored for parasite detection. Rather than verifying every possible frequency, the system focuses on the specific frequency bands relevant to the application, using just enough filters to cover the necessary ranges. This partial action approach maintains reliability for the critical functions while avoiding unnecessary complexity from comprehensive verification.

Inventive Principle:
Principle #16Partial or excessive action

3Measurement precision

If images captured during improper synchronization are withheld from parasite detection systems, then detection accuracy is improved, but loss of useful information increases

Engineering Contradiction:
Improveparasite detection accuracyVSAvoidpotential parasite detection data
Core Design Contradiction:
Measurement precisionVSLoss of information

Solution Approach 1:

The patent implements feedback control by continuously monitoring filter image intensities and using this information to determine synchronization status. The system feeds back the synchronization verification results to control whether images are submitted to the parasite detection system. This feedback mechanism ensures that only images captured during properly synchronized illumination are processed, maintaining high detection accuracy while minimizing the loss of valid data through automated decision-making.

Inventive Principle:
Principle #23Feedback

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 framework effectively verifies synchronization, ensuring accurate parasite detection by ensuring images are captured with the correct light frequencies, reducing errors and improving the predictive capabilities of machine learning models.

Implementation Method 1

An image processor receives images generated by a first image generating device that includes a light filter that is associated with light of a particular light frequency

Methodology Applied
Scientific EffectOptical filtering: Filter (optical)

Data Source

PatentUS20240314444A1Enhanced controller synchronization verification
Publication Date: 2024.09.19 TIDALX AI INC
  • US20240314444A1 patent drawing
  • US20240314444A1 patent drawing
  • US20240314444A1 patent drawing

AI summary

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that validate the synchronization of controllers in an aquaculture environment. An image processor receives images generated by a first image generating device that includes a light filter that is associated with light of a particular light frequency while an aquaculture environment was illuminated with light. The image processor determines whether the intensity value of the light frequency in the image satisfies a threshold value based on the generated image. The image processor determines whether the aquaculture environment was illuminated with light of a particular light frequency when the image was generated based on the whether the intensity value of the particular light frequency in the image exceeds the threshold value. The image processor provides for output an indication of whether the aquaculture was illuminated with light of the particular frequency when the image was generated.