Underwater Image Sensor Turbidity Measurement
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Solution Overview
Problem
Existing methods for evaluating water turbidity in artificial water bodies, such as swimming pools, are often complex, costly, and require extensive maintenance, limiting their accessibility and efficiency.
Innovation Solution
A method and system that utilize image data from underwater imaging sensors to estimate water turbidity by analyzing the brightness changes of pixels in images of submerged objects or patterns, employing techniques such as fitting functions and machine learning models to evaluate turbidity based on image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional chemical testing equipment is used to evaluate water turbidity, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex chemical testing equipment with a simplified optical system using imaging sensors (camera) to capture images of the water column. The system uses image processing algorithms to analyze light scattering patterns and calculate turbidity values, substituting mechanical/chemical measurement systems with optical-digital systems that are less complex and more accessible.
Solution Approach 2:
The patent creates a digital copy of the physical water sample by capturing its optical properties through images. Instead of physically analyzing water samples with complex equipment, the system creates image representations that can be processed digitally to derive turbidity information, simplifying the measurement process while maintaining accuracy.
2Measurement precision
If traditional chemical testing equipment is used to evaluate water turbidity, then measurement precision is improved, but maintenance requirements increase
Solution Approach 1:
The patent implements a system that requires minimal maintenance by using solid-state imaging sensors and software-based analysis. The system automatically calibrates itself using reference images and performs self-diagnosis, eliminating the need for frequent manual cleaning, chemical reagent replacement, and mechanical maintenance associated with traditional turbidity meters.
3Device complexity
If image processing methods are used to evaluate water turbidity, then device complexity is reduced, but measurement precision may worsen
Solution Approach 1:
The patent incorporates feedback mechanisms where the system continuously captures images, processes them through algorithms that analyze light scattering patterns, and adjusts its measurements based on reference comparisons. The system uses iterative optimization and validation against known standards to ensure measurement accuracy despite the simplicity of the optical setup.
Solution Approach 2:
The patent transforms the physical parameter of light scattering in water into digital image parameters (pixel intensity values, gradient measurements, histogram distributions). By changing the measurement domain from direct optical density to image processing parameters, the system achieves accurate turbidity measurement using simple, low-cost imaging equipment.
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
This approach provides a simple, cost-effective, and accessible means to evaluate water turbidity, enabling rapid action to maintain water clarity and safety, while reducing the need for complex chemical testing equipment.
Implementation Method 1
Turbidity of the water may constitute a major indicator of water quality and/or chemical balance since it is an indication of the amount of particles accumulated in the water
Implementation Method 2
The one or more images depict one or more varying color patterns of at least part of a circumferential wall and/or floor of the pool
Data Source
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AI summary
Disclosed herein are systems and methods for estimating water turbidity using image data, comprising analyzing a plurality of images of one or more objects submerged in water captured under water from a plurality of distances, calculating a luma value for each of a plurality of pixels along one or more gradient lines across the object(s) in each of the plurality of images, calculating, for each image, a respective maximal intensity change between a lowest luma value and a highest luma value of the pixels along the gradient line(s) in the respective image, evaluating a turbidity of the water based on mapping of the respective maximal intensity change to each of the plurality of distances, and initiating one or more actions in case the turbidity exceeds a certain threshold.