Automated Animal Weight Estimation via Image Processing
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Solution Overview
Problem
Current animal farming systems face inaccuracies in weight determination, laborious feed composition preparation, and lack of precision in feeding and health management, leading to suboptimal animal performance and nutrient waste, with manual weighing being impractical and stressful for animals.
Innovation Solution
An automated method that assigns animals to groups, measures feed intake, and calculates intermediate and final weights using a control unit, generating precise farming instructions for feeding, health, and climate control, eliminating the need for frequent animal weighing and reducing labor and equipment costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual weighing of animals is performed regularly to obtain accurate weight data, then measurement precision of animal weight is improved, but labor requirements and stress on animals increase significantly
Solution Approach 1:
The patent replaces manual mechanical weighing systems with an automated image processing system. Cameras capture images of animals, and software algorithms automatically estimate weight based on visual characteristics, eliminating the need for physical handling and mechanical scales.
Solution Approach 2:
The system enables animals to be weighed without human intervention or animal cooperation. The automated image capture and processing occurs as animals naturally move through the facility, eliminating the labor-intensive process of restraining and positioning animals for weighing.
2Measurement precision
If expensive automatic weighing systems or camera systems are deployed to improve weight measurement accuracy, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses standard, inexpensive cameras and processing equipment rather than specialized expensive weighing infrastructure. The system leverages readily available technology to achieve accurate weight estimation without requiring costly dedicated hardware.
Solution Approach 2:
The image processing system serves multiple functions: weight estimation, growth monitoring, and potentially other animal metric assessments. This multi-functionality reduces the need for separate specialized equipment for each measurement type.
3Manufacturing precision
If precise weight data is obtained through frequent manual weighing to optimize feeding, then feeding precision is improved, but time consumption and animal stress increase
Solution Approach 1:
The automated system enables continuous or near-continuous weight monitoring without interrupting animal routines. Images can be captured repeatedly and processed automatically, providing ongoing feeding optimization data without periodic disruptions for manual weighing.
Solution Approach 2:
Replacing manual weighing with automated image-based estimation eliminates the time-consuming process of capturing, restraining, and weighing individual animals, allowing frequent measurements without time loss.
4Ease of operation
If rough estimation methods are used for animal weight to reduce labor and equipment needs, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent replaces subjective visual estimation with objective automated image analysis. Computer vision algorithms quantitatively assess animal dimensions and convert them to weight estimates, eliminating human subjectivity while maintaining operational simplicity.
Solution Approach 2:
The system automatically performs the estimation without requiring farmer expertise or judgment. The software independently processes images and generates weight data, providing precise measurements as easily as simple visual assessment would be performed.
Data Source
Figure 1
AI summary
A method for optimizing farming of one or more groups of animals at one or more farming locations, comprises the steps of assigning individual animals at a start of their growth period to one of the groups and farming locations, sending animal-related information to a control unit, feeding the groups with amounts of respective feed compositions of specified formulae containing specific nutrient values, measuring feed intake amounts by each group, sending the feed intake amounts of the groups together with their specified formulae and specified nutrients to the control unit, calculating intermediate and/or final weights for each group by the control unit based upon at least their measured periodic feed and nutrient intake amounts of their specified formula, and generating farming instructions for each group of animals during the growth period based upon their calculated intermediate and/or final weights.