2D Livestock Mobility Monitoring for Early Lameness Detection
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Solution Overview
Problem
Existing livestock monitoring systems for lameness and mobility issues in farm animals are non-scalable, prone to inconsistencies, require manual intervention, and are limited by the need for specialized 3D cameras that are difficult to configure and maintain, with restricted operative distance and poor performance in outdoor or poorly illuminated environments.
Innovation Solution
A method using a two-dimensional camera to capture video recordings, segment frames, detect reference points on animal bodies, and use a neural network to determine mobility scores based on relative position changes, enabling autonomous monitoring and early detection of lameness without specialized equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specialized 3D camera equipment is used for monitoring animal mobility, then measurement precision is improved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The patent uses 2D video recordings as a simplified copy or alternative representation instead of requiring complex 3D camera systems. The 2D video data is processed through neural networks to extract mobility information, achieving accurate lameness detection without the complexity of specialized 3D equipment.
Solution Approach 2:
The patent replaces the mechanical/optical complexity of 3D camera systems with a computational approach using 2D video analysis and neural networks. This substitution of physical measurement systems with information processing systems reduces device complexity while maintaining measurement capability.
2Measurement precision
If specialized 3D camera equipment is used for monitoring animal mobility, then measurement precision is improved, but ease of operation worsens due to difficult configuration and maintenance
Solution Approach 1:
The patent uses standard 2D video recording technology instead of specialized 3D cameras, making the system easier to operate and maintain. The neural network processing of 2D video data achieves mobility measurement without requiring expert configuration or specialized maintenance knowledge.
3Measurement precision
If manual sensor positioning on animals is used for monitoring, then measurement precision is improved, but productivity deteriorates due to non-scalable manual intervention
Solution Approach 1:
The patent replaces manual sensor attachment with automated 2D video analysis. The system processes video recordings to extract mobility data without requiring physical contact with animals, enabling scalable monitoring of large populations while maintaining measurement precision through neural network analysis.
Solution Approach 2:
The system performs automated analysis of video recordings to detect lameness and mobility issues without requiring manual intervention for each animal. The neural network automatically processes the data and generates results, enabling the system to scale to monitor entire herds independently.
4Device complexity
If existing video analytics technology is used, then device complexity is reduced, but measurement precision deteriorates due to restricted operative distance and poor performance in outdoor or poorly illuminated spaces
Solution Approach 1:
The patent transforms the approach by changing from 3D spatial measurement to 2D temporal analysis. The neural network analyzes changes in animal appearance and movement patterns across video frames, extracting mobility information from 2D images without requiring controlled lighting or specific distances, thereby maintaining precision while using simple equipment.
Data Source
AI summary
The present invention provides a method and a system for monitoring the mobility levels of individual farm animals and accordingly determining their corresponding mobility score. The mobility score may be indicative of the health and/or welfare status of the animals. The present invention processes a 2D video recording obtained from an imaging device to detect the movement of individual animals through a space. The video recording is segmented over a set of individual frames and in each frame the individual instances of the animal appearing in the vide frame are detected. The detected instances of each animal over a number of frames are grouped together. From each detected instance of an individual animal a set of reference points are extracted. The reference points are associated with location on the animal body. The present invention determines the mobility score of each animal by monitoring the relative position between reference points in each frame and the relative position of each reference point across the set of individual frames associated with an animal.