3D Camera Calving Prediction System

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Solution Overview

Problem

Current methods for monitoring cows in labor are labor-intensive, time-consuming, and prone to errors, making it difficult for farmers to predict the calving moment accurately.

Innovation Solution

A method using three-dimensional images to monitor parameters such as body contraction, orientation, pin line length, laying down frequency, and tail movement to predict the calving moment, with a device comprising a 3D camera system and processing unit to record, process, and compare these parameters with reference data to provide timely warnings.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual monitoring of cows in labor is performed, then farmers can observe the calving process, but it is labor-intensive and time-consuming

Engineering Contradiction:

Improvemonitoring accuracyVSAvoidtime for monitoring

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical monitoring with an automated optical measurement system using 3D cameras and image processing algorithms to detect body contraction parameters, thereby eliminating the need for continuous human observation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-monitoring of the cow's calving process through automatic detection of body contraction parameters from 3D images, with the cow's own body movements providing the measurement data without requiring external human intervention

Inventive Principle:

Principle #25Self-service

2Measurement precision

If continuous monitoring of cows in labor is performed, then accurate prediction of calving moment is possible, but it requires constant human presence

Engineering Contradiction:

Improvecalving moment prediction accuracyVSAvoidoperational simplicity

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent replaces continuous human observation with automated 3D image capture and processing systems that continuously analyze body contraction parameters and predict calving moments without human intervention

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system implements continuous feedback by repeatedly capturing 3D images, analyzing body contraction parameter changes, and updating calving moment predictions in real-time based on the rate of change of these parameters

Inventive Principle:

Principle #23Feedback

3Reliability

If manual monitoring method is used, then farmers can detect calving, but it is prone to errors

Engineering Contradiction:

Improvedetection accuracyVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces error-prone manual detection with automated 3D optical measurement and image processing systems that objectively quantify body contraction parameters, eliminating human subjectivity and error

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent transitions from 2D visual observation to 3D spatial measurement, capturing depth information and volumetric changes of the cow's body to provide more accurate and comprehensive calibration parameter measurements

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS10687927B2Method and device to automatically detect calving

Publication Date: 2020.06.23 LELY PATENT NV

AI summary

The invention relates to a method to automatically predict a calving moment of a cow, comprising: recording, by a three-dimensional camera system, at least one three-dimensional image of the cow, processing, by a processing device, the at least one image of the cow, wherein processing of the image comprises determining a parameter indicative of the calving moment, and predicting a calving moment of the cow on the basis of the parameter.