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Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

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Automatic identification and analysis of multi-object cattle rumination based on computer vision.

Yueming Wang¹, Tiantian Chen¹, Baoshan Li¹

¹School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China.

Journal of Animal Science and Technology

|June 19, 2023

Summary

This summary is machine-generated.

This study introduces a computer vision method for automatic cattle rumination monitoring, reducing labor and avoiding animal harm. The system accurately calculates rumination time and chews, supporting smart pasture operations.

Keywords:

Cattle Frame difference KCF Rumination YOLOv4

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Area of Science:

Animal Science
Computer Vision
Agricultural Technology

Background:

Cattle rumination is vital for health and productivity, necessitating accurate monitoring.
Manual monitoring is labor-intensive, and wearable sensors can harm animals.
Automated, non-invasive methods are needed for smart pasture management.

Purpose of the Study:

To develop and validate a computer vision-based system for automatic multi-object cattle rumination identification.
To accurately calculate rumination time and the number of chews per cow without manual intervention.
To provide a contactless monitoring solution for enhanced smart farming.

Main Methods:

Utilized a multi-object tracking algorithm combining YOLO and KCF for cattle head detection.
Implemented a frame difference method for rumination recognition and parameter calculation.
Processed individual cow head images to automatically detect and quantify rumination events.

Main Results:

The system achieved an average error of 5.902% for rumination time calculation.
The average error for the number of chews was 8.126%.
Demonstrated accurate multi-object cattle rumination identification and data calculation.

Conclusions:

The proposed computer vision method offers a feasible, contactless approach for monitoring cattle rumination.
This technology provides essential technical support for intelligent smart pasture operations.
Automated monitoring enhances animal welfare and farm management efficiency.