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An Automatic Movement Monitoring Method for Group-Housed Pigs.

Ziyuan Liang1, Aijun Xu1, Junhua Ye2

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Summary
This summary is machine-generated.

This study introduces an automated system for precise pig movement monitoring using YOLOv8m-seg and agglomerative clustering (AC). This technology enhances pig welfare by enabling rapid detection of abnormalities through efficient, real-time analysis of pig behavior.

Keywords:
YOLOv8agglomerative clusteringmovement monitoringpigspatial moment

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Area of Science:

  • Animal Science
  • Computer Vision
  • Agricultural Technology

Background:

  • Continuous monitoring of pig movement is crucial for welfare but technically challenging.
  • Existing methods lack precision and automation for group-housed swine.
  • Identifying subtle changes in pig behavior is key to early abnormality detection.

Purpose of the Study:

  • To develop and validate an automated system for precise monitoring of group-housed pig movement.
  • To improve early detection of pig abnormalities and enhance animal welfare.
  • To provide an efficient and scalable solution for farm-based animal monitoring.

Main Methods:

  • Instance segmentation using YOLOv8m-seg to detect individual pigs.
  • Spatial moment algorithm to determine pig center points from detected contours.
  • Agglomerative clustering (AC) to aggregate individual pig points into a group position.
  • Calculating movement volume based on consecutive frame displacements.

Main Results:

  • YOLOv8m-seg achieved high performance with F1 scores >90% and mAP50-95 of 0.96.
  • The AC algorithm processed data efficiently with an average extraction time under 1 millisecond.
  • The system demonstrated effective monitoring of pig movement over 1500 hours of video data.
  • The method is suitable for efficient implementation on standard hardware.

Conclusions:

  • The developed automated system accurately and efficiently monitors group-housed pig movement.
  • This approach offers a practical solution for enhancing pig welfare through continuous behavior analysis.
  • The technology has the potential to be widely adopted in precision livestock farming.