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Estrus Detection and Dairy Cow Identification with Cascade Deep Learning for Augmented Reality-Ready Livestock

İbrahim Arıkan1, Tolga Ayav1, Ahmet Çağdaş Seçkin2

  • 1Computer Engineering Department, İzmir Institute of Technology, Izmir 35430, Türkiye.

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Accurate estrus period prediction in cows is vital for livestock farming efficiency. This study uses augmented reality and AI for precise estrus detection and cow identification, improving animal husbandry outcomes.

Keywords:
artificial intelligenceaugmented realitydairy cow identificationdeep learningestrus detectionimage processinglivestockprecision livestock farmingtransfer learning

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Area of Science:

  • Agricultural Science
  • Computer Science
  • Veterinary Medicine

Background:

  • Estrus period prediction is critical for efficient animal husbandry and preventing economic losses in dairy farming.
  • Current methods for estrus detection can be labor-intensive and may lack precision, impacting insemination success and farm profitability.

Purpose of the Study:

  • To develop and evaluate an integrated system for accurate estrus period detection and cow identification using augmented reality (AR) and deep learning.
  • To enhance insemination efficiency and reduce economic losses in livestock farming through precise estrus monitoring.

Main Methods:

  • Utilized deep learning for mounting behavior detection.
  • Employed YOLOv5 for identifying the region of interest (ROI) of mounting events.
  • Integrated YOLOv5 for cow ID detection within the cropped ROI.
  • Combined AR technology with AI for real-time livestock monitoring.

Main Results:

  • Achieved 99% accuracy in detecting mounting behavior.
  • Reached 98% accuracy in identifying the mounting region of interest (ROI).
  • Demonstrated 94% accuracy in detecting the specific cows involved in mounting (mounting couple).

Conclusions:

  • The proposed AR and AI-integrated system significantly improves the accuracy of estrus period detection and cow identification in livestock.
  • This technology offers a promising advancement for precision livestock farming, enhancing operational efficiency and economic viability.
  • The system's high accuracy highlights its potential for broader applications in animal husbandry and AI-driven agricultural solutions.