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

Abstract

Accurate prediction of the estrus period is crucial for optimizing insemination efficiency and reducing costs in animal husbandry, a vital sector for global food production. Precise estrus period determination is essential to avoid economic losses, such as milk production reductions, delayed calf births, and disqualification from government support. The proposed method integrates estrus period detection with cow identification using augmented reality (AR). It initiates deep learning-based mounting detection, followed by identifying the mounting region of interest (ROI) using YOLOv5. The ROI is then cropped with padding, and cow ID detection is executed using YOLOv5 on the cropped ROI. The system subsequently records the identified cow IDs. The proposed system accurately detects mounting behavior with 99% accuracy, identifies the ROI where mounting occurs with 98% accuracy, and detects the mounting couple with 94% accuracy. The high success of all operations with the proposed system demonstrates its potential contribution to AR and artificial intelligence applications in livestock farming.

Designing a diagnostic method to predict the optimal artificial insemination timing in cows using artificial intelligence

“…However, challenges arise owing to the shortened duration of estrus and an increase in weak estrus cases, where cows ovulate without exhibiting discernible estrus signs. This is attributed to rising herd sizes and augmented milk production (Arıkan et al, 2023). While daily assessments of ovarian dynamics through rectal examination or ultrasound imaging offer a reliable means for determining the optimal insemination time, practicality diminishes as operations scale up and labor resources decrease.…”