Thai Beef Cattle Recognition for Fattening Farms: An Empirical Study of Cattle Cooperative Practices in Chiang Rai

This research focuses on developing an automated system to identify the breed and sex of Thai beef cattle using advanced computer vision technology. By using the YOLOv11 (You Only Look Once) model, a state-of-the-art object detection tool, this system can quickly and accurately identify cattle breeds and determine their sex. High-resolution image datasets were collected and augmented, yielding 81.2% accuracy for breed detection and 95.0% for sex classification, with mAP@50 scores of 85.1% and 99.3%, respectively. However, limited data for certain breeds, like Thai Native and Japanese cattle, reduced the model’s performance for those categories. To overcome this, we aim to expand the dataset from CCTV footage in future studies. The system will include user-friendly features, such as real-time alerts and dashboards, making it practical for farmers to use. This project demonstrates how AI can improve cattle farming by saving time, reducing errors, and supporting better decisions. Future improvements will explore applications in disease detection and behavior monitoring.