Utilizing Physiological Metrics and Change Point Analysis for Real-Time Livestock Health Monitoring

Objective: This study introduces a smart ear tag system for real-time monitoring of cattle health, integrating physiological metrics such as body temperature, heart rate, and oxygen saturation (SpO2) with Change Point Analysis (CPA) to detect state changes. Materials and Methods: The system was tested over a 7-day period on 10 cattle, monitoring health metrics continuously. CPA was applied to identify synchronized changes in the monitored parameters. The system's performance was evaluated based on its ability to detect potential health status changes while maintaining reliability and specificity. Results: The system successfully identified synchronized state changes in one animal, flagging a potential health issue, while showing no significant changes in the other nine animals. This indicates the system’s capability to differentiate between normal variability and significant health-related changes. Conclusion: The proposed smart ear tag system demonstrates significant potential for Precision Livestock Farming. By integrating multiple physiological metrics and advanced analysis, it offers a reliable framework for improving animal welfare and enabling early disease detection.