Simulation–based detection of bovine health anomalies using machine learning and synthetic IoT sensor data
This approach provides a methodological basis for the development of intelligent monitoring systems in precision livestock farming, with potential application in real–world scenarios through the incorporation of IoT sensor data, thus contributing to improved animal welfare and optimized bovine productivity.