Prediction of Behavioral Movement of Cattle Using Accelerometer and Gyro Sensors

Through the observation of individual animal behavior, precision technologies are growing in the context of livestock farming to enhance management techniques and the health and well-being of cattle [1]–[3]. Numerous priority areas can be addressed by consistently gathering data on cattle behavior. The study was conducted to predict the behavioral pattern of cattle using a self-developed prototype model. This study confirmed that the prototype model, i.e., i) a Bluetooth-based cattle node with a neck collar, ii) a low-cost networked software architecture, and iii) a processing algorithm, may enhance livestock management. The low-power Bluetooth protocols provide a dependable data transfer module between the gateway and the node linked to the cow. This low-cost device might be valuable for quick and real-time implementations. A comparison study was made between annotated data and AI-ML algorithms, which showed a significant outcome. So, in this work, an advanced node-based health monitoring module is presented to correctly predict the behavioral parameters of individual cattle, which may help to predict health status far in advance.