Automatic temperature monitoring system for pigs using ear tag sensors integrated with bluetooth and machine learning
Abstract
The automatic temperature monitoring system for pigs, integrated with ear tag sensors combined with Bluetooth Low Energy (BLE) technology and machine learning models, offers a modern and efficient solution for monitoring the health of pig herds. The sensors are directly attached to ear tags and are capable of continuously measuring each pig’s body temperature, while also collecting environmental information such as humidity and ambient temperature inside the housing facility. Data is transmitted to a central server via BLE and analysed on a cloud computing platform. The system employs advanced machine learning models such as PCA-SVC, PCA-Decision Tree, PCARandom Forest, and 1D-CNN to enable early detection of abnormal signs. Among these models, 1D-CNN demonstrates outstanding performance, achieving an accuracy of 96.58%, proving its effectiveness in processing time-series data and identifying health issues. The application of smart sensor technology not only enhances monitoring accuracy and reduces labor costs but also optimises real-time surveillance capabilities. This contributes significantly to disease prevention and improves overall livestock management efficiency.
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