Internet-of- Things Behavior Monitoring System Based on Wearable Inertial Sensors for Classifying Dairy Cattle Health Using Machine Learning
2023 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)(2023)
摘要
In this work, an Internet-of- Things (IoT) system for monitoring dairy cattle behavior is developed using wearable inertial sensors and machine learning algorithms. A behavior recognition model is established using the K-Nearest Neighbors (KNN) algorithm to monitor feeding and movement behaviors, including standing, lying, walking, resting, feeding, and ruminating, with high accuracy above 80%. Based on the recognized behaviors from leg and collar sensors, a health classification model is further developed using the Support Vector Machine (SVM) machine learning algorithm, achieving an accuracy of up to 70%. By embedding these models into the developed IoT system, online real-time monitoring of dairy cattle's daily behaviors and health score is demonstrated, enabling health status alerting. This work lays the foundation for designing IoT systems for real-time monitoring of dairy cattle behaviors and health status classification towards cost-effective livestock farming.
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关键词
Internet-of- Things,Behavior classifier,Cattle health,Inertial sensor,Machine learning
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