behavior classification; inertial measurement units; machine learning; precision livestock farming; Animal Science and Zoology; Veterinary (all); General Veterinary
Abstract :
[en] The behavior of livestock on farms is the primary representation of animal welfare, health conditions, and social interactions to determine whether they are healthy or not. The objective of this study was to propose a framework based on inertial measurement unit (IMU) data from 10 dairy cows to classify unitary behaviors such as feeding, standing, lying, ruminating-standing, ruminating-lying, and walking, and identify movements during unitary behaviors. Classification performance was investigated for three machine learning algorithms (K-nearest neighbors (KNN), random forest (RF), and extreme boosting algorithm (XGBoost)) in four time windows (5, 10, 30, and 60 s). Furthermore, feed tossing, rolling biting, and chewing in the correctly classified feeding segments were analyzed by the magnitude of the acceleration. The results revealed that the XGBoost had the highest performance in the 60 s time window with an average F1 score of 94% for the six unitary behavior classes. The F1 score of movements is 78% (feed tossing), 87% (rolling biting), and 87% (chewing). This framework offers a possibility to explore more detailed movements based on the unitary behavior classification.
Disciplines :
Animal production & animal husbandry Computer science
Author, co-author :
Li, Yongfeng; Agricultural Information Institute, Chinese Academy of Agriculture Sciences, Beijing 100086, China ; AgroBioChem/TERRA, Precision Livestock and Nutrition Unit, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
Shu, Hang ; Université de Liège - ULiège > TERRA Research Centre ; Agricultural Information Institute, Chinese Academy of Agriculture Sciences, Beijing 100086, China
Bindelle, Jérôme ; Université de Liège - ULiège > Département GxABT > Ingénierie des productions animales et nutrition
Xu, Beibei; Agricultural Information Institute, Chinese Academy of Agriculture Sciences, Beijing 100086, China
Zhang, Wenju; Agricultural Information Institute, Chinese Academy of Agriculture Sciences, Beijing 100086, China
Jin, Zhongming; Agricultural Information Institute, Chinese Academy of Agriculture Sciences, Beijing 100086, China
Guo, Leifeng; Agricultural Information Institute, Chinese Academy of Agriculture Sciences, Beijing 100086, China
Wang, Wensheng; Agricultural Information Institute, Chinese Academy of Agriculture Sciences, Beijing 100086, China
Language :
English
Title :
Classification and Analysis of Multiple Cattle Unitary Behaviors and Movements Based on Machine Learning Methods.
Inner Mongolia Autonomous Region Science and Technology Major Project
Funding text :
Acknowledgments: I want to thank the financial support from the program of China Scholarships Council (202103250035).Funding: This research was funded by Inner Mongolia Autonomous Region Science and Technology Major Project (2020ZD0004), Science and technology innovation project of Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2016-AII) and 03 Special Project from Jiangxi province (20204ABC03A09).
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