Classification of cow behavior using 3-DOF accelerometer and decision tree algorithm

Monitoring cattle motion is essential, since it helps farmers to take a comprehensive view of the cattle's health and estrus time. However, the issue is not able to supervise the cattle in a long time and raising many cattle especially. Therefore, this paper aim to build a device which can sens...

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Bibliographic Details
Published in2016 International Conference on Biomedical Engineering (BME-HUST) pp. 45 - 50
Main Authors Khanh, Phung Cong Phi, Chinh, Nguyen Dinh, Cham, Trinh Thi, Vui, Pham Thi, Tan, Tran Duc
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2016
Subjects
accelerometer
Cow behavior
Decision support systems
decision tree
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Summary:Monitoring cattle motion is essential, since it helps farmers to take a comprehensive view of the cattle's health and estrus time. However, the issue is not able to supervise the cattle in a long time and raising many cattle especially. Therefore, this paper aim to build a device which can sense the states of behavior actives and researches a method to prognosticate the cattle's health by using a cattle monitoring device that can record the 3-axis acceleration to analyze. This sensor is used to measure three-axis accelerometer data on the natural behavior of Vietnamese Yellow cows that live in a cage. The data of the accelerometer output signal are used to modify a simple behavioral classification such as: lying, standing and feeding. Therefore, we can identify some of cattle health events like lameness and estrus cycle. The classification results were tested with the model of the cow.
ISBN:1509010971
9781509010974
DOI:10.1109/BME-HUST.2016.7782100