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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Published in | 2016 International Conference on Biomedical Engineering (BME-HUST) pp. 45 - 50 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.10.2016
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Subjects | |
Online Access | Get full text |
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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. |
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ISBN: | 1509010971 9781509010974 |
DOI: | 10.1109/BME-HUST.2016.7782100 |