基于云计算的智能领式畜牧业健康诊断服务平台研究

Chaowei Jia, Fei Dong
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引用次数: 0

摘要

牲畜的健康状况与牧场的经济效益密切相关。传统的家畜健康监测仍然依赖于人的判断。随着养殖规模的扩大和现代畜牧兽医人才的稀缺,这种方法已不再适用。因此,实现对牲畜身体参数的自动监测是畜牧业未来的发展方向。为了准确判断家畜的健康状况,本文基于智能项圈,研究设计了一种面向家畜的家畜健康诊断算法,可以为养殖户的决策提供一定的参考。通过研究家畜生理状态变化时标志参数的变化规律,决定以家畜的温度、反刍时间和运动量作为特征参数。分别使用基于最小二乘法的线性回归算法、峰值检测算法和k均值聚类算法对原始数据进行提取和校正,并将得到的结果作为健康诊断算法的输入。
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Research on Intelligent collar animal husbandry health diagnosis service platform based on Cloud Computing
The health status of livestock is closely related to the economic benefits of pastures. The traditional health monitoring of livestock still depends on human judgment. With the expansion of breeding scale and the scarcity of modern animal husbandry and veterinary talents, this method is no longer applicable. Therefore, the realization of automatic monitoring of livestock physical parameters is the future development direction of animal husbandry. In order to accurately judge the health status of livestock, based on the intelligent collar, this paper studies and designs a livestock oriented livestock health diagnosis algorithm, which can provide a certain reference for farmers' decision-making. By studying the change law of sign parameters when the physiological state of livestock changes, it is decided to take the temperature, rumination time and exercise volume of livestock as the characteristic parameters. The original data are extracted and corrected by using the linear regression algorithm based on least square method, peak detection algorithm and K-means clustering algorithm respectively, and the obtained results are used as the input of health diagnosis algorithm.
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