Research on Intelligent collar animal husbandry health diagnosis service platform based on Cloud Computing

Abstract

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With the expansion of breeding scale and the scarcity of modern animal husbandry and veterinary talents, this method is no longer applicable.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.