基于机器学习的低功率种猪温度监测与分析

Chunxi Zhu, Shaopeng He, Yusong Yan, Jian Xiao
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摘要

针对目前种猪体温测量精度差、效率低、体温数据缺乏深入研究的问题,采用国产LP5100低功耗嵌入式芯片,结合ADT7320高精度温度检测芯片和LoRa通信模块,集成成电子耳标,可佩戴在被测猪身上,能够快速高效地对种猪进行高频准确测量。数据将被传输到后台网关进行汇总,由人工智能训练模型进行分析,然后通过网页、微信小程序等形式传输到终端设备。因此,使用温度测量数据来实时确定猪是否发烧,这将大大提高育种效率。本文建立了一个机器学习训练模型,对健康体温进行准确的指导,并设置报警。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temperature Monitoring and Analysis of Low-power Breeding Pigs Based on Machine Learning
In view of the problems of poor accuracy and low efficiency of current breeding pig body temperature measurement and lack of further research of body temperature data, the domestic LP5100 low-power embedded chip, combined with ADT7320 high-precision temperature detection chip and LoRa communication module, is integrated into an electronic ear tag, which is able to worn on the tested pig, can quickly and efficiently carry out high-frequency and accurate measurement of the breeding pig. The data will be transmitted to the background gateway for summary, analyzed by the artificial intelligence training model, and then transferred to the terminal equipment through the form of web page, WeChat Mini Programs and so on. So that using temperature measurement data to determine whether pigs have a fever in real time, which would dramatically improve the efficiency of breeding. In this paper, a machine learning training model is established to give accurate guidance of healthy body temperature and set up an alarm.
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