群养奶牛体温实时监测系统设计与实现

Design and Implementation of Monitoring System for Multiple Cows Body Temperature

将无线连接Wi Fi技术应用于群养奶牛体温实时监测系统,实现了奶牛体温的智能化监测,使奶牛的管理和监控更科学方便。利用DS18B20型数字温度传感器测量奶牛耳道边沿温度,外部通过单线接口与ESP-WROOM模组进行双向通信。ESP-WROOM模组在初次上电时,必须通过Smart Config通信协议获得要接入的AP(Access point)参数并将参数写入程序存储器中,使之与AP建立连接。模组连接成功后,温度传感器采集奶牛体温并传输给微处理器,微处理器接到数据后打包相应参数通过TCP协议发送给数据服务器,My SQL数据库分类储存每头奶牛的数据。使用Java语言编写人机交互界面可以查看相应数据库,实现了奶牛体温变化的实时显示、温度补偿以及历史数据查询等功能。在群养奶牛中同时接收数量众多的体温数据时,可能出现数据并发现象,利用异步通信框架,解决了数据并发问题。采用序时平均数算法更精确地描绘出奶牛体温变化曲线,并且解决了个别数据异常导致曲线波动较大的问题。试验结果表明,系统最佳传输距离在80 m左右时,网络丢包率为4.42%。该系统模块体积小、性能可靠、功耗低,能够快速完成温度监测,并且在30~50℃温度范围内测试精度能够达到±0.2℃。

The body temperature is one of the important parameters for cow health status and also is one of great significance reference for disease diagnosis and treatment. The data collection of cow body temperature by manual can't be real-timing and sometimes has errors so that brings a lot of difficulties to management. In view of development of computer technology and applications in the agriculture,based on the current mainstream of Wi Fi,a real-time monitoring system was applied to inspect the variation of cow body temperature. The digital temperature sensor DS18B20 was used to collect cow 's aural temperature,communicated with ESP-WROOM module that was integrated Tensilica L106,32-bit microcontroller( MCU),a 16-bit RSIC with the complete system and self-contained Wi Fi networking capabilities through one-wire connector. At the first time ESP-WROOM module must be configured by Smart Config protocol with AP's( Access point) parameters which aiming to be slinked with AP. Once the connection was successfully established,the temperature data will be sent to MCU. After received,MCU packs data and parameters send to server through TCP protocol. And the data collected were stored in My SQL database respectively in different cows. The soft system programmed with Java language canachieve real-time acquisition,storage,display and inquiry of cow's temperature data. The asynchronous communication models in view of Java NIO class were used to solve the masses of service requests delivered and the request congestion excluded. The results of experiment showed that errors of the proposed device were ± 0. 2℃ with the range of 30 ~ 50℃,the proper transfer distance of sensor node was 80 m,and the loss rate of network passage was 4. 42%. The power consumption was decreased with collecting time and sleep mode. It is proved that the characteristic of low-power,small bulk,high precision of sample can be provided and applied practically.