摘要
针对母羊体征监测费时费力、采集方案不完善、传输距离受限等问题,设计了一套基于WSN的母羊体征监测系统。该系统首先通过颈环采集节点实时采集母羊体温,再基于ZigBee和GPRS技术组成无线传感网络将数据传输至云服务器,服务器将数据存储于数据库并在网页平台实时显示。此外,为验证系统的准确性和有效性,采用实时平均数算法计算体温数据的相对误差并对通信方案的网络丢包率进行测试。结果表明,基于WSN的母羊体征监测系统能够实时采集、传输和显示母羊的体征参数,测温相对误差小于1%,网络丢包率小于4%,满足羊场的实际使用需求。研究设计的监测系统运行稳定并突破了通信距离的限制,大大提高了管理人员的工作效率,采集的体征信息对建立母羊运动量及健康评估模型具有十分重要的意义。
Aiming at the problems of time-consuming,manpower-spending,imperfect collection schemes and limited transmission distance of physical parameters monitoring for ewes,a set of physical parameters monitoring system for ewes based on WSN was de⁃signed.Firstly,the system collected body temperature information of ewes through the acquisition node of the collar.Then,wireless sensor network formed by ZigBee and GPRS technology transmitted the data to the cloud server.The server stored the data in the data⁃base and displayed it on the web platform simultaneously.Besides,in order to verified the accuracy and effectiveness of the system,the real-time average algorithm was used to calculate the relative error of body temperature data and the network packet loss rate of the communication scheme was tested.The experimental results showed that physical parameters monitoring system for ewes based on WSN was able to collect,transmit and display physical parameters for ewes in real time.The relative error of temperature measurement was less than 1%,and the network packet loss rate was less than 4%,which met the actual demand of the sheep farm.The monitoring system designed in the research ran stably and broke through the limitation of communication distance.It greatly improved the work ef⁃ficiency of managers.The collected physical data was very important for establishing the amount of exercise and the health assessment model of ewes.
作者
应烨伟
曾松伟
赵阿勇
颜菲菲
杨建铝
YING Ye-wei;ZENG Song-wei;ZHAO A-yong;YAN Fei-fei;YANG Jian-lyu(School of Information Engineering,Zhejiang A&F University,Hangzhou 311300,China;College of Animal Science and Technology,Zhejiang A&F University,Hangzhou 311300,China)
出处
《湖北农业科学》
2021年第11期129-133,140,共6页
Hubei Agricultural Sciences
基金
国家自然科学基金项目(31872397)
浙江省自然科学基金公益项目(LGN18C200017)
浙江农林大学科研发展基金项目(2017FR020)。