摘要
为构建农作物环境信息实时监测系统,实现农作物生长的智慧管理,构建了一种智慧农业监测管理系统。首先,基于物联网技术从感知层、传输层、应用层3个维度,以STM32为控制核心搭建智慧农业监测管理系统,通过传感器收集环境温湿度、土壤温湿度、光照强度、空气质量等环境数据,利用无线模块将其传输至服务器,实现对环境因子的监测和远程控制;其次,基于OpenCV库的图像处理算法和SVM模型实现对作物病害图像的分类、识别;最后,基于QT平台完成上位机UI界面的设计。通过试验测试,该系统在信息传输和设备控制方面准确、可靠,对病害图像分类平均准确率为96.3%,对石榴褐斑病的识别准确率最高,达97.4%。
In order to build a real-time monitoring system of crop environmental information and realize intelligent management of crop growth,an intelligent agricultural monitoring and management system was constructed.Firstly,based on the Internet of Things technology,the intelligent agricultural monitoring and management system was built with STM32 as the control core from three dimen⁃sions of perception layer,transmission layer and application layer.The environmental data such as environmental temperature and hu⁃midity,soil temperature and humidity,light intensity and air quality,etc,were collected through sensors,and transmitted to the serv⁃er using a wireless module to achieve monitoring and remote control of environmental factors.Secondly,the image processing algorithm and SVM model based on OpenCV database were used to classify and recognize crop disease images.Finally,the upper computer UI interface was designed based on the QT platform.Through experimental tests,the system was accurate and reliable in information transmission and equipment control.The average accuracy rate of the system for disease image classification was 96.3%,and the accu⁃racy rate of pomegranate brown spot recognition was the highest,reaching 97.4%.
作者
何建强
张莹
许兴
HE Jian-qiang;ZHANG Ying;XU Xing(College of Electronic Information and Electrical Engineering,Shangluo University,Shangluo 726000,Shaanxi,China;Shangluo Intelligent Agriculture Research Center,Shangluo 726000,Shaanxi,China)
出处
《湖北农业科学》
2024年第8期176-181,187,共7页
Hubei Agricultural Sciences
基金
陕西省教育厅2022年度专项科学研究计划项目(22JK0356)
陕西省大学生创新创业训练计划项目(S202311396068)。
关键词
物联网
智慧农业
监测管理系统
图像识别
SVM
Internet of Things
intelligent agriculture
monitoring and management system
image recognition
SVM
