智慧农业导刊2024，Vol.4Issue(5)：9-12,4.DOI:10.20028/j.zhnydk.2024.05.003
基于物联网的智慧农业监测系统分析
摘要
Abstract
The main goal of the smart agricultural system is to automatically monitor farmland through automatic irrigation and pest detection framework.Traditional agricultural methods have low crop yields and require a lot of manpower.Therefore,this paper proposes a scheme of smart agricultural monitoring system based on the Internet of Things.The main function of the system is automatic irrigation and plant disease detection,using machine learning algorithm to accurately predict the amount of water needed in farmland,and automatically identify pests according to the needs of farmland.The pest detection module uses proximity algorithm and support vector machine learning algorithm to accurately predict plant diseases.Extracting convenient features from plant leaves and then using these features for classification is helpful to detect whether plants are infected with insect pests.The system monitors,analyzes,evaluates and controls farmland to realize automatic irrigation of water and identification of plant diseases.The machine learning algorithm is numerically analyzed,and the accuracy of classification is up to 84%.关键词
深度学习/神经网络/物联网/分类/特征提取Key words
deep learning/neural network/Internet of Things/classification/feature extraction分类
信息技术与安全科学引用本文复制引用
黄晓艳..基于物联网的智慧农业监测系统分析[J].智慧农业导刊,2024,4(5):9-12,4.基金项目
重庆市教委科学技术研究项目(KJQN202205404) （KJQN202205404）
