基于物联网的智慧农业监测系统分析

An Analysis of Smart Agriculture Monitoring System Based on Internet of Things

智能农业系统的主要目标是通过自动灌溉和害虫检测框架自动监测农田。传统农业方法存在作物产量低且需要大量人力。因此,该文提出一种基于物联网的智慧农业监测系统方案。该系统主要功能是自动灌溉和植物病害检测,利用机器学习算法准确预测农田所需的水量,并根据农田的需求自动识别害虫。害虫检测模块使用邻近算法和支持向量机器学习算法,以精确预测植物疾病。先从植物叶片中提取方便的特征,然后利用这些特征进行分类,有助于检测植物是否感染害虫。该系统能监控、分析、评估和控制农田,实现水的自动灌溉和植物病害的识别。对机器学习算法进行数值分析,分类的准确性达到84%。

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%.