利用基于物联网传感器网络的机器学习技术检测植物病害

IF 0.9 Q4 TELECOMMUNICATIONS
Bere Sachin Sukhadeo, Y. Sinkar, Sarika Dilip Dhurgude, Shashikant V. Athawale
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引用次数: 0

摘要

近年来,智慧农业发展迅速。农作物病害一般由害虫、昆虫或病原体引起,会对农作物的产量产生不利影响,从而降低农作物的产量。由于各种农作物病害,全国各地的农作物损失严重,其中一个原因就是无法在病害早期发现,使他们无法找到解决办法。本文利用物联网(IOT)传感器网络对叶片中的病害进行检测和分类。精准农业利用机器学习技术来提高作物生长、控制种植过程,并在减少人工参与的情况下提高作物产量。物联网传感器网络正在利用机器学习技术用于精准农业。所提方法的结果显示,总体准确率为 88%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Plant disease detection using machine learning techniques based on internet of things (IoT) sensor network
In recent years, smart agriculture has grown rapidly. A crop disease is generally caused by pests, insects, or pathogens and reduces the productivity of the crop by adversely affecting its yield. There is a severe loss of crops across the country due to various crop diseases, and one reason is not being able to detect the disease in its early stages keeps them from finding a solution. An Internet of Things (IOT) sensor network is used to detect and classify diseases in leaves in this paper. Precision agriculture uses machine learning techniques to increase crop growth, control the cultivation process, and enhance crop productivity with less human involvement. IOT sensor networks are being used in precision agriculture using machine learning techniques. A result of the proposed method shows an overall accuracy of 88%.
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