Plant disease detection using machine learning techniques based on internet of things (IoT) sensor network

被引：0

作者：

Sukhadeo, Bere Sachin ^{[1
]}

Sinkar, Yogita Deepak ^{[2
]}

Dhurgude, Sarika Dilip ^{[3
]}

Athawale, Shashikant V. ^{[4
]}

机构：

[1] Dattakala Grp Inst Fac Engn Bhigwan, Comp Engn Dept, Pune, India

[2] SVPM Coll Engn Malegaon Bk Baramati, Comp Engn Dept, Pune, India

[3] Genba Sopanrao Moze Coll Engn, Comp Engn Dept, Pune, India

[4] AISSMS COE, Dept Comp Engn, Pune, India

来源：

INTERNET TECHNOLOGY LETTERS | 2024年

关键词：

disease detection; gateways; IOT; machine learning; MQTT; Raspberry P-i; sensor network;

D O I：

10.1002/itl2.546

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

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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页数：6

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