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A Fully Automated Crop Disease Monitoring and Management System Based on IoT: IoT-Based Disease Identification for Banana Leaf
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Author(s): K. Seetharaman (Annamalai University, India)
Copyright: 2021
Pages: 20
Source title:
Deep Learning Applications and Intelligent Decision Making in Engineering
Source Author(s)/Editor(s): Karthikrajan Senthilnathan (Revoltaxe India Pvt Ltd, Chennai, India), Balamurugan Shanmugam (Quants IS & CS, India), Dinesh Goyal (Poornima Institute of Engineering and Technology, India), Iyswarya Annapoorani (VIT University, India)and Ravi Samikannu (Botswana International University of Science and Technology, Botswana)
DOI: 10.4018/978-1-7998-2108-3.ch008
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Abstract
In recent years, the IoT has evolved and plays a significant role in many fields like smart city, precision farm, traffic signal control system, and so on. In this chapter, an IoT-based crop disease management (CDM) system is proposed that adopts statistical methods for identifying disease, recognizing a right pesticide, and recommending a right pesticide to farmers. The proposed CDM system monitors the agricultural crops with the help of a CCD camera. The camera continuously photographs the crops and sends them to a Raspberry PI processor, which is placed at a workstation and it is connected to the camera with the help of IoT components. The proposed CDM system analyses the crop leaf images, such as removes noise; segments region of interest (RoI), that is, diseased part of the leaf image; extracts features from the RoI; and identifies the disease and takes appropriate measures to control the disease. The proposed IoT-based CDM system was experimented, and the results obtained encourage both the farmers and the researchers in this field.
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