Advancements in AI and AutoML for Plant Leaf Disease Identification in Sustainable Agriculture

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wiley

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info:eu-repo/semantics/embargoedAccess

Özet

The application of artificial intelligence (AI) has shown to be transformational in the field of precision agriculture. In recent years, the demand for effective agricultural practices has been growing considerably, and thus, the proper utilization of AI capabilities will certainly resolve some of the challenging issues and further develop the processes for environmental preservation. Also, the AI’s transformative effect on agriculture has developed itself by replacing some substandard practices with modern and effective approaches. The proposed system describes the idea of an AI application that uses plant scanning technologies to solve agricultural issues. The goal of this smartphone application is to give farmers, agricultural professionals, and other related stakeholders a simple tool for the early detection and proactive management of plant-related difficulties. The proposed system uses AI tools, including machine learning and computer vision techniques, to analyze images that the potential users can take using a mobile smartphone to investigate plants diseases. The software instantly analyzes the images after scanning a plant to produce a detailed report explaining the implicit faults found along with possible remedies and interventions. Eventually, our system offers comprehensive solutions for effectively predicting and addressing the impeding agricultural issues that scan through various plants. Further, the proposed system tends to provide solutions for monitoring the state of the plant and enhance the space for high crop yielding, which, in turn, reduces losses and paves the way for sustainable agricultural practices. Let us explore the cutting-edge world of AI and automated machine learning (AutoML) in the context of sustainable agriculture with a focus on the rapid and accurate identification of plant diseases. This chapter delves into the latest advancements that promises to revolutionize the agricultural industry offering innovative solutions to address plant health challenges and ensure sustainable food production. © 2025 Scrivener Publishing LLC. All rights reserved.

Açıklama

Anahtar Kelimeler

AI, CNN, leaf symptoms, Plant leaf disease, ResNet, SVM

Kaynak

Automated Machine Learning and Industrial Applications

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Künye

Elci, Atilla, Ranichandra C., Senthilkumar N.C. & Narayanasamy, Senthil Kumar (1 January 2025). Advancements in AI and AutoML for Plant Leaf Disease Identification in Sustainable Agriculture. wiley. Automated Machine Learning and Industrial Applications. (63-77). https://doi.org/10.1002/9781394272426.ch4.

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