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

dc.contributor.authorElci, Atilla
dc.contributor.authorRanichandra C.
dc.contributor.authorSenthilkumar N.C.
dc.contributor.authorNarayanasamy, Senthil Kumar
dc.date.accessioned2025-12-15T10:57:15Z
dc.date.available2025-12-15T10:57:15Z
dc.date.issued1 January 2025en_US
dc.departmentHKÜ, Fen Bilimleri Enstitüsü, Elektrik Elektronik Mühendisliği Anabilim Dalıen_US
dc.description.abstractThe 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.en_US
dc.identifier.citationElci, 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.en_US
dc.identifier.doi10.1002/9781394272426.ch4
dc.identifier.endpage77en_US
dc.identifier.isbn978-139427242-6
dc.identifier.isbn978-139427239-6
dc.identifier.orcid0000-0002-3329-0150en_US
dc.identifier.scopus2-s2.0-105019011883
dc.identifier.scopusqualityN/A
dc.identifier.startpage63en_US
dc.identifier.urihttps://doi.org/10.1002/9781394272426.ch4
dc.identifier.urihttps://hdl.handle.net/20.500.11782/5110
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherwileyen_US
dc.relation.ispartofAutomated Machine Learning and Industrial Applications
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectAIen_US
dc.subjectCNNen_US
dc.subjectleaf symptomsen_US
dc.subjectPlant leaf diseaseen_US
dc.subjectResNeten_US
dc.subjectSVMen_US
dc.titleAdvancements in AI and AutoML for Plant Leaf Disease Identification in Sustainable Agriculture
dc.typeArticle

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