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Deepali Prashant Shete is an Assistant Professor in the Department of Statistics and Mathematics at Modern College of Commerce and Computer Studies, Nigdi, Pune, Maharashtra, India. Her academic background combines mathematical and statistical perspectives with emerging computational applications. She contributes to the application of autonomous AI agents for plant disease detection and smart agriculture.
Plant ailments significantly influence agricultural yield, crop calibre, and food safety. Prompt and precise detection of plant ailments is crucial for reducing agricultural losses and facilitating prompt intervention strategies. Traditional disease detection often relies on manual field assessments and agricultural knowledge, which can be labour-intensive, subjective, and challenging to implement throughout extensive farming regions. Recent developments in Artificial Intelligence (AI), computer vision, deep learning, the Internet of Things (IoT), unmanned aerial vehicles (UAVs), remote sensing, and edge computing have facilitated the automation of plant disease identification.Autonomous AI agents can establish a basis for anticipatory, scalable, and data-informed plant health management, all while ensuring suitable supervision from farmers and agronomists.