(Velalar College of Engineering and Technology, India.)
N. Gayathri is an Assistant Professor in the Department of Computer Science and Engineering at Velalar College of Engineering and Technology, Erode, Tamil Nadu, India. She is engaged in academic teaching and computer science education. Her contribution addresses AI-based approaches for plant disease identification and precision agriculture.
M.S.Devimani, Bolisetty Sreelatha, N.Gayathri. In: Multimodal Artificial Intelligence: Foundations, Intelligent Applications, and Emerging Trends — ISBN: 978-81-17543-28-3. Pages: 202 - 225
Plant ailments pose a significant risk to agricultural output, food safety, and sustainable agriculture practices. Traditional methods of diagnosing plant diseases predominantly depend on visual examination and specialist expertise, which might be constrained by workforce availability, diagnostic lags, environmental fluctuations, and the challenge of differentiating between diseases that exhibit analogous symptoms. This section explores the principles of multimodal plant disease identification, pertinent data types, methods for feature extraction and integration, applications in precision agriculture, and systems for real-time decision support. The chapter additionally addresses the creation of datasets, experimental assessments, issues related to field generalisation and diagnostic ambiguity, as well as nascent trends in explainable AI, edge computing, agricultural foundational models, and autonomous agriculture.
