Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Crop production is vital for food supply, yet plant diseases continue to cause significant
losses and reduce farmers’ income. In India, the problem is intensified by the overuse of pesticides, which can damage ecosystems and affect human health. Quick and accurate disease detection is essential, but many farmers lack timely access to expert support.This project presents a simple mobile-based system that helps identify plant diseases using images of affected crops. By applying Artificial Intelligence, particularly Convolutional Neural Networks (CNNs), the system provides fast and reliable results along with basic treatment guidance. It also improves over time by learning from new data and allows farmers to connect with agricultural experts when needed.The solution is designed to be affordable and easy to use, supporting better crop management and promoting safer farming practices
Keywords:
Plant disease detection, Artificial Intelligence, CNN, Image-based diagnosis, Precision agriculture, Sustainable farming, Farmer support system
Cite Article:
"Leaf Speak: Detect, Predict, Protect", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b187-b192, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604164.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator