Real-time plant disease detection and ai-powered solution system
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Date
2026-06
Journal Title
Journal ISSN
Volume Title
Publisher
AIKTC
Abstract
This project focuses on developing a Plant Disease Detection System using
Convolutional Neural Networks (CNN) which a type of deep learning model
widely used in image classification tasks. The system can accurately identify
and classify various plant diseases from leaf images.
The model is trained on a large dataset containing images of healthy and
diseased leaves of multiple crops such as apple, tomato, potato, corn, grape,
and more. It can detect up to 30 different plant diseases with high accuracy.
By using image processing and deep learning techniques, this model helps farmers
and agriculturists quickly identify plant diseases and take preventive measures,
thereby reducing crop loss and improving productivity.
The trained CNN model is integrated into a simple web interface (or mobilefriendly
app) where users can upload a leaf image to get an instant prediction
of the disease along with its name and confidence score.