Plant Disease Detection using Deep Learning

Background: Agriculture is a vital sector, providing livelihood and food for a large population. Ensuring plant health is essential for sustainable crop production. Need and Methods: This work proposes a deep learning-based system using Convolutional Neural Networks (CNNs) for automatic detection of plant diseases from leaf images. The model identifies symptoms early, thus supporting timely treatment and reducing crop loss. Results: The system accurately detects plant diseases, recommends suitable fertilizers, and displays real-time sensor data such as temperature and humidity, all on a monitoring interface. Conclusion: Deep learning enables fast, accurate, and automated disease detection, improving crop health and agricultural productivity.