Plant Disease Detection Using Deep Learning

Plant Disease Detection Using Deep Learning

N. Manoj Kumar1, N. Tejaswi2, J. Anitha3, Mohammad Inzamamul Huq⁴, K.B. Srinidhi5

Dr. G. Sateesh6, Mrs. V. Anupama7

[1],[2],[3],[4],[5] B Tech Student, Department of Computer Science and Information Technology

[6] Associate Professor, Department of Computer Science and Information Technology

[7] Associate Professor, Department of Computer Science and Engineering

[1],[2],[3],[4],[5],[6],[7] Lendi Institute of Engineering and Technology, Vizianagaram.

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ABSTRACT
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.