AgriSense: Plant Disease Detection Model

This study focusses on the creation and use of AgriSense, a web-based tool for classifying and identifying plant diseases through the uploading of images. The program uses a CNN model trained on a library of plant leaf images to identify healthy, powdery mildew, and rust-infected plant leaves. It is also equipped with features where users can send pictures in ZIP format containing several photos and get a health percentage of all the files. This solution will help farmers and agricultural professionals use the method of early disease detection and monitoring to prevent loss and improve crop yield quality. It then focuses on examining the current state of the system, its efficiency, and recommendations for further enhancement.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2024-11-26
DOI
https://doi.org/10.22214/ijraset.2024.65450
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

AgriSense: Plant Disease Detection Model

Prathamesh Lakhe
International Journal for Research in Applied Science and Engineering Technology
Smart Agriculture and AI
article

AgriSense: Plant Disease Detection Model

Prathamesh Lakhe
article en

Abstract

This study focusses on the creation and use of AgriSense, a web-based tool for classifying and identifying plant diseases through the uploading of images. The program uses a CNN model trained on a library of plant leaf images to identify healthy, powdery mildew, and rust-infected plant leaves. It is also equipped with features where users can send pictures in ZIP format containing several photos and get a health percentage of all the files. This solution will help farmers and agricultural professionals use the method of early disease detection and monitoring to prevent loss and improve crop yield quality. It then focuses on examining the current state of the system, its efficiency, and recommendations for further enhancement.

International Journal for Research in Applied Science and Engineering TechnologyVol. 12(11)
Openalex Percentile: Top 88%
Smart Agriculture and AI
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