Agrovision: Smart Plant Monitoring System

Plant diseases pose a significant challenge to the sustainable production of food and agriculture on a global scale. This paper aims to develop a sophisticated system for detecting plant diseases utilizing state-of-the-art Convolutional Neural Network (CNN) techniques in corporation with Internet of Things (IoT) integration. CNN models are renowned for their precision in recognizing objects within images, making them ideal for identifying diseases in intricate leaf images. Moreover, the system incorporates IoT technology to monitor environmental factors like temperature, humidity, and soil moisture in real-time, offering crucial data for prompt decision-making. The model demonstrates exceptional performance in real-world scenarios, boasting an impressive 97 percent accuracy rate.

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Publication Details

Published
2025-02-07
DOI
https://doi.org/10.1109/etis64005.2025.10960828
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Agrovision: Smart Plant Monitoring System

Yedhu Gopan, N Rajeev
Smart Agriculture and AI
article

Agrovision: Smart Plant Monitoring System

Yedhu Gopan, N Rajeev
article en

Abstract

Plant diseases pose a significant challenge to the sustainable production of food and agriculture on a global scale. This paper aims to develop a sophisticated system for detecting plant diseases utilizing state-of-the-art Convolutional Neural Network (CNN) techniques in corporation with Internet of Things (IoT) integration. CNN models are renowned for their precision in recognizing objects within images, making them ideal for identifying diseases in intricate leaf images. Moreover, the system incorporates IoT technology to monitor environmental factors like temperature, humidity, and soil moisture in real-time, offering crucial data for prompt decision-making. The model demonstrates exceptional performance in real-world scenarios, boasting an impressive 97 percent accuracy rate.

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Agrovision: Smart Plant Monitoring System — Yedhu Gopan, N Rajeev · (2025) | TGRS Research Map | TGRS