AI - Driven Drone System Using CNN For Detecting Manganese Toxicity & Bacterial Diseases In Tomato Crop

Abstract

in machine learning ml and deep learning dl have revolutionized plant disease detection significantly enhancing agricultural productivity and improving food security this paper presents smart-crop defender an innovative drone-based system that integrates internet of things iot capabilities with deep learning algorithms for autonomous plant disease detection and targeted pesticide application the system leverages convolutional neural networks cnn trained on comprehensive datasets such as plant village to achieve accurate real-time disease identification

Plant phenotyping relevance

CNNを用いたドローン画像によるトマトの病害・マンガン毒性検出が研究の中心であり、植物の状態を直接推定するフェノタイピング手法である。

Code and data availability

The paper is a review/proposal-style article describing a proposed 'Smart-CropDefender' drone system. It mentions training CNNs on PlantVillage, but that is a generic public dataset cited as prior work, not a paper-specific asset. No author datasets, images, code, models, or availability statements are provided, and no

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