AI Powered Plant Identification and Plant Disease Classification System

Agriculture is the livelihood for thousands and thousands of people and appreciably contributes to the monetary boom of countries. a major venture in agriculture is figuring out illnesses as a result of pests and finding effective solutions for restoration. This venture ambitions to locate vegetation and their sicknesses within six one-of-a-kind families of vegetation. It includes 3 modules: preprocessing, identification, and supplementary. in the preprocessing module, the uploaded picture is in comparison with pix to be had inside the plant leaf dataset the use of augmentation techniques. The identification level includes spotting the plant and its diseases the use of a CNN. The supplementary level offers guidelines for important fertilizers to enhance the plant's situation. The undertaking makes use of a plant village dataset, overlaying six households of culmination and a total of 39 sicknesses. The device analyzes the photograph to determine if the plant is in appropriate circumstance or suffering from a sickness, and if affected, it recommends the essential dietary supplements for treatment. This proposed plant sickness category device pursuits to obtain better accuracy compared to existing systems.

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Publication Details

Published
2024-10-15
DOI
https://doi.org/10.1109/icses63445.2024.10763167
Citations
24
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
13.79
Controls
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article

AI Powered Plant Identification and Plant Disease Classification System

M. Sanjay, U. Hemavathi, RVS Praveen, R. Sathya et al.
24 citations
Smart Agriculture and AI
13.79
article

AI Powered Plant Identification and Plant Disease Classification System

M. Sanjay, U. Hemavathi, RVS Praveen, R. Sathya, Afshan Siddiq, S. Gowdish
article en
24 citations

Abstract

Agriculture is the livelihood for thousands and thousands of people and appreciably contributes to the monetary boom of countries. a major venture in agriculture is figuring out illnesses as a result of pests and finding effective solutions for restoration. This venture ambitions to locate vegetation and their sicknesses within six one-of-a-kind families of vegetation. It includes 3 modules: preprocessing, identification, and supplementary. in the preprocessing module, the uploaded picture is in comparison with pix to be had inside the plant leaf dataset the use of augmentation techniques. The identification level includes spotting the plant and its diseases the use of a CNN. The supplementary level offers guidelines for important fertilizers to enhance the plant's situation. The undertaking makes use of a plant village dataset, overlaying six households of culmination and a total of 39 sicknesses. The device analyzes the photograph to determine if the plant is in appropriate circumstance or suffering from a sickness, and if affected, it recommends the essential dietary supplements for treatment. This proposed plant sickness category device pursuits to obtain better accuracy compared to existing systems.

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), Institute of Science and Technology
Zero hunger
Openalex Percentile: Top 1%
Smart Agriculture and AI
13.79
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