Agri Smart AI: Crop and Fertilizer Advisor with Leaf Disease Detection Using Machine and Deep Learning

Agri Smart AI is a precision agriculture system leveraging artificial intelligence to detect plant diseases and provide crop and fertilizer recommendations. It combines Convolutional Neural Networks (CNNs) for disease detection and a Random Forest classifier for crop recommendation, achieving 99.55% and 95.12% accuracy respectively using the PlantVillage and Indian Agricultural datasets. Crop suggestions are based on soil quality, climate conditions, and historical yield data, while fertilizer recommendations are guided by NPK values to prevent overuse and nutrient waste. The system incorporates real-time weather forecasting to enhance decision-making and delivers insights through a user-friendly website to support farmers in improving yield and reducing resource wastage. It offers a cost-effective and scalable solution to modern agricultural challenges. Future development includes expanding the dataset, integrating live sensor data for real-time analysis, and optimizing prediction models for greater adaptability across diverse farming environments.

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Published
2025-06-06
DOI
https://doi.org/10.1109/icicke65317.2025.11136685
Primary Topic
Smart Agriculture and AI
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article
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Agri Smart AI: Crop and Fertilizer Advisor with Leaf Disease Detection Using Machine and Deep Learning

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Agri Smart AI: Crop and Fertilizer Advisor with Leaf Disease Detection Using Machine and Deep Learning

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article en

Abstract

Agri Smart AI is a precision agriculture system leveraging artificial intelligence to detect plant diseases and provide crop and fertilizer recommendations. It combines Convolutional Neural Networks (CNNs) for disease detection and a Random Forest classifier for crop recommendation, achieving 99.55% and 95.12% accuracy respectively using the PlantVillage and Indian Agricultural datasets. Crop suggestions are based on soil quality, climate conditions, and historical yield data, while fertilizer recommendations are guided by NPK values to prevent overuse and nutrient waste. The system incorporates real-time weather forecasting to enhance decision-making and delivers insights through a user-friendly website to support farmers in improving yield and reducing resource wastage. It offers a cost-effective and scalable solution to modern agricultural challenges. Future development includes expanding the dataset, integrating live sensor data for real-time analysis, and optimizing prediction models for greater adaptability across diverse farming environments.

University of Mysore (IN)
Openalex Percentile: Top 81%
Smart Agriculture and AI
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