IDENTIFICATION OF FERTILIZER BASED ON NPK VALUES AND CROP RECOMMANDATION USING ML ALGORITHM

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M VENKATESAN; M NEERAJA; K GREESHMA; V SUNEETHA; S AVINASH REDDY; U MANU VARDHAN

IDENTIFICATION OF FERTILIZER BASED ON NPK VALUES AND CROP RECOMMANDATION USING ML ALGORITHM

Authors: M VENKATESAN, M NEERAJA, K GREESHMA, V SUNEETHA, S AVINASH REDDY, U MANU VARDHAN

Unique Paper ID: 176884
Volume: 11
Issue: 11
PageNo: 7616-7620

Keywords: Precision Agriculture Machine Learning Fertilizer recommendation Soil Nutrient Analysis.

Abstract:
FertiForecast is an intelligent system designed to identify the most suitable fertilizer for crops based on soil and environmental parameters using machine learning algorithms. The system integrates a Raspberry Pi with multiple sensors, including an air quality sensor, temperature sensor, soil moisture sensor, pH sensor, and NPK sensor, to continuously monitor essential soil and environmental conditions. These sensor values are transmitted to a machine learning model, which analyzes the data and predicts the appropriate fertilizer needed for optimal crop growth. By leveraging predictive analytics, the system recommends fertilizers tailored to specific crops such as chili (mirchi), groundnut, tomato, and paddy, ensuring efficient nutrient management and improved agricultural productivity. This approach helps farmers make data-driven decisions, enhancing yield quality while minimizing excess fertilizer usage and environmental impact. Keywords: Fertilizer recommendation, NPK levels, machine learning, Raspberry Pi, pH sensor, air quality monitoring, precision farming.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 7616-7620

IDENTIFICATION OF FERTILIZER BASED ON NPK VALUES AND CROP RECOMMANDATION USING ML ALGORITHM

Available:https://ijirt.org/article?manuscript=176884

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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