Machine Learning-based Smart Farming with Matlab

A key part of the Indian economy is agriculture. However, India's agriculture is currently going through a structural shift that is creating a catastrophe. The sole solution to The crunch is to do everything within our power to turn agriculture into a lucrative business and entice farmers to keep growing crops. This project would use machine learning to assist farmers in making informed decisions about their crops in an attempt to move in this direction. The goal of this study is to employ supervised machine learning algorithms to predict the crop that will be grown based on historical data and environmental conditions. Based on meteorological conditions, this study will provide a crop selection strategy for maximizing crop production. Using seasonal weather forecasting, it also recommends the ideal time to plant certain crops. The Random Forest classification technique is used for selecting appropriate crops, while machine learning algorithms are used to predict the weather.

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Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-04-29
DOI
https://doi.org/10.36948/ijfmr.2025.v07i02.43081
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine Learning-based Smart Farming with Matlab

Nayana Ghuikar
International Journal For Multidisciplinary Research
Smart Agriculture and AI
article

Machine Learning-based Smart Farming with Matlab

Nayana Ghuikar
article en

Abstract

A key part of the Indian economy is agriculture. However, India's agriculture is currently going through a structural shift that is creating a catastrophe. The sole solution to The crunch is to do everything within our power to turn agriculture into a lucrative business and entice farmers to keep growing crops. This project would use machine learning to assist farmers in making informed decisions about their crops in an attempt to move in this direction. The goal of this study is to employ supervised machine learning algorithms to predict the crop that will be grown based on historical data and environmental conditions. Based on meteorological conditions, this study will provide a crop selection strategy for maximizing crop production. Using seasonal weather forecasting, it also recommends the ideal time to plant certain crops. The Random Forest classification technique is used for selecting appropriate crops, while machine learning algorithms are used to predict the weather.

International Journal For Multidisciplinary ResearchVol. 7(2)
National Institute of Statistics and Geography (MX)
Openalex Percentile: Top 94%
Smart Agriculture and AI
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Machine Learning-based Smart Farming with Matlab — Nayana Ghuikar · International Journal For Multidisciplinary Research (2025) | TGRS Research Map | TGRS