Agriculture and associated sectors account for roughly 18 percent of India's Gross Value Added (GVA). A large-scale, ill-informed decision by farmers could have a severe impact on the entire economy of a region. We ought to build a system that can provide Indian farmers with predictive insights, allowing them to make better decisions about which crops to produce.In most circumstances, a farmer's decision on which crop to cultivate is impacted by his intuition as well as other irrelevant aspects such as generating fast profits, being oblivious of market demand, overestimating the potential of a soil, and so on. The farmer's unwise decision could put his family's financial status under severe strain. Perhaps this will lead to debt, which is one of the numerous contributing factors to the significant number of farmer suicides.

We propose an Intelligent Crop Recommendation system using Machine Learning that predicts crop suitability by factoring all relevant data such as temperature, rainfall, location, and soil condition. This system is primarily concerned with performing AgroConsultant's principal role, which is to provide crop recommendations to farmers.

DHARUN NARAYANAN L K
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ASHWANTH K
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D T SUVANESH
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B VIGNESH
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