CROP DOCTOR A Prediction Model Using Machine Learning Algorithm

Abstract

Farming has been practiced in our country for a long time. Agriculture has evolved significantly over time as modernity. The major issue Indian farmers come across is that they do not choose the relevant crop for their soil. They may experience a significant drop in production as a result of this. Here we used accurate farming to solve farmers’ problems. Accurate farming is a modern strategy that combines analyzed information with soil types, city, season, and irrigation techniques to choose the best crop for a particular region. With the city as a base input, we are using weather API for extracting temperature and humidity from a given city. This avoids crop selection errors and improves yield. In this paper, we are developing a crop suggestion system called Crop Doctor, which uses Naive Bayes a machine learning technique, to forecast which crop is suitable for a particular soil category based on data sets. It gives us a recommendation with the benefit of efficient input and output. It assists the farmer to take informed farming decisions.

Keywords: API, Flask, Machine Learning, Naïve Bayes

JEL Classification: C02