A Process for Improved Agriculture: Harvest Forecasting

Abstract

According to the Niti Aayog study, the Indian government plans to quadruple farmers' incomes by 2022. In different research, Niti Aayog showed that from 2001 to 2011, there was a 3.6 percent decline in all agricultural activity. The soil birthrate, volume of water, and temperature are shifting in India as well as its subcontinent, that is one of the main reasons why people are giving up farming. As a result, the farmers' crops don't provide an abundance following harvest. The naive bayes method, a supervised learning technique, will be used by the model to forecast the best crop. Along with pertinent factors like temperature, humidity, and climate, the seed information for the plants will really be gathered to help them develop effectively and efficiently. Users may anticipate the most appealing crop for improved agriculture by entering parameters like area, weather, etc. on the application system.