Published Paper Details:

Agriculture is an important field all over the world where there are many challenges in solving problems in the process of estimating crops based on the conditions. Many solutions have been proposed regarding this problem using IOT based services and Mechanical technology to reduce manual work. These methods are mostly useful in the case of reducing manual work but not in prediction process. It is necessary to be able to predict the optimal crop to be planted based on the soil conditions to minimize losses and maximize profits. In this project we build Machine Learning models to recommend optimum crops to be cultivated by farmers based on several parameters and help them make an informed decision before cultivation. Dataset is prepared with Nitrogen, Phosphorous, Potassium and pH values of the soil. Also, it also contains the humidity, temperature and rainfall required for a particular crop. In this system, we can give input as various features of soil and temperature, humidity, rainfall conditions of the region, based on which a suitable crop will be recommended.