Crop Prediction Based on Soil Properties using Machine Learning for Smart Farming

The main difficulty of farming in our country is that the right perception of the farm’s wellbeing, and organize the showering. The reason for this idea is to break down the capacity of IoT procedures comparable to poverty in these areas, other than the prerequisites known in these products and with weight on cultivating. This study breaks down examples of an IoT to alter the cultivating wants of the items for the area to boost the supply. Our paper aims to provide guidance on regression and machine learning models, an overview of issues pertaining to assessing a model’s accuracy, and recommendations for presenting a model’s results. This paper gives the prediction for the crop on the bases of soil properties. Implementation shows accuracy and error rate of different regression models on given dataset and gives the predicted crop as well. As outcome random forest and decision tree both gives the remarkable output for crop prediction.