Agriculture growth mainly depends on diverse soil parameters, namely Nitrogen, Phosphorus, Potassium,Crop rotation, Soil moisture, pH, surface temperature and weather aspects like temperature, rainfall, etc. Technology will prove to be beneficial to agriculture which will increase crop productivity resulting in better yields to the farmer. The proposed work provides a solution for Smart Agriculture by monitoring the agricultural field which can assist the farmers in increasing productivity to a great extent. This work presents a system, in a form of a website, which uses Machine Learning techniques in order to predict the most profitable crop in the current weather and soil conditions. This system can also help in predicting the yield of the crop using weather parameter, soil parameter and historic crop yield. Thus, the work develops a system by integrating data from various sources, data analytics, prediction analysis which can improve crop yield productivity and increase the profit margins of farmer helping the mover a longer run.

Agriculture growth mainly depends on diverse soil parameters, namely Nitrogen, Phosphorus, Potassium,Crop rotation, Soil moisture, pH, surface temperature and weather aspects like temperature, rainfall, etc.