India Ranks the second country in the world in farm output of 64% of cultivated land which depends on monsoons. Irrigation accounts for Fifty-five to seventy-five percent of water usage In the World. Also, nearly sixty percent of this water while irrigation is wasted. So now we have to conserve the water by making use of soil moisture sensors resulting in smart water management Another is an issue is people always focus on the crop yield whereas before the crop yield the other process such as soil quality and soil fertility, which crop to be grown and what fertilizers needed plays a very important role in the yield of the crop. So in our project, we have focused on these factors such as irrigation, prediction for fertilizer, and which crop to be grown. This project takes real-time data from the deployed sensors such as temperature, moister, NPK and ph values into account and predicts the output in the IoT machine learning environment. The system implemented will be introduced to the semi-supervised learning model where we will be applying algorithms such as KNN and random forest and SVM to predict fertility and whereas for the crop along with this we have considered other factors such as season and place.