intelligent crop growth monitoring system using IoT and machine learning

Agriculture is the important part of any developing country. As population increases food requirement also be so traditional farming not sufficient to fulfill food. The development industries, decreases in land space, insufficient rainfall, chemicals used and peoples are moving towards urban cities challenges agricultural field. So we have use another source which called as hydroponics. In hydroponics can developed our plant by supplying nutrients through water without soil. this study had applicability machine learning algorithm like support vector regression(SVR), Linear Regression, Lasso Decision Tree(DT), Ridge regression Random forest find crop growth accuracy from result found that random has given highest 95% performance evaluated on various model Tree Regression having better (R2=0.86), Support Vector (MAE=12.65 RMSE= 21.31) (MSE=4.51). whole dataset stored csv file divided into two subpart 80% data for training 20% testing.