Iot and Weather Based Smart Irrigation Monitoring And Controlling System for Agriculture

Effective and successful agriculture requires effective water management. Irrigation at appropriate periods and at appropriate levels results in profitable yields. Technology can provide an effective solution for this domain. This work presents an IoT based prediction model that can be to create a smart irrigation system for farming. The proposed architecture is composed of three layers; the data collection layer, machine learning based rainfall prediction layer and the rulebased irrigation requirement identification layer. The data collection layer operates in multiple levels using sensors and APIs, obtaining ground based information and also weather information. The machine learning layer performs rainfall prediction based on past data and the final layer uses defined rules to identify the irrigation needs of crops. The major advantage of this model is that it is not fine tuned to a single crop. The model can be used for any crop and can also be used for multiple crops by the same farmer.