Desalination management and resource use have become increasingly important due to burgeoning water demand and deteriorating environmental conditions. Seawater desalination is a logical solution for producing potable water due to the shortage of freshwater. In this section, a novel deep seawater desalination system using Reverse Osmosis SystEm (Deep-ROSE) proposed method has been proposed for the seawater converted into freshwater and classified by using deep learning. Initially, the seawater is suctioned using an SWP motor for the desalination process. After that, the multimedia filter removes the salts and other impurities in the seawater. The output of filtered water can be classified using a deep belief network (DBN). It is classified as water without minerals, brine disposal, or seawater disposal. The reverse osmosis (RO) system removes salt from the DBN classifier’s output water. The RO system has four different systems: (a) a pretreatment system; (b) high-pressure pumps; (c) membrane systems; and (d) posttreatment. Finally, the RO system produces pure water, which is stored in the freshwater tank. To control and monitor the desalination site, it uses cloud-based portals for correlating and gathering metrics and data generated by IoT sensors. The experimental result shows it produces highly pure water at a low PV temperature.