Design and Implementation of Under Water Level Maintaining and Automatic Controlling System for Industries Using Machine Learning Algorithms

Industrial water consumption has been the target of conscious and reduction policies in order to avoid the waste of natural resources and financial resources. This is the biggest problem for governments. The notified draft rules said that even district magistrates have the power to grant NOC if the water withdrawal was 20–50 cubic meters per day depending on the type of area. This project describes the development of an android application for monitoring and automatic control using a flow sensor to measure water consumption for industries. The proposed system collects data from a flowmeter equipped with a borehole and sends this information via IOT (internet of things) to the server (municipality) and consumers, access records in the cloud at any time through platforms such as Thing Speak, issuing automatic flow readings water. This method enables live monitoring of water consumption and also provides identification of consumption patterns. Idea of using an ML model to gather and transmit real-time data to a licenced central command center regarding the water levels of various water bodies that supply the dams that evaluates the information gathered and chooses the appropriate course of action. The decision of whether to release the water can subsequently be made in accordance with the ML Model's recommendation. Where it reproduced the failure of the real environment. Wasting water is the biggest problem in households in developing countries like India,