An Intelligent Approach for Adaptive Liquid Level Control System Using Machine Learning

Abstract

Abstract: Liquid level control is a mechanism that monitors, compares, and regulates the level of liquids within a process to a set value. Level measurement determines the position of the level relative to the top or bottom of the process fluid storage tank or silo. Level control and measurement are essential to assuring the safety and profitability of industrial processes. In this project, we are Implementing an intelligent mechanism using machine learning to predict the level of liquid in a reservoir based on the time and motor speed thus avoiding errors and keeping the process is ongoing. Keywords: Adaptive Liquid level control, Machine learning, Intelligent system, red