Intelligent water quality and level detection system using hybrid classifier

Abstract The use of a water storage system to store and distribute water is a widely adopted approach in numerous households. The issue of assessing the quality of water in the overhead tank prior to its distribution to households remains unresolved. The advanced method of monitoring and managing water resources is through the implementation of the intelligent system for detecting water quality and level. In this work, the system employs hybrid classifiers with a combination of three machine learning algorithms, to detect water quality parameters such as pH level, turbidity, total dissolved solids, as well as water level in real-time. The system provides accurate and reliable information to water treatment facilities and environmental agencies for effective decision making, ensuring the availability of safe and clean water for the community. The system has a feature of real time monitoring of water quality and level through Internet of Things.