IoT-Enabled Smart Water Quality Monitoring And ML-Based Potability Prediction System

The “Water Potability Prediction and Purification Recommendation System” now forms a key topic in regards to the fundamental necessity for the health of humans, agriculture, and industrial clean drinking water from pollution. Unsafe water is a condition for millions and causes hundreds of diseases. With an increasing rate of pollution day after day, it is vital for public health and environmental conservation that monitoring and maintenance be implemented for water quality. Traditional water quality analysis is time-consuming, expensive, and not easily scalable. However, due to advances in IoT and machine learning technologies, focus has started to shift towards automation because of advancements in real-time analysis capabilities. The nature of development, however, remains expensive and complex. Hence, automated systems that are cheap and provided for continuously monitoring and predicting water purity cease to exist. This project is a smart and integrated system which is going to be the IoTs blended with machines dealing with the parameters of water quality monitoring, potability prediction, and purification recommendation. The sensed data from the sensors will be processed through the Arduino microcontroller using machine learning algorithms to give accurate predictions and recommendation outputs. This will make the system provide real-time prediction of water potability along with recommendations for purification methods through a user-friendly interface by integrating an IoT-based architecture with an ML-powered backend. Therefore, this project is expected to bridge the gap between traditional methods of testing water and modern automated solutions in areas that are resource-limited towards improving access to clean water.