Aqua Trace Intelligent Water Quality Monitoring and Management System Using Machine Learning for Smart Water Safety

Access to safe drinking water is essential for public health, yet conventional water quality monitoring systems are often slow, manual, and lack real-time accessibility. This paper presents Aqua Trace, an intelligent water quality monitoring and management platform that integrates mobile and web technologies with machine learning for water classification, contamination mapping, lab-oratory report delivery, and predictive filter recommendation. The system uses Random Forest for water quality classification, Linear Regression for filter prediction, and K-Nearest Neighbour interpolation for contamination visualization. Developed using Django REST Framework, Flutter, MySQL, and Google Maps API, Aqua Trace improves efficiency, transparency, and public accessibility in smart water management. Experimental results confirm faster reporting, accurate contamination detection, and enhanced decision-making for water safety.