AI-Powered Anomaly Detection for Water Service Optimization

Keeping water systems running smoothly depends on quickly identifying issues like leaks, pressure drops, or equipment failures. This project develops an AI-driven solution that can detect these problems earlier and more accurately than traditional methods, helping utilities respond before small issues become major disruptions.

By analyzing both historical data and real-time information from sensors, the system learns patterns in how water systems normally operate and flags unusual behavior as it occurs. This approach enables more proactive and efficient management of water infrastructure, improving reliability and reducing downtime. Designed to be scalable, the project aims to provide a modern, data-driven solution that can strengthen water systems and support more sustainable operations.