WCW26

Advanced Metering Infrastructure (AMI) is rapidly evolving from a billing-focused technology into a foundational data source for utility-wide operational intelligence. As utilities expand metering programs and pursue digital transformation initiatives, the next generation of AMI—AMI 2.0—enables organizations to leverage high-resolution consumption data to address persistent challenges such as non-revenue water, leak detection, and system inflow and infiltration (I&I) awareness.


By integrating AMI data with operational, hydraulic, and environmental datasets, Utilities can generate actionable insights across both customer and system levels. By integrating AMI data with operational, hydraulic, and environmental datasets, Utilities can generate actionable insights across both customer and system levels. Influenced by implementation work with the City of Immokalee, Florida, this approach demonstrates how continuous meter analytics can identify abnormal flow patterns, persistent consumption, and nighttime flow conditions that indicate leaks or operational inefficiencies.  When aggregated and contextualized, meter data also provides valuable system-level indicators that help utilities better understand flow anomalies and potential I&I impacts, enabling more targeted investigation and response.


AMI 2.0 shifts the role of smart meters from passive measurement devices ('cash registers') to active components of a utility’s digital ecosystem. By combining advanced analytics, data integration, and scalable enterprise architecture, utilities can move beyond reactive workflows toward proactive operations that improve water accountability, optimize field resources, and strengthen infrastructure planning.


As water metering adoption accelerates across regions such as Western Canada, utilities have an opportunity to design programs that maximize long-term value from the outset. Leveraging AMI data for both leak detection and broader system intelligence supports improved resiliency, operational efficiency, and measurable return on investment while establishing a scalable foundation for future analytics and AI-driven applications.