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Advancement of Smart Water Meter Asset Infrastructure: A Review of Maintenance and Management Strategies
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DOI：10.1002/wat2.70078.png)
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Abstract
En 中文
Smart water meters (SWMs) are key to modern residential, industrial and agricultural water supply and management systems. enabling accurate real-time data, timely leak detection, reduced water loss, and improved billing accuracy. High system performance enables better forecasting and optimization, especially in areas with aging infrastructure or growing populations, while resilience against cyber threats ensures safety and security. However, maintaining and managing these assets is challenging, due to data reliability and analytical issues, communication failures, and increasing system complexity This review synthesizes current literature on key challenges, recent innovations, and best practices for efficiently managing and maintaining smart water meter (SWM) assets. We highlight the potential of predictive and condition-based maintenance supported by asset management, the plan-do-check-act (PDCA) approach alongside tool such as root cause analysis (RCA), reliability-centered maintenance (RCM), conditioning monitoring or failure modes and effects analysis (FMEA)) in accordance with ISO 55002 to enhance reliability and operational efficiency. We advocate for the adoption of machine learning and internet of things (IoT)-enabled monitoring to facilitate a shift from reactive to predictive maintenance, which remains underexplored in traditional water management literature. The findings offer valuable insights for water utilities aiming to advance smart water infrastructure through strategic asset management, data frameworks, and capability development.
Keywords:
asset lifecycle
data integrity
predictive maintenance
retrofitted sensors
smart meters
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