SCADA And IOT-Enabled Smart Water Metering: A Systematic Review of Resilient Supply Monitoring

Abstract

This study has examined the contribution of SCADA and IoT-enabled smart water metering to resilient supply monitoring in digitally monitored water utility, cloud-enabled infrastructure, and enterprise-level smart water management cases. The main problem addressed in this research has been the continuing inability of many conventional and fragmented water monitoring systems to detect leakage, pressure instability, abnormal consumption, data delays, and operational faults in a timely and integrated manner. The purpose of the study has been to evaluate whether SCADA-based monitoring capability, IoT-enabled smart metering capability, real-time data quality, predictive analytics and anomaly detection, and SCADA-IoT integration significantly improve resilient supply monitoring. The study has followed a quantitative, cross-sectional, case-based research design and has collected data from 214 valid respondents, including water utility operations staff, SCADA operators and engineers, IoT and smart meter technicians, water distribution engineers, data analysts, monitoring specialists, and municipal water authority staff. Data have been analyzed through descriptive statistics, reliability analysis, correlation analysis, multiple regression modeling, hypothesis testing, leakage-pressure-abnormal consumption detection assessment, and a Resilience Readiness Index. The findings have shown strong agreement across the major constructs, with SCADA-IoT integration recording the highest mean score of 4.16, followed by resilient supply monitoring at 4.11, SCADA-based monitoring capability at 4.08, IoT-enabled smart metering capability at 4.02, real-time data quality at 3.96, and predictive analytics and anomaly detection at 3.89. Reliability has been confirmed through Cronbach’s alpha values ranging from 0.82 to 0.90, with overall scale reliability of 0.92. Correlation results have shown significant positive relationships with resilient supply monitoring, led by SCADA-IoT integration at r = 0.69 and predictive analytics at r = 0.63. The regression model has been statistically significant, F(5, 208) = 62.47, p < 0.001, explaining 59.4% of the variance in resilient supply monitoring. SCADA-IoT integration has been the strongest predictor, β = 0.31, followed by predictive analytics, β = 0.24, SCADA capability, β = 0.21, IoT metering, β = 0.18, and real-time data quality, β = 0.15. The Resilience Readiness Index has scored 4.02 out of 5.00, confirming high readiness. The study implies that integrated SCADA-IoT systems can strengthen early warning, leakage visibility, pressure monitoring, abnormal-consumption detection, and data-driven response in resilient water supply operations.