AI-Driven Predictive Analytics
AWS-hosted Machine Learning turns big data into actionable intelligence. Predictive Demand Forecasting anticipates water needs before shortages occur. Smart Leak Detection pinpoints anomalies, reducing Non-Revenue Water (NRW) losses. Risk Mitigation AI provides early warnings for drought and water quality deterioration.
What This Layer Does
The AI & Analytics layer transforms the continuous stream of IoT sensor data into operational intelligence. Using AWS SageMaker-hosted ML models, IWMS learns the baseline behavior of every pipeline, valve, and sensor — then detects deviations indicating leaks, equipment failure, or supply imbalances. All models are continuously retrained on new data, improving accuracy over time.
Features & Capabilities
NRW Leak Detection
ML models analyze flow imbalances between supply meters and consumer meters across each DMA zone. Anomalous patterns pinpoint leak locations to within 100m.
Demand Forecasting
LSTM time-series models trained on 3+ years of data predict hourly water demand per zone up to 72 hours ahead.
Pressure Anomaly AI
Regression models detect pressure drops and surges that precede pipe bursts or pump failures. Reduces emergency shut-downs by up to 60%.
Water Quality AI
Multivariate analysis detects quality deterioration events 2–6 hours before reaching consumer taps — enabling pre-emptive source switching.
Consumption Analytics
Per-zone consumption dashboards automatically flag high-consumption outliers indicating illegal connections or end-consumer leaks.
Drought Risk Index
Reservoir storage, borewell level, and rainfall data combined into a Drought Risk Index with automated escalation protocols.
Technical Specifications
Use Cases
- NRW reduction programs for municipal utilities
- Demand-responsive pump scheduling
- Water quality deterioration early warning
- Seasonal supply planning for peak demand
- Illegal connection detection via consumption outliers
- Drought preparedness and reservoir management