From REACTIVE TO PROACTIVE
Urban Water ManagentÂ
The AQASight initiative was founded in 2025 recognizing that water networks are no longer just physical infrastructure.Â
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We bridge the gap between R&D and practical utility management by providing AI-powered, proactive monitoring systems. Our solutions are specifically engineered to support water infrastructure vision for sustainable water services, ensuring water networks remains resilient and efficient in the face of growing demand.
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WorkflowÂ
AQA-Sight offers a staged workflow from data ingestion to model selection, pilot validation, and live system integration, enabling progressive buy-in at each level while minimizing the implementation risk of AI solutions through controlled testing, measured deployment, and confidence-building before full operational adoption.
1. Data AcquisitionÂ
QA-Sight ingests heterogeneous utility data into a governed data lake, where SCADA, sensor, laboratory, hydraulic, asset, weather, historical, and event-log data are harmonized, quality-controlled, and reduced to the most decision-relevant parameters which then drive higher-order outputs including water quality indexing, risk scoring, forecasting, and anomaly detection.
2. Model ScreeningÂ
Model screening identifies the most reliable candidate models by testing them against historical data, controlled scenarios, and utility-relevant performance criteria. Models are assessed for accuracy, robustness, interpretability, stability, and resilience to noisy or incomplete data. This stage filters out weak or overfitted approaches early, ensuring that only the strongest models progress to pilot-scale validation.
3. Pilot TestingÂ
Selected models from the data acquisition and process development stage are tested in a controlled pilot-scale water distribution network to validate performance under realistic operating conditions. Using pilot measurements from smart sensors, pressure transducers, and water quality instruments, the platform compares predictions against observed system behaviour across routine and disturbance scenarios. This stage supports independent model validation, parameter refinement, and feature improvement, strengthening confidence in model reliability before full-scale deployment.
4. System integrationÂ
System integration is the stage where validated AQA-Sight models are deployed into the live utility environment and connected to SCADA and enterprise data systems. Through secure integration, standardized data flows, and API-based deployment, the platform delivers real-time predictions, alerts, dashboards, and decision support directly within existing operational workflows. This embeds predictive intelligence into day-to-day utility management while enabling continuous improvement, compliance support, and scalable digital integration.