Automated Leak Detection

Automated leak detection is not just about triggering an alert. The real operational problem is speed and certainty: identifying abnormal water behaviour early, narrowing the likely source region fast, and giving responders enough context to act without exploratory disruption. When teams lack localisation and confidence, leaks become expensive, slow to resolve, and hard to explain to stakeholders or insurers.

We design leak detection as an operational workflow, not a sensor gimmick. That means continuous sensing, stable signal processing, and diagnostics that can distinguish genuine anomalies from normal demand variation. In real buildings, usage patterns change constantly. The goal is repeatable detection that stays calm by default and only escalates when the evidence supports action.

Detection is typically delivered using a blended topology that matches the environment: flow and consumption baselining for long-run anomalies, pressure transient analysis for burst-like signatures, and point sensors in high-risk zones where direct confirmation is valuable. The system correlates multiple inputs, assigns confidence, and surfaces a clear story of what changed and when.

Localisation is where most systems fail. Knowing that something is wrong is not enough. We focus on reverse-trace diagnostics and zone-aware correlation so responders can narrow down the probable origin area quickly. This reduces exploratory work, shortens the damage window, and keeps disruption to occupants or operations minimal.

Evidence matters. Every material event should carry timestamps, a confidence signal, and supporting telemetry so teams can audit decisions and defend actions. That is important for facilities governance, claims workflows, and post-incident review. Good evidence also drives learning: thresholds improve, placement improves, and outcomes become more consistent across portfolios.

Rollout is practical. We start with constraints and known incident patterns, propose a sensing topology, validate cadence and alert semantics, then run a short pilot with acceptance criteria. Once proven, scaling becomes systematic: prioritise high-risk zones, tune false-alarm controls, and standardise reporting so leak detection becomes a repeatable operational capability across sites.

Automated leak detection becomes most valuable when it is treated as part of a wider operational control loop, not a standalone alerting tool. In mature deployments, detection events feed directly into escalation workflows, maintenance response, and, where appropriate, mitigation actions. This ensures that abnormal behaviour does not just generate noise, but results in timely, accountable intervention.

For organisations managing multiple sites, automated leak detection also supports governance. Standardised alert semantics, evidence logs, and response thresholds make it easier to demonstrate control to insurers, auditors, and internal stakeholders. Over time, this consistency reduces friction, improves trust in the system, and enables confident scaling across portfolios without increasing operational overhead.