Every Tree Nurturing System (TNS™) node can be monitored in real time. BGI integrates Matter's SensAI sensing so performance is measured continuously against a calibrated baseline – turning maintenance from a fixed schedule into a data-driven, predictive response.
Matter sensor units are installed in vertical inspection pipes positioned behind each ETI and EnviroKerb® High Flow Inlet. Each sensor watches what the kerb unit in front of it is taking in.
Each Matter unit is configured with a baseline intake curve calibrated to the commissioned intake of the specific node it monitors – whether an ETI with a clean ARI Water Filter, which protects the void structure from fines, or an EnviroKerb® unit.
Intake is measured against that baseline continuously, drawing on established principles of smart-infrastructure monitoring for predictive maintenance and optimisation.
If measured intake falls below the baseline curve, the system flags an inspection notification. The size of the deviation sets the maintenance response.
A single framework maps how far intake has dropped to the specific action required – so routine upkeep stays proportionate and most events are handled with a street sweeper. The full regime – redundancy, access and the budget case – is on the Maintenance page.
| Severity level | Maintenance action |
|---|---|
| Minor deviation | Vacuum street sweeping throughout the zone |
| Moderate deviation | Lifting and pressure washing an ETI tray |
| Significant deviation | Replacing an ETI tray or ARI Water Filter |
| Major deviation | Pressure washing the EnviroKerb® unit |
| Critical deviation | Lifting out and replacing the EnviroKerb® unit |
Zone-level consistency. With multiple Matter units across a zone, the system cross-checks them: if one unit flags while the others stay within baseline, the issue is likely localised; if several flag at once, it points to a zone-wide event needing broader maintenance.
Classification, MUSIC modelling and the relief-drain position sit on the compliance page: every element modelled as a standard in-built node, assessed on the standard pathway rather than a device approval.
Compliance & approvals →The Matter team is actively developing AI-enabled camera technology, co-located with the sensor units, to visually estimate the rate, spread width and depth of water in the kerb and channel. Cross-referencing camera estimates against sensor data would create a redundant verification layer and open advanced analytics – including correlations between rainfall intensity, urban heat and intake.
Status: a development pathway, not a shipping feature. Matter's current sensing hardware is SensAI and FloodScan.
Matter (watermatters.ai) – digital water-risk intelligence. BGI integrates Matter's SensAI radar-and-AI sensing into climate-resilient precinct design for real-time stormwater and flood monitoring.
Specification sheet, standard drawings, and the ARR-referenced hydrologic and hydraulic parameters – with the MUSIC node parameters if you are modelling. Sent by email.
The maintenance technical paper is requested separately, on the maintenance page. Or see how the system works.
