Sparse Sentinel
This form collects the information we need to calibrate Sentinel for your air quality environment. Sentinel learns normal behaviour across your network — pollutant, meteorology, context, and quality signals — and detects deviation early, before conventional thresholds and indices react.
Sensor-agnostic. It works with any combination of reference stations, roadside and background monitors, indoor air quality sensors, meteorological sensors, and contextual feeds such as traffic or airport activity. If your monitoring system produces data, Sentinel can learn from it.
No new hardware. Sentinel works on the data your existing monitors, SCADA/telemetry, and air-quality platforms already produce. Upload 48+ hours of baseline data and we typically return an initial calibration response within 24 hours.
Every site you monitor with Sentinel builds a structured record of air-quality behaviour — normal patterns, episode signatures, degradation trajectories, and state-specific drift. Over time, this becomes a valuable intelligence asset. Cities, infrastructure operators, and regulators need exactly this kind of real-world performance data but can rarely obtain it from fragmented monitoring feeds. Your monitored estate isn’t a cost — it’s an investment that grows in value with every monitoring day.