Applications

Common denominator

A small drone creates the same problem for a forward site and for a regional airport: single sensors are noisy, and an operator flooded with unfused alerts cannot act on any of them with confidence. The fusion approach is the same in every domain, which is what makes this a dual-use software layer. So is the stage: everything below is where this would apply, not where it is deployed.

Defence and national security

Layered early warning across sites and borders, where wide-area coverage from dedicated hardware alone is hard to afford. The fusion layer allows coverage to be assembled from heterogeneous sensors and merged into one picture.

Airports and airfields

Separating registered ADS-B and Remote ID traffic from an unregistered contact near an approach path. Context feeds are key here — without them it is not possible to tell legal traffic from an unknown contact.

Energy, water and industrial sites

Long perimeters and dispersed assets, where one radar per site does not scale. The fusion layer can work with events from existing sensors without needing new dedicated hardware at each site.

Ports and offshore energy platforms

Large open areas with constant legitimate movement, so the false-alarm rate decides whether an alert is trusted at all. Offshore, a thin link to shore is why the layer runs on site. Maritime sensing is on the roadmap, not built.

Stadiums and public events

Temporary coverage at short notice, assembled from sensors already on site. The fusion layer does not require new hardware to be installed for each event.

Prisons and secure facilities

Small, low, short-duration flights that any single sensor class routinely misses. This is where the value of fusion shows — a combination of sources catches what a single sensor does not.

Convoys and mobile units

Moving formations where static perimeter coverage is not enough. Acoustic vector detection can provide directional information for the whole formation from one or a few nodes — but this is an area that requires real sensors and pilot measurement, not part of the running demo.

Urban environment and NLOS

Dense built-up areas with a lack of line of sight and a strong noise floor. Acoustic vector detection is relevant here because it does not require line of sight and can separate a drone signature from other sound sources. Real urban deployment requires pilot measurement — this is an area where it would apply.

Gunfire and artillery detection

Acoustic vector detection is also relevant for detecting and locating small-arms fire, artillery and other sources. The same fusion logic can be applied here. This is an area with its own regulatory requirements and it is not part of the running demo.

Scope note

All areas above are places where the fusion layer would apply. None of them is currently deployed. Real deployment requires a partner, real sensors and pilot measurement. The goal of a pilot is to measure the real false-alarm rate — the number that actually decides whether an alert is trusted.