Mapped to a shared offline runtime family and usable with a recording or compatible ESP32 CSI stream.
Intended capability
Evaluate the sensing evidence for “Seat-Level Occupant Classifier — Smart Restraint Input” in a stationary, controlled, ground-truthed vehicle study. This is not a vehicle, occupant, child, pet, or driver-safety system.
This describes the intended outcome. Readiness is shared-family mapped, evidence is class B, and a catalog mapping or recording is not proof of this outcome at a real site.
Solution blueprint
See the environment before installing it.
This exact kit is one of 191 first-class designs. It includes geometry, objects, nodes, wording, scenarios, installation, limitations, and catalog-bound readiness.
No rendered revision is available yet.
Bundled recording
A related Automotive scene
This is one recorded vertical scenario. It is not separate validation of every capability in the catalog.
01 The physics
Living occupants produce breathing-band micro-Doppler localized to their seat zone; adults vs children differ in scattering cross-section (body-size-dependent attenuation in RTI voxels) and breathing frequency (children breathe faster, 0.3-0.7Hz). Objects attenuate but produce zero physiological modulation.
02 Shared processing path
RTI differential imaging for per-seat attenuation voxels -> micro-Doppler physiological band per zone -> PCA feature fusion -> per-seat classifier with cross-vehicle z-score transfer.
This is a capability design path. Components may be shared with other catalog entries; it is not presented as a unique algorithm.
03 Validation plan
WiMANS for multi-person zone separation; own-hardware: 4-seat cabin matrix (adult/child/object/empty x seat position), 20 subjects, confusion-matrix target >90% per-seat accuracy.
04 Commercial hypothesis
One RF stack replaces four seat-mat sensors for occupant classification and belt reminders — sold to interior-systems Tier-1s chasing per-vehicle BOM reduction.