The evidence is proven or strong, but this capability still needs a capability-specific ESP32 or Rust runtime adapter.
Intended capability
Validate this target only after a capability-specific adapter and ground-truth study exist: A site-specific 'RF PLC': operators teach the system discrete plant states — valve open/closed, blast door position, truck present on the pad, hopper loaded/empty — by demonstrating each state once; the mesh then reports these states forever without any instrumentation on the asset.
This describes the intended outcome. Readiness is needs edge adapter, 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 Industrial scene
This is one recorded vertical scenario. It is not separate validation of every capability in the catalog.
01 The physics
Every large metal actuator position (valve handwheel + stem, damper blade, roller door) is a distinct scatterer configuration producing a repeatable static CIR fingerprint (delays + amplitudes). Controlled perturbation during teaching isolates exactly which CSI subspace that asset controls, making the axis robust to unrelated variation.
02 Shared processing path
Axis discovery via poke-and-observe (stage 7) driving supervised perturbations -> CIR fingerprint subspace per asset (stage 1) -> projection onto the learned axis with anomaly manifold guarding against off-axis confounders (stage 3) -> CUSUM for stuck-between-states conditions (stage 6).
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
Own-hardware: teach 5 assets in a workshop (metal door, large gate valve mockup, cart present/absent, damper, cabinet open/closed), then 30-day blind state-classification accuracy under normal foot traffic; SenseFi protocols for the fingerprint-classification methodology.
04 Commercial hypothesis
Retrofit state sensing for un-instrumentable legacy assets: 'show it once, monitor it forever' — sold to the brownfield digitalization lead drowning in quotes for limit switches and cabling.