A frontier proposal with a validation plan, not an implemented detector.
Intended capability
Research whether the field could support this proposed outcome: Spatial map of crop water status across greenhouse benches, revealing drought-stressed or over-irrigated zones before visible wilting so irrigation can be zoned precisely.
This describes the intended outcome. Readiness is research concept, evidence is class C, 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 Agriculture scene
This is one recorded vertical scenario. It is not separate validation of every capability in the catalog.
01 The physics
Leaf and stem water content dominates vegetation permittivity (well-established in radar remote sensing); as canopy relative water content drops, eps_r and the volume-scattering signature fall measurably, changing reflected amplitude and effective path length through the canopy.
02 Shared processing path
CIR sparse recovery through the canopy layer -> RFF/NeRF reconstruction of a canopy eps_r map -> compartment Kalman tracking of each bench-zone's water-content proxy across the day -> CUSUM to flag zones drifting toward chronic stress
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: ESP32 grid above/below benches vs gravimetric leaf-water-content sampling and stomatal-conductance porometer across an irrigation cycle; use ESP32-wall/CIR benchmarks to validate through-medium eps_r recovery.
04 Commercial hypothesis
'CanopyScan' — zone-level irrigation intelligence for high-value greenhouse growers; cuts water use and prevents silent yield loss.