examples/research-sota/04-rssi/README.md
RSSI is the simplest CSI summary (one number per packet). These scripts quantify what's recoverable from RSSI alone vs full CSI.
| Script | Thread | Headline |
|---|---|---|
r8_rssi_only_count.py | R8 | RSSI-only person count: 59.1% accuracy = 94.82% of full-CSI v0.0.2 with a tiny 656-parameter MLP. RSSI keeps 95% of counting capacity. |
r9_rssi_fingerprint_knn.py | R9 | Cosine-NN on RSSI fingerprints: 2.18× lift over chance (MODERATE). Surfaces counting-vs-localization asymmetry: RSSI is great for count, weaker for per-location ID. |
R8 + R9 together demonstrate that RSSI:
This means RSSI-only deployments (the cheap path) are viable for occupancy / count but inadequate for per-occupant features (vitals, identity, pose).
Per ADR-113 placement matrix, RSSI-only is appropriate for:
cog-presence (binary occupancy)cog-person-count (occupant count)NOT appropriate for:
cog-vital-signs (needs CSI per-subcarrier shape)cog-pose-estimation (needs CSI multistatic geometry)cog-quantum-vitals (ADR-114, needs CSI fusion with NV)docs/research/sota-2026-05-22/R8-*.md, R9-*.md01-physics-floor/ (uses Fresnel forward model insight)