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PR #744 moved the files into 9 thematic folders via git mv but missed the READMEs due to a working-directory issue with git add. This PR adds the actual READMEs: - examples/research-sota/README.md (main overview) - examples/research-sota/01-physics-floor/README.md - examples/research-sota/02-placement/README.md - examples/research-sota/03-spatial-intelligence/README.md - examples/research-sota/04-rssi/README.md - examples/research-sota/05-cross-room-reid/README.md - examples/research-sota/06-structure-detection/README.md - examples/research-sota/07-negative-results/README.md - examples/research-sota/08-verticals/README.md - examples/research-sota/09-quantum-fusion/README.md Each sub-README documents: - Scripts + headlines table - Why this folder bounds/composes with others - Sample output / honest scope - Cross-references to related loop notes + ADRs Main README covers: - Folder map with thread numbers - Cross-folder dependency graph - 8-entry headline findings table - Reading order for newcomers (4 scripts in suggested order) - Honest scope (synthetic-physics caveats)
04 — RSSI-only sensing
RSSI is the simplest CSI summary (one number per packet). These scripts quantify what's recoverable from RSSI alone vs full CSI.
Scripts
| 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. |
The counting-vs-localization asymmetry
R8 + R9 together demonstrate that RSSI:
- Retains 95% of person-count capacity (R8)
- Retains only ~30% of localization capacity (R9)
This means RSSI-only deployments (the cheap path) are viable for occupancy / count but inadequate for per-occupant features (vitals, identity, pose).
When to use RSSI-only
Per ADR-113 placement matrix, RSSI-only is appropriate for:
cog-presence(binary occupancy)cog-person-count(occupant count)- Very cost-sensitive deployments (chicken-scale R19 livestock, for instance)
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)
See also
- Research notes:
docs/research/sota-2026-05-22/R8-*.md,R9-*.md - Composes with:
01-physics-floor/(uses Fresnel forward model insight)