## Security audit (`mqtt::security`)
New module enforcing the ADR-115 §3.9 / §7 wire-level invariants as
pure functions, callable from both the publisher hot path and the
unit-test suite:
- **Topic safety** — reject `+`, `#`, `\0`, `/` in segment-level
identifiers (node_id, client_id, zone tag). Prevents a malicious
upstream payload from injecting MQTT wildcards that would corrupt
subscription semantics.
- **Path safety** — reject NUL / newline in TLS cert / CA paths.
- **Payload-size cap** — 32 KB hard limit per publish, well below
broker defaults (most brokers cap at 256 KB). Lets the publisher
drop oversized payloads with a WARN instead of crashing.
- **Credential hygiene** — `password_via_env_only` is a canary: if
the CLI ever grows an inline `--mqtt-password` flag, this test
fails on purpose. Today we only accept `--mqtt-password-env <VAR>`.
- **STRICT_TLS upgrade** — `RUVIEW_MQTT_STRICT_TLS=1` promotes the
`PlaintextOnPublicHost` advisory from `MqttConfig::validate` to
fatal. This is the planned v0.8.0 default per ADR §9.5.
- **Discovery prefix sanity** — rejects non-alphanumeric prefixes
outside [_-/], so a malformed `--mqtt-prefix` can't escape the HA
topic namespace.
15 unit tests (mqtt::security) covering every invariant + 1
properly-`#[ignore]`d test for the env-mutating STRICT_TLS path.
## Criterion benchmarks (`benches/mqtt_throughput.rs`)
Micro-benchmarks for the MQTT + semantic hot paths:
- discovery payload generation (presence / heart_rate / fall event)
- state encoders (boolean / numeric / event)
- rate-limiter `allow()` decisions (first sample + within-gap)
- privacy `decide()` (strip HR vs keep presence)
- full bus tick across all 10 semantic primitives
Bench targets (laptop-class release build):
- discovery payload: <5 µs state encode: <2 µs
- rate limit: <100 ns privacy decide: <50 ns
- bus tick (10 prim): <10 µs
Run with `cargo bench -p wifi-densepose-sensing-server --bench
mqtt_throughput --features mqtt`. Numbers will be captured into the
witness bundle in P10.
`criterion` 0.5 added as dev-dep. `[[bench]] required-features = ["mqtt"]`
so default `cargo bench --workspace` doesn't try to build it without
rumqttc.
Lib test count: **372 passed** (357 → 372, +15 security tests).
Refs #776.
Co-Authored-By: claude-flow <ruv@ruv.net>
Adds three integration tests (`v2/crates/wifi-densepose-sensing-server/
tests/mqtt_integration.rs`) that prove the publisher works against a
real broker, gated behind `--features mqtt` + `RUVIEW_RUN_INTEGRATION=1`:
1. `discovery_topics_appear_on_broker` — spawn the publisher, subscribe
`homeassistant/#` with rumqttc, drain for 6s, assert that presence/
heart_rate/fall discovery config topics all landed with the exact
JSON shape (device_class, payload_on/off, unique_id namespace).
2. `privacy_mode_suppresses_biometric_discovery` — with
`privacy_mode=true`, biometric topics (heart_rate, breathing_rate,
pose) must NEVER appear on the wire. Semantic primitives
(someone_sleeping, etc) MUST still appear — they're inferred
states, not biometric values, per ADR-115 §3.12.3.
3. `state_messages_published_on_snapshot_broadcast` — push a
VitalsSnapshot through the broadcast channel, assert ON/OFF state
messages reach the broker.
Plus `.github/workflows/mqtt-integration.yml` — spins up Mosquitto
2.0.18 as a GH Actions service container, waits for it via
`mosquitto_pub` health probe, runs both the lib unit suite under
`--features mqtt` and the integration suite. Dumps broker logs on
failure for debugging.
Tests are SKIPPED locally unless `RUVIEW_RUN_INTEGRATION=1` is set —
default `cargo test --workspace` stays fast for developers.
Fixed an unused-import warning in `semantic::bus` (gated `Reason`
behind `#[cfg(test)]`).
Lib test count now: 357 passed across the crate (cli 6 + mqtt 45 +
semantic 66 + everything else 240 — all green under
`cargo test --no-default-features --lib`).
Refs #776.
Co-Authored-By: claude-flow <ruv@ruv.net>
Two new files under docs/integrations/:
- `home-assistant.md` (~340 lines) — operator guide for both protocols:
* Quick start (Docker + cargo)
* Entity reference (11 raw + 10 semantic, Matter device-type mapping)
* Complete CLI matrix (every --mqtt-*, --matter-*, --semantic-* flag)
* Zone-tag YAML format + threshold-override format
* Privacy mode contract (HR/BR/pose stripped; semantic primitives preserved)
* Three starter HA Blueprints per §9.4 maintainer ACK:
1. Notify on possible distress
2. Dim hallway when someone sleeping
3. Wake-up routine on bed exit
* Lovelace dashboard examples (single-room + multi-node grid)
* Advanced brokers (EMQX, VerneMQ, HiveMQ Edge)
* Troubleshooting recipe matrix
- `semantic-primitives-metrics.md` (~120 lines) — per-primitive
precision/recall reference + methodology for reproducing numbers
+ failure-mode catalogue (v1 → v2 deltas) + threshold-tuning notes.
Numbers grounded in the 1,077-sample ADR-079 paired-capture held-out
subset. Open-set caveats explicitly listed.
README.md Documentation section gets two new rows pointing at the
guides plus a "Works with Home Assistant" + "Works with Matter"
positioning line — matches the ambient-intelligence-platform pitch
[[project-ruview-positioning]].
User guide untouched in this commit; will be updated in P6 once the
release lands with concrete version numbers.
Refs #776.
Co-Authored-By: claude-flow <ruv@ruv.net>
Lands the remaining six §3.12 v1 primitives:
- `distress` (PossibleDistress) — EWMA baseline HR + 1.5× multiplier
+ agitated motion + no-fall + 60 s dwell → ON. Refractory 5 min
after exit. Baseline only updates when NOT active AND NOT in
candidate-distress state (low motion, HR near baseline) so a
sustained elevated HR doesn't drift the baseline up before the
dwell completes — without this guard the test would never fire.
- `elderly_anomaly` (ElderlyInactivityAnomaly) — current idle stretch
> 2× longest-observed-idle baseline. Baseline floor at 30 min so
the first day doesn't fire spuriously. 24 h refractory per resident.
- `meeting` (MeetingInProgress) — n_persons ≥ 2 + low-amplitude motion
(1–20%) + 10 min dwell → ON. 2 min exit dwell on count drop.
- `fall_risk` (FallRiskElevated) — 0–100 continuous score from
near-fall count in trailing 24 h + recent motion variance. Emits
Scalar every tick; emits Event on upward threshold crossing
(default 70).
- `bed_exit` (BedExit) — edge-triggered event: was in bed_zone, now
not, between 22:00 and 06:00 local (wrap-around window honoured).
- `multi_room` (MultiRoomTransition) — edge-triggered event: zone
exit + different zone enter within 10 s gap. Reason payload carries
from/to zone tags so HA automations can route paths.
Bus wired to dispatch all 10 primitives; `SemanticKind` enum expanded
to match. `tick()` returns up to 10 events per snapshot.
32 new tests (66 semantic + 45 mqtt + 6 cli = **117 total**):
- distress (7): does-not-fire-with-normal-HR, fires-on-sustained-
elevated-HR-with-motion, does-not-fire-during-fall, exits-when-
motion-calms-and-HR-normalises, refractory-blocks-immediate-refire,
refire-allowed-after-refractory, baseline-does-not-track-during-
active.
- elderly_anomaly (5): fires-when-idle-exceeds-2x-baseline, does-not-
fire-before-threshold, motion-clears-active-state, baseline-grows-
to-observed-max, refractory-prevents-repeat-alerts.
- meeting (4): fires-after-dwell-with-2+, does-not-fire-with-1-
person, does-not-fire-with-high-motion, exits-after-2-min-of-low-
count.
- fall_risk (5): warmup-blocks, emits-scalar-when-active, score-
grows-with-falls, emits-event-when-crossing-threshold, fall-
history-evicts-after-24h.
- bed_exit (6): fires-on-bed-to-non-bed-overnight, does-not-fire-
during-day, does-not-fire-without-prior-in-bed, warmup-blocks,
does-not-fire-when-bed-zones-unconfigured, fires-just-after-
midnight-window-start.
- multi_room (5): fires-when-zone-changes-quickly, does-not-fire-
after-long-gap, does-not-fire-on-same-zone-re-entry, warmup-blocks,
handles-simultaneous-zone-swap.
ADR-115 §3.12 inference layer now complete. Each primitive has
warmup, hysteresis, explainability tags, configurable thresholds.
Adding a v2 primitive is one file + one bus entry.
Refs #776.
Co-Authored-By: claude-flow <ruv@ruv.net>
ADR-115 §3.12 keystone. Raw signals are not the product — customers want
first-class entities like `binary_sensor.bedroom_someone_sleeping`, not a
Node-RED flow that thresholds breathing rate at night. This commit lands
the inference layer that turns the broadcast channel into 10 v1 semantic
primitives, starting with the 4 highest-leverage ones.
Modules:
- `semantic::common` — `RawSnapshot` projection, `PrimitiveState`,
`PrimitiveConfig` (thresholds matching the v1
catalog in ADR §3.12), `in_window` for time-gated
primitives, `Reason` explainability struct.
- `semantic::sleeping` — SomeoneSleeping FSM: presence + motion<5%
+ BR ∈ [8,20] bpm + 5min dwell. Exit on
presence-drop (immediate) or motion>15%
for 30s.
- `semantic::room_active` — motion >10% in 30s window → ON. Exit on
presence-drop or 10min idle.
- `semantic::bathroom` — presence + zone tagged as bathroom. Safe
in privacy mode (no biometrics in the
derivation).
- `semantic::no_movement` — presence + motion<1% for 30min → ON.
Safety-check primitive for aging-in-place.
- `semantic::bus` — single dispatch that runs all primitives
on each `RawSnapshot`, returns a list of
`SemanticEvent`s for MQTT+Matter publish.
Every primitive has:
- Warmup suppression (60s default, §3.12.4)
- Hysteresis (enter + exit thresholds different)
- Explainability via `Reason::new(&["motion<5%", "br=12bpm", ...])`
- Configurable thresholds via `PrimitiveConfig`
Test coverage (34 tests, all passing under `--no-default-features`):
- common: in_window simple + wrap-around midnight, default thresholds
match ADR catalog, Reason struct.
- sleeping (7 tests): warmup blocks, fires after dwell, no-fire on high
motion, no-fire on BR out of range, exits on presence-drop immediately,
exits on sustained motion only after 30s, brief blip does not exit.
- room_active (6 tests): warmup, fires on high+presence, no-fire without
presence, no-fire below threshold, exits on presence-drop, exits on
extended idle.
- bathroom (5 tests): fires on zone match, ignores other zones, requires
presence, warmup blocks, emits OFF on zone exit.
- no_movement (4 tests): fires after dwell, no-fire with motion, brief
motion resets timer, exits on motion.
- bus (6 tests): empty during warmup, emits room_active, emits bathroom,
multiple simultaneous primitives, event carries node_id+ts, reason
populated for HA debug.
Total cargo test count now:
cli: 6 + mqtt: 45 + semantic: 34 = 85 tests passing
P4.5b (next iteration) lands the remaining 6 primitives: distress
(HR multiple over baseline), elderly_anomaly (long-window inactivity),
meeting (multi-person dwell), fall_risk (gait instability score),
bed_exit (sleeping → presence-out between 22:00-06:00),
multi_room (track_id continuous across zones).
Refs #776.
Co-Authored-By: claude-flow <ruv@ruv.net>
Adds `mqtt` and `matter` Cargo features (default off) plus 20+ new CLI
flags wired through cli.rs per ADR-115 §3.8 / §3.10 / §3.11 / §3.12:
- MQTT (HA-DISCO): --mqtt, --mqtt-host/--mqtt-port/--mqtt-username/
--mqtt-password-env/--mqtt-client-id/--mqtt-prefix, TLS controls
(--mqtt-tls/--mqtt-ca-file/--mqtt-client-cert/--mqtt-client-key),
rate controls (--mqtt-refresh-secs, --mqtt-rate-{vitals,motion,count,
rssi,pose}, --mqtt-publish-pose).
- Privacy (ADR-106): --privacy-mode strips HR/BR/pose pre-publish.
- Matter (HA-FABRIC): --matter, --matter-setup-file, --matter-reset,
--matter-vendor-id (dev VID 0xFFF1 per §9.9), --matter-product-id.
- Semantic (HA-MIND): --semantic (default ON), thresholds/zones files,
--semantic-baseline-window-days, --no-semantic <PRIMITIVE> repeatable.
rumqttc 0.24 added as optional dep with rustls (Windows-friendly parity
with ureq in this crate). matter-rs deferred to P7 spike per §9.10.
6 unit tests cover defaults, compound flag composition, and repeatable
--no-semantic. Tests pass:
cargo test -p wifi-densepose-sensing-server --no-default-features cli::tests
6 passed; 0 failed.
Branch coordination: this work is on feat/adr-115-ha-mqtt-matter off
main, parallel to ADR-110 work on adr-110-esp32c6 (no file overlap).
Refs #776 (ADR-115 implementation tracking issue).
Co-Authored-By: claude-flow <ruv@ruv.net>
ADR-115 lands the dual-protocol HA integration design:
- MQTT auto-discovery (HA-DISCO) carrying full RuView telemetry
- Matter Bridge (HA-FABRIC) carrying the standardised subset across
Apple Home / Google Home / Alexa / SmartThings / HA
- Semantic Automation Primitives (HA-MIND) — 10 v1 inferred states
(someone-sleeping, possible-distress, room-active, elderly-anomaly,
meeting-in-progress, bathroom-occupied, fall-risk-elevated, bed-exit,
no-movement, multi-room-transition) that turn raw signals into HA
entities, Matter events, and Apple Home scene triggers — the inference
layer that moves RuView from "RF sensing" to "ambient intelligence
infrastructure". All 13 §9 open questions ACK'd by maintainer.
P1 (this commit) — `mqtt` and `matter` Cargo features (default off) +
20+ new CLI flags wired through cli.rs:
- --mqtt / --mqtt-host / --mqtt-port / --mqtt-username /
--mqtt-password-env / --mqtt-client-id / --mqtt-prefix /
--mqtt-tls / --mqtt-ca-file / --mqtt-client-cert / --mqtt-client-key
- --mqtt-refresh-secs / --mqtt-rate-{vitals,motion,count,rssi,pose} /
--mqtt-publish-pose
- --privacy-mode (ADR-106 primitive-isolation contract)
- --matter / --matter-setup-file / --matter-reset /
--matter-vendor-id (dev VID 0xFFF1 per §9.9) / --matter-product-id
- --semantic (default ON) / --semantic-thresholds-file /
--semantic-zones-file / --semantic-baseline-window-days /
--no-semantic <PRIMITIVE> (repeatable)
6 unit tests cover: defaults safe (mqtt off, vid=0xFFF1, semantic on),
compound flag composition, repeatable --no-semantic. All pass:
cargo test -p wifi-densepose-sensing-server --no-default-features cli::tests
test result: ok. 6 passed; 0 failed.
rumqttc 0.24 added as optional dep (gated behind `mqtt` feature) with
rustls instead of openssl for Windows parity with the rest of the
workspace. matter-rs intentionally absent until P7 spike validates the
SDK choice (§9.10).
Coordinates with ADR-110 work (different branch, different files).
This branch is feat/adr-115-ha-mqtt-matter off main. ADR-110 work
continues on adr-110-esp32c6.
Co-Authored-By: claude-flow <ruv@ruv.net>
* fix(ui): unbreak viz.html — OrbitControls importmap, WS URL, toast NPE (#760)
Three independent bugs were stacking to make ui/viz.html unusable from `main`:
1. Three.js r160 removed `examples/js/OrbitControls.js`, so the script-tag
load 404'd and `new THREE.OrbitControls(...)` threw. Switch to an
importmap that pulls the ES module build, then re-expose
`window.THREE` and `THREE.OrbitControls` so the existing component
modules (scene.js, body-model.js, …) keep working without a wider
refactor.
2. The WebSocket client was hardcoded to `ws://localhost:8000/ws/pose`,
but the sensing-server listens on `--ws-port` (8765 default, 3001 in
the Docker image) at `/ws/sensing`. Reuse the existing
`buildSensingWsUrl()` helper from `sensing.service.js` so port
pairings are handled centrally, and add a `?ws=…` query-string
override for non-standard setups. The websocket-client.js default is
also updated to derive from `window.location` instead of the dead
`:8000/ws/pose` literal.
3. `ToastManager.show()` called `this.container.appendChild(...)` even
when `init()` had never been called, throwing a TypeError that
killed the rest of page initialization. Auto-init the container
lazily on first show (patch from issue reporter).
Closes#760.
Co-Authored-By: claude-flow <ruv@ruv.net>
* fix(ui): single module script + mutable THREE — OrbitControls validated
Browser validation against the previous commit caught two stacked issues:
1. `import * as THREE from 'three'` returns a frozen Module Namespace
Object — assignment `THREE.OrbitControls = OrbitControls` silently
no-ops, so the global never gets the OrbitControls reference.
2. Two separate `<script type="module">` blocks (one installing the
THREE global, one consuming it via Scene) are independently
async-resolved. The second can finish dependency loading first and
call `new THREE.OrbitControls(...)` before the first script has run.
Fixed by spreading the namespace into a plain mutable object and merging
all initialization into a single module script with `await import()` for
component modules. Order is now strictly: import THREE → install
window.THREE → import components → run init().
Validated via agent-browser: page logs `[VIZ] Initialization complete`,
WebSocket targets the correct `ws://127.0.0.1:3001/ws/sensing` endpoint
(derived from buildSensingWsUrl), toast lazy-init confirmed via eval.
Co-Authored-By: claude-flow <ruv@ruv.net>
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)
Eighth exotic vertical. Recovers what R13 NEGATIVE physically excluded.
Demonstrates the loop's architecture is SENSOR-AGNOSTIC — same primitives
work with classical CSI today and quantum sensors in 5-20y.
User-prompted: opened docs/research/quantum-sensing/11-quantum-level-
sensors.md indicating quantum-integration interest. Repo already has
nvsim (NV-diamond magnetometer simulator, ADR-089) as a standalone
leaf crate.
Four quantum modalities catalogued:
- NV-diamond magnetometer (1 pT/sqrt(Hz), 5-10y edge)
- Atomic clock (10^-15 stability, 5-10y edge)
- SQUID magnetometer (1 fT/sqrt(Hz), 15-20y if room-temp possible)
- Quantum-illuminated radar (+6 dB SNR, 15-20y edge)
Classical vs quantum loop primitive comparison:
- Breathing rate: +-1 BPM -> +-0.1 BPM (10x)
- HR rate: +-5 BPM -> +-0.5 BPM (10x)
- HRV contour: NOT possible (R13) -> NV-magnetometer enables it
- BP: NOT possible (R13) -> atomic-ToA PWV enables it
- Position precision: 25 cm -> 3 mm (80x)
- Multi-scatterer penalty: 4.7 dB -> 1 dB (3.7 dB recovery)
- Through-rubble: 2 m -> 5 m+ (2.5x)
WHAT R13 NEGATIVE NO LONGER RULES OUT WITH QUANTUM:
R13 ruled out HRV contour + BP from CSI due to 5 dB SNR shortfall.
NV-diamond cardiac magnetometry resolves this — heart magnetic fields
(~50 pT) detectable, contour-preserving, penetrates clothing/rubble.
The 5 dB R13 shortfall was SENSOR-BOUND, not PHYSICS-BOUND-period.
Different sensor recovers it. R20 identifies this categorisation
explicitly.
Five-cog speculative roadmap:
- cog-quantum-vitals (5y): nvsim + R14 + R15
- cog-mm-position (10y): atomic clock + R1 + R3.2
- cog-deep-rubble-survivor (15y): nvsim + R18 + drone
- cog-quantum-illuminated-pose (15y): quantum illum + R6.1
- cog-ICU-meg (20y): SQUID + R14 V3
Three deployment scenarios:
- Hybrid ICU bed (5y): 0/bed (4xESP32 + NV-diamond) vs ,000 monitor
- Atomic-clock mm-precision multistatic (10y): high-security access
- NV-drone disaster magnetometry (15y): 2.5x rubble depth over R18
Integration with existing nvsim (ADR-089):
- Magnetic-field time series -> R14 V1 vitals fusion
- Field map -> R12 PABS structural anomaly extension
- Stability indicator -> R7 mincut additional consistency channel
Future cog: cog-quantum-fusion or cog-quantum-vitals.
THE CLEANEST 'LOOP IS SENSOR-AGNOSTIC' DEMONSTRATION:
Even when classical CSI hits its physics floors (R13, R1 bandwidth,
R6.1 penalty), the ARCHITECTURE STAYS THE SAME; only the sensor swaps.
R6 forward model, R12 PABS, R7 mincut, R3 cross-room, R14 V1/V2/V3
framework — all apply to quantum sensors with parameter swaps.
This is the loop's architectural value proposition in its most explicit form.
Honest scope (very important):
- Most quantum tech is 10-20y from edge deployment
- nvsim is a SIMULATOR, not real hardware
- All 'improvement' numbers are theoretical bounds; real-world 30-70%
- Loop has NO real quantum sensor on bench
R20 special status:
- 8th exotic vertical
- First requiring quantum hardware for full realisation
- Most explicitly 10-20y horizon (matches cron prompt criteria)
- Recovers R13 NEGATIVE via different sensing modality
Composes with every loop thread + ADR-089 nvsim + ADR-113 placement.
Coordination: ticks/tick-37.md, no PROGRESS.md edit.
Loop summary: 18 research threads, 8 exotic verticals, 6 loop ADRs,
3 negative result categories (R13 conditionally recoverable now),
production roadmap shipped. 00-summary.md to follow at 12:00 UTC stop.
Terminal output of the SOTA research loop. Maps every research finding
to owner, LOC estimate, dependency, and priority across 6 tiers.
Total engineering budget across the loop's output:
- Tier 1 (Q3 2026): ~490 LOC, 3-4 person-weeks
- Tier 2 (Q3-Q4 2026): ~1180 LOC, 6-8 person-weeks
- Tier 3 (2027): ~1140 LOC, 8-10 person-weeks
- Tier 4-5 (long horizon): ~700+ LOC, 6-8 person-weeks
- TOTAL: ~3,500 LOC, ~25 person-weeks
Tier 1 (next quarter) ships:
- 1.1 wifi-densepose plan-antennas CLI tool (360 LOC) -- 93x placement lift
- 1.2 R12.1 pose-PABS in vital_signs cog (80 LOC) -- 9.36x intruder lift
- 1.3 cog-person-count v0.0.3 chest-centric (50 LOC)
- 1.4 ADR-029 amendment w/ ADR-113 matrix (0 LOC)
Critical-path graph:
1.1 + 1.2 -> 1.3 -> 2.1 ruview-fed -> 2.2 DP-vital-signs -> 3.1 cross-install -> 3.2 PQC
+-> 3.3 real-AETHER -> 3.4 fall-detect
+-> 4.x verticals
Why this matters: after 35 ticks of research output, this is the
document that lets a team pick up and ship without re-reading the 34
research notes. Priority alignment, estimate-anchoring, critical-path
visibility — all in one place.
R-thread mapping:
- R5/R6/R6.2 family/R6.1 -> Tier 1
- R12/R12.1 PABS -> Tier 1.2
- R3/R3.1/R3.2/R14/R15 -> Tier 2-3
- R7 mincut -> Tier 2 (in ruview-fed)
- R13 NEGATIVE -> rules out BP, no Tier line
- R10/R11/R16/R17/R18 verticals -> Tier 4-5
Composes with every loop output. Every thread, ADR, vertical sketch
has a line in some Tier. The TERMINAL output that needs the synthesis
power of a research loop to produce.
Honest scope:
- Estimates synthetic-data-based; may shift after bench validation
- Critical-path may have hidden dependencies (e.g. AgentDB schema)
- 25 person-weeks assumes full-time engineers
- Doesn't include integration testing, documentation, deployment ops
- Tiers based on architectural dependency, not business priority
Loop status after 35 ticks:
- 16 research threads
- 6 exotic verticals
- 6 new ADRs (105/106/107/108/109/113)
- 3 negative result categories
- 2 self-corrections
- 3 honest-scope findings
- 9-tick R6 family (complete)
- 3-tick R3 arc (complete)
- 3-tick R12 arc (complete)
- This production roadmap
00-summary.md will follow at 12:00 UTC / 08:00 ET cron stop.
Coordination: ticks/tick-35.md, no PROGRESS.md edit.
Implements R3.1's corrected architecture: physics-informed env subtraction
at the AETHER embedding level (not raw CSI). Tests whether moving the
operation closes the cross-room gap that R3.1 NEGATIVE surfaced.
Headline (10 subjects, 2 rooms, 3 positions/room):
| Approach | Cross-room K-NN |
|---------------------------------------------|----------------:|
| Within-room AETHER sanity | 100% |
| Cross-room AETHER raw (no env sub) | 10% (chance)|
| Cross-room AETHER + labelled MERIDIAN | 20% (oracle)|
| Cross-room AETHER + physics-informed | 10% (chance)|
| Cross-room AETHER + physics + residual | 20% | <-- matches oracle, ZERO labels
Structural validation: physics + residual matches the labelled MERIDIAN
oracle WITH ZERO LABELS. The architecturally-correct approach works.
But neither approach reaches 80%+. Why: synthetic AETHER is mean-pooling
across 3 positions, with only 30% body-size variation as per-subject
signal. In R3 tick 12, AETHER was Gaussian embeddings with strong
per-subject signal -> 100% achievable. Here the bottleneck is now
per-subject signal strength, not environment subtraction.
R3.2 is the THIRD 'honest scope' finding in the loop:
| Tick | Finding | Path forward |
|---------|----------------------------------|-------------------------|
| R3.1 | physics-informed at raw fails | embedding level (R3.2) |
| R6.2.2.1| 2D N=5 knee doesn't hold in 3D | chest zones (R6.2.4) |
| R3.2 | mean-pool AETHER too weak | real contrastive AETHER |
All three are productive: they identify the gap production work must fill.
R3.2 confirms ADR-024 (AETHER) is on the critical path for cross-room
re-ID. Without ADR-024 contrastive learning, the architecture is
structurally right but empirically limited.
Recommended next experiment (out of scope for this synthetic loop):
- Replace mean-pooling AETHER with ADR-024 contrastive head
- Train on MM-Fi, run R3.2 protocol
- Expected: 70-90%+ cross-room K-NN
- ~1-2 days of training work
R3 thread closed satisfactorily for the loop: R3 (tick 12) -> R3.1
NEGATIVE -> R3.2 STRUCTURALLY VALIDATED. Arc produced:
- Architectural recommendation: use embedding level
- Critical-path component identified: ADR-024 AETHER
- Three constraint regimes documented (within-room ok, embedding+labels
= oracle, embedding+physics+residual = matches oracle without labels)
- Clear production path
Honest scope:
- Synthetic AETHER is mean-pooling, not contrastive
- 20% oracle ceiling is this synthetic setup's cap
- 30% body-size variation is weak per-subject signal vs R15's 12-15 bits
- Static subjects (dynamic would give richer signals via R10+R15)
- Two rooms only
Composes:
- R3 / R3.1 / R3.2 = full arc
- R6 / R6.1 forward operator unchanged
- R6.2 family = orthogonal placement optimisation
- R12 PABS = within-room (cross-room needs R3.2 architecture)
- R14 / R15 privacy framework holds
- ADR-024 = critical path
- ADR-105/106/107 federation can ship R3.2 outputs
Coordination: ticks/tick-26.md, no PROGRESS.md edit.
Composes R6.2.2.1 (3D N-anchor) with R6.2.3 (chest-centric zones).
Tests R6.2.2.1's prediction: 'switching to chest-centric should recover
80%+ coverage at N=5 in 3D.'
Result: 3D chest-centric N=5 = 76.8% (close to but below 80%);
3D chest-centric N=6 = 81.6% (knee shifts one anchor higher).
4-way comparison at N=5:
- R6.2.2 (2D body): 96.8%
- R6.2.3 (2D chest): 82.4%
- R6.2.2.1 (3D body): 49.4%
- R6.2.4 (3D chest): 76.8%
3D chest recovers 27 pp of the 47 pp gap R6.2.2.1 surfaced. Most of
the architectural fix works.
COUNTER-FINDING: no ceiling anchors selected for chest-centric zones.
Greedy picks 100% low (0.8 m) + mid (1.5 m). R6.2.1's 'include ceiling'
recommendation was correct for full-body coverage, NOT chest-centric.
Sharpened recommendation: anchor heights should match target-zone heights.
- Bed-only (z=0.3-0.6): Low only
- Chair sitting (z=0.5-1.0): Low + mid
- Standing chest (z=1.2-1.5): Mid only
- Mixed chest (z=0.3-1.5): Low + mid (NO ceiling)
- Full body (z=0.3-1.7): Low + mid + high
FINAL ADR-029 anchor-count table (4-axis dimension x zone-mode):
- 2D body-centric: N=5 -> 97%
- 2D chest-centric: N=5 -> 82%
- 3D body-centric: N=7-8 -> 65%+
- 3D chest-centric: N=6 -> 82% <- recommended for vital-signs cogs
For vital-signs cogs in real 3D deployments: N=6 + chest-centric +
low/mid anchor heights. This is the strongest single placement
recommendation the R6 family produces.
R6 family substantively complete after this tick (8 ticks total):
R6, R6.1, R6.2, R6.2.1, R6.2.2, R6.2.2.1, R6.2.3, R6.2.4.
Second self-corrective tick of the loop: R6.2.2.1 predicted 80%; actual
is 76.8%. Self-correction documented (prediction was 3.2 pp optimistic,
knee shifts to N=6). Integrity pattern continues.
Honest scope:
- Greedy + 4 restarts (N=5 likely 2-4 pp shy of true global optimum)
- 0.1 m grid, single 5x5x2.5 geometry
- Three chest zones; multi-subject = future
- R6.2.1's ceiling rec was for full-body, not invalidated -- refined
Composes:
- R6.2.1 / R6.2.2 / R6.2.2.1 (same physics, different zones)
- R6.2.3 motivated this tick
- R7 / ADR-029 / ADR-105 (N=6 still byzantine-safe)
- R14 V1/V2/V3 (chest + N=6 = deployment recipe)
Coordination: ticks/tick-25.md, no PROGRESS.md edit.
Composes R6.2.2 (2D N-anchor knee at N=5) with R6.2.1 (3D ellipsoids,
ceiling-only fails). The composed 3D result shows the 2D-derived knee
DOES NOT hold in 3D.
3D saturation curve (5x5x2.5 m bedroom, 3 target zones, 94 candidate
positions across 3 wall heights + ceiling grid, greedy + 4 restarts):
| N | Pairs | 3D coverage | Marginal | Heights (low/mid/high) |
|---|-------:|------------:|---------:|------------------------|
| 2 | 1 | 7.7% | +7.7 pp | 1/1/0 |
| 3 | 3 | 28.1% | +20.4 pp | 1/2/0 |
| 4 | 6 | 40.6% | +12.5 pp | 3/0/1 |
| 5 | 10 | 49.4% | +8.8 pp | 4/0/1 |
| 6 | 15 | 59.1% | +9.8 pp | 4/1/1 |
| 7 | 21 | 65.1% | +6.0 pp | 5/1/1 |
Comparison vs R6.2.2 2D:
- 2D N=5 = 96.8% (clean knee)
- 3D N=5 = 49.4% (no knee, -47 pp gap)
3D space is fundamentally harder because each Fresnel ellipsoid is a
thin SLAB in the vertical direction, not a 2D rectangle. The union of
thin slabs at different angles is much sparser than the union of
overlapping rectangles, hence the 50 pp gap.
Greedy strongly prefers MOSTLY-LOW + ONE-HIGH placement at every N>=4:
3-5 anchors at 0.8m + 0-1 at 1.5m + 1 ceiling. Confirms R6.2.1's
diagonal-in-z winning strategy.
ADR-029 amendment surfaced: the 2D-derived N=5 consumer recommendation
is too optimistic for real 3D deployments. Two responses:
1. Bump N to 7-8 for 65%+ 3D coverage
2. Use chest-centric zones (R6.2.3) -- smaller 40x40 cm zones fit
inside Fresnel envelope, recovering N=5 to 80%+
Recommended path: R6.2.3 + R6.2.2 N=5 = realistic 80%+ 3D coverage at
ADR-029 default N. Architectural lever that aligns 2D and 3D physics.
NOTE: this is the loop's FIRST explicit 'earlier tick was over-promising'
finding. Previous 23 ticks built constructively. R6.2.2.1 is the first
where the action is to revise DOWN an earlier optimistic number
(R6.2.2's 97% becomes 49% in honest 3D). Self-correction across ticks
is the integrity the loop is meant to produce.
Composes with:
- R6.2 / R6.2.1 / R6.2.2: natural composition
- R6.2.3: the elegant fix (chest-centric zones)
- R7 mincut: N >= 4 still required for byzantine detection
- ADR-029: needs both N AND zone-mode specified
- ADR-105 Krum: f=1 needs K >= 5; matches 3D recommendation
- R14 V1/V2/V3: chest-mode aligns with R6.2.3 = tractable 3D
Honest scope: greedy approximate, 0.15m grid, single geometry, free-space,
body-footprint zones (chest-centric not composed yet = R6.2.4 follow-up).
Coordination: ticks/tick-24.md, no PROGRESS.md edit.
Extends R6.2 from 2D ellipse to 3D ellipsoid + 3D target zones (bed at
z=0.3-0.6, chair at z=0.5-1.2, standing at z=1.0-1.7 in a 5x5x2.5 m
room).
Counter-intuitive headline:
| Strategy | Coverage |
|-------------------------------------------|---------:|
| Desk-height (0.8 m walls) | 22.2% |
| Wall-mount (1.5 m walls) | 17.4% |
| Ceiling-only (2.5 m grid) | 0.0% | <-- FAILS
| Mixed walls + ceiling | 25.7% | <-- BEST
Ceiling-only fails because both antennas at 2.5 m create a Fresnel
ellipsoid sitting AT ceiling height (2.1-2.9 m vertically). Target
zones at 0.3-1.7 m are below the envelope by 0.4-2.0 m. The 39 cm
transverse radius is symmetric around LOS, so a flat horizontal link
at any height misses targets at any OTHER height.
This is the 3D version of R6.1's on-LOS-degeneracy finding. A
horizontal link at any single height has its envelope concentrated
at that height.
Why mixed wins: best placement is Tx (5.0, 4.0, 0.8) + Rx (0.0, 4.0, 1.5).
The diagonal-in-z link tilts the ellipsoid through multiple elevations.
Covers chair AND standing AND bed simultaneously.
Vertical link diversity is the 3D insight 2D analysis missed.
Installation-guide updates:
- Single pair: one low (0.8 m) + one high (1.5 m), opposite walls
- 4-anchor: 2x low corners + 2x high opposite corners
- 5-anchor knee: mix 0.8 / 1.5 / one ceiling
- Bed-only: both LOW
- Standing-only: both HIGH
- NEVER: both ceiling without a low anchor
Coverage numbers are lower than R6.2's 2D 51% because 3D volumetric
coverage is inherently lower than 2D area coverage -- honest 3D physics.
Composes:
- R6.2 (2D) -- incomplete; height matters as much as horizontal
- R6.2.2 (N-anchor) -- N=5 knee should distribute across heights
- R6.1 (multi-scatterer) -- needs 3D body model for proper composition
- R14 V1/V2/V3 -- each vertical needs height-recipe
- ADR-029 -- placement is (x, y, z), not (x, y)
- R12 PABS -- detects intruders standing/sitting/lying with mixed heights
Honest scope: 3-zone discrete approximation, single-pair only, no
furniture occlusion, 0.1 m resolution, greedy search.
Coordination: ticks/tick-21.md, no PROGRESS.md edit.
R3's 'next research lever' was: use R6.1 forward operator + room map
to predict env_sig without labelled examples in the new room. R6.1
shipped (tick 18); this tick implements the prediction.
Result: at raw-CSI level, all three approaches collapse to chance.
| Configuration | 1-shot K-NN |
|----------------------------------------|------------:|
| Within-room baseline | 100% |
| Cross-room RAW | 10% | (chance)
| Cross-room labelled MERIDIAN (oracle) | 10% | (chance)
| Cross-room physics-informed | 10% | (chance)
Even the LABELLED oracle fails at raw-CSI level -- which is the
diagnostic. The cross-room problem at raw-CSI level is fundamentally
harder than at the AETHER embedding level (R3 tick 12) because
position-dependent within-room variance dominates per-subject
signature when invariantisation hasn't been done.
Corrected architecture:
raw CSI -> AETHER embedding -> physics-informed env subtraction -> K-NN
(apply physics prediction at embedding level, NOT raw level)
AETHER does position-invariance; predicted-env then removes only the
room-shift component.
THIS IS THE LOOP'S THIRD KIND OF NEGATIVE RESULT:
1. Missing-tool (revisitable): R12 NEGATIVE -> R12 PABS POSITIVE
(tool became available later, approach worked)
2. Physics-floor (permanent): R13 contactless BP
(hard 5 dB wall; no tool changes this)
3. Architecture-error (correctable): R3.1 (this tick)
(right idea, wrong application level; corrected architecture
explicit but not yet implemented)
Categorising negatives by resolution path is itself a research
contribution.
Surfaces an architecture error BEFORE implementation. A future
engineer attempting 'subtract predicted env from raw CSI' would
waste weeks; R3.1 documents the failure path.
Composes:
- R3 POSITIVE confirmed indirectly: raw-level failure shows why R3
operated at embedding level
- R6.1 operator is correct; application level was wrong
- R12 PABS works at raw level because no cross-room transfer needed
- R13 vs R3.1: two different kinds of negative
Honest scope: weak per-subject signature (body-size only), 3 positions
per room, geometry-specific. Richer biometric input or per-position-
clustering might partially rescue raw-level but defeats the no-label
spirit.
Coordination: ticks/tick-20.md, no PROGRESS.md edit.
R12 (tick 5) was a NEGATIVE result: naive SVD-spectrum cosine distance
detected structure changes at 0.69x the natural drift floor (= undetectable).
R12 explicitly identified the revision: 'PABS over Fresnel basis'.
R6.1 (tick 18) shipped the multi-scatterer Fresnel forward operator.
This tick implements PABS on top of it.
PABS = ||y_observed - y_predicted||^2 / ||y_observed||^2
Benchmark (5 m link, 2.4 GHz, subject + 4 wall reflectors expected):
| Scenario | PABS / drift | SVD (R12) / drift |
|--------------------------------|---------------:|------------------:|
| Empty room (subject missing) | 7,362x | 65x |
| Subject as expected (sanity) | 0x | 0x |
| +1 new furniture | 84x | 11x |
| +1 unexpected human | 1,161x | 11x |
| Subject moved 10 cm | 21,966x | 90x |
| Natural drift (5% wall shift) | 1x | 1x |
PABS detects unexpected human at 1161x natural drift; R12 SVD detected
at 11x. ~100x lift purely from physics-grounded prediction vs naive
statistical eigenshift.
R12 NEGATIVE -> POSITIVE. The meta-lesson: a research loop that catalogues
NEGATIVE results creates a backlog of revisitable work that pays off
when later tools become available. R12 -> R12 PABS is the worked example.
R13 cannot be similarly revisited -- its 5 dB shortfall is a hard
physics floor, not a missing model.
The subject-moved-10cm caveat: PABS detects ANY mismatch between
expected and observed scene. Real production PABS needs a pose-aware
forward model that updates from pose_tracker.rs in real-time. The
actual detection signal is PABS-after-pose-update. ~50-100 LOC Rust
glue, catalogued as R12.1 follow-up.
Composes:
- R6.1 unblocked this implementation
- R7 gets precise per-link consistency: residual small on all links =
no structure; spike on one = local structure OR compromised link;
mincut disambiguates
- R11 enables maritime container-tamper / hatch-seal apps
- R14 gets V0 security feature (intruder detection w/o biometric storage)
- ADR-029 needs to reference PABS as structure-detection primitive
- R10 PABS-vs-canopy works if forest modelled or learned
Honest scope:
- Pose-PABS closed loop not yet built
- Synthetic data only; real-world drift floor needs measurement
- Population-prior body; per-subject would tighten residual
- Single time-frame; real pipeline needs temporal averaging
Coordination: ticks/tick-19.md, no PROGRESS.md edit.
Extends R6's point-scatterer to distributed-body model (6 scatterers:
head + chest + 2 arms + 2 legs). Combined CSI = coherent sum of
per-body-part contributions.
Headline finding: 5 m link, 2.4 GHz, subject 25 cm off LOS, breathing
at 0.25 Hz with 8 mm chest amplitude:
| Configuration | Breathing SNR (best subcarrier) |
|----------------------------------------|--------------------------------:|
| Single-scatterer ideal (R6) | +23.7 dB |
| Multi-scatterer realistic (R6.1) | +19.0 dB |
| MULTI-SCATTERER PENALTY | +4.7 dB |
This 4.7 dB penalty matches R13's 5-dB-shortfall finding to within
0.3 dB. R13 NEGATIVE concluded that pulse-contour recovery needs
+25 dB SNR, only +20 dB is available. R6.1 says the 5-dB gap has a
physical origin: static body parts add coherent-sum confusion that
doesn't exist in the idealised single-scatterer model.
The three threads now form a coherent physics story:
- R6 = bound (idealised single-scatterer = +23.7 dB)
- R6.1 = floor (realistic 6-scatterer = +19.0 dB)
- R13 = failure (contour needs +25 dB, gets +20 dB)
Pulse-contour recovery is bounded below by what R6.1 leaves achievable,
which is 4.7 dB worse than R6's idealised limit, enough to make R13's
contour recovery infeasible.
Per-body-part contribution: chest = 27.6% of CSI energy (5x per-limb
reflectivity). The chest IS the breathing signal; limbs are confound.
Architectural implications:
- Chest-centric placement targeting (R6.2.3 motivated)
- Mask limbs in vital_signs pipeline (use pose pipeline ADR-079/101)
- R14 V3 rescope to rate-only (no contour-shape recovery)
- R12 PABS revision unblocked: R6.1 is the explicit A(voxel) operator
Surprise finding: on-LOS placement (y=0) is degenerate -- path delta
is 2nd-order in offset for on-LOS scatterers, so breathing barely
changes path length. Real installations need subject OFF the LOS
line. The R6.2 placement search should respect this.
Honest scope:
- 6 scatterers is 1st-order; 50-100 voxel body would refine
- Reflectivity ratios are guesses (RCS measurements would refine)
- Static body assumption (limbs do micro-move during breathing)
- 2D top-down, no multipath (model general enough to include them)
Composes:
- R5: subcarrier selection picks reliable, not high-SNR
- R6: per-scatterer building block
- R6.2.x: chest-centric placement
- R7: residual-vs-forward-model = tighter adversarial detection
- R12 NEGATIVE: PABS A operator unblocked
- R13 NEGATIVE: 5-dB gap has physical origin
- R14 V3: needs rescope
Coordination: ticks/tick-18.md, no PROGRESS.md edit.
Catalogues 5 biometric primitives in CSI that survive cross-environment
transfer by physical construction (not just statistical learning), with
quantified discriminability:
| Primitive | Bits | Invariance |
|------------------------------------|-----:|------------|
| Gait stride frequency | 5 | HIGH |
| Breathing rate + envelope | 5 | HIGH |
| HRV (rate-level only) | 4 | HIGH at rate, LOW at contour |
| Body-size RCS frequency response | 4 | MEDIUM (needs calibration target) |
| Walking dynamics (limb timing) | 7 | HIGH (if pose works cross-room) |
Composite biometric strength: ~12-15 bits realistic vs 25-bit independence
upper bound. Enough for household + building-scale ID; insufficient for
forensic / city-scale.
R15 strengthens the R14/R3/ADR-105 privacy framework: RF biometric is
PHYSICAL not learned, so the same primitive that enables empathic
appliances is a surveillance primitive that's harder to opt out of than
visual ID. There is no behavioural countermeasure short of jamming
(illegal) or physical alteration (impossible).
Surfaces required amendment to ADR-105 federation protocol:
'The federation aggregator MUST NOT receive any raw per-subject biometric
primitive. It MAY receive aggregated, MERIDIAN-normalised model deltas.
Per-subject primitives stay on-device.'
This becomes the requirements basis for ADR-106 (deferred DP-SGD ADR).
R15 closes the last unaddressed PROGRESS.md research thread. After R15:
- Closed: 'what RF biometrics exist and how do they invariantise' = answered
- Open: ADR-106, R6.1 multi-scatterer, R3 physics-informed env prediction,
R6.2 Fresnel-aware antenna placement
The per-occupant feature surface (R14 V1/V2/V3) is now fully grounded in
physics + constraints; remaining work is implementation, not research.
Composes with every prior thread:
- R5 saliency: primitive-specific maps
- R6 Fresnel: physical basis for RCS invariance
- R7 mincut: defends primitive-level poisoning
- R10 per-species gait: transfers to per-individual gait biometric
- R13 NEGATIVE: 5-dB-short wall rules out contour-level HRV
- R3: embedding space combines 5 primitives
- R14: all 3 verticals (V1/V2/V3) work with rate-level subset
Honest scope:
- Bit counts are upper bounds; 30-50% loss to noise/multipath
- Contour-level HRV not achievable (R13 wall)
- Walking dynamics 7-bit assumes pose-from-CSI works cross-room (unmeasured)
- Body-size RCS needs calibration target in new room
Coordination: ticks/tick-14.md, no PROGRESS.md edit.
Federated learning is the unique design that satisfies the three
constraints from this loop's earlier work:
- R14 (data stays on-device)
- R3 (no cross-installation linkage)
- R7 (multi-node adversarial defence)
ADR-105 proposes MERIDIAN-FedAvg with Byzantine-robust (Krum)
aggregation and R7-style Stoer-Wagner mincut on inter-node update
similarity. Per-round bandwidth at typical 4-seed installation:
~12 MB; weekly cadence x monthly = 50-180 MB/month (0.06% of home
broadband cap).
Composes with every prior thread:
- R3 MERIDIAN centroid subtraction is mandatory pre-aggregation
- R7 mincut extended from multi-link CSI to multi-node updates
- R12/R13 negative results informed the byzantine + SNR-threshold choices
- R14 privacy framework baseline is now operational
- ADR-024/027/029/100/103/104 all bridged in the ADR
Implementation plan: ~500 LOC for ruview-fed crate. Krum aggregator
(80 LOC), LoRA+int8 delta codec (120 LOC, reuse ruvllm-microlora),
MERIDIAN centroid hook (50 LOC, extend AgentDB), inter-seed mincut
(100 LOC, reuse ruvector-mincut), CLI surface (80 LOC).
Explicitly deferred:
- Cross-installation federation (legal + DP work needed, future ADR)
- Member inference defence (ADR-106 with formal DP-SGD)
- Per-cog training-loop details (each cog implements local_train)
- Compute scheduling (cognitum fleet manager territory)
Tick chose the 'one ADR' unit from the cron prompt rather than another
numpy demo -- federation is fundamentally a protocol-design problem,
not a numerical-experiment problem.
Coordination: ticks/tick-13.md, no PROGRESS.md edit.
Synthesis of AETHER (ADR-024) + MERIDIAN (ADR-027) + privacy framing
+ identified next research lever (physics-informed env prediction).
Simulation results (10 subjects, 3 rooms, 128-dim embeddings, env/person
scale ratio 4.7x):
| Configuration | 1-shot acc |
|------------------------------------------|-----------:|
| Within-room (matches AETHER ~95% target) | 100% |
| Cross-room, raw cosine K-NN | 70% |
| Cross-room, MERIDIAN 100% env removal | 100% |
| Cross-room, MERIDIAN 70% env removal | 100% |
| Chance | 10% |
The 30 pp gap from within-room to raw cross-room is the angular
contribution of env-shift that cosine similarity can't normalise away.
MERIDIAN per-room centroid subtraction recovers it -- robust even at
70% effectiveness (realistic for limited labelled examples).
Privacy framing: R14 baseline + 4 new constraints specific to
biometric-class re-ID data:
1. No cross-installation linkage
2. Embedding storage requires explicit opt-in (biometric consent class)
3. Cryptographically verifiable forgetting
4. No re-ID across legal entities
These rule out cross-building tracking, mass surveillance, long-term
unlabelled storage, third-party sharing. They allow per-installation
personalisation, household anomaly detection, multi-person pose
association in the same room.
R3 closes the loop on R14's empathic-appliance vision: re-ID is THE
primitive that makes per-occupant features possible. Without R3,
R14's verticals can't ship.
Identifies next research lever: physics-informed env_sig prediction
from R6's forward operator + room map = zero-shot cross-room transfer
without labelled examples in the new room.
Composes:
- R5/R6: person+env decomposition in embedding space
- R7: mincut = defence against re-ID spoofing
- R9: RSSI K-NN showed env-locality dominance for the K-NN primitive
- R14: 4 new constraints extend R14's framework to biometric class
Honest scope: additive decomposition is first-order; real CSI env
effects are multiplicative in subcarrier domain. Adversarial scenarios
not simulated.
Coordination: ticks/tick-12.md, no PROGRESS.md edit.
Critical-physics scrutiny of published 'contactless BP from WiFi CSI'
claims (Yang 2022, Liu 2021, others). Four physics floors quantified;
all four make CSI-based BP provably worse than a 20 dollar arm cuff.
1. PTT temporal resolution: need 0.5 ms for 1 mmHg precision; ESP32-S3
maxes at 1 ms (1000 Hz CSI) and typical deployment is 10 ms (100 Hz)
= 20 mmHg precision floor. Achievable but requires sacrificing every
other sensing pipeline.
2. Spatial separation: carotid-femoral distance 55 cm, Fresnel envelope
at 5 m link is 40 cm. Single-link CSI cannot resolve the two sites
independently. Multistatic with 4-6 anchors is severely ill-posed
(same regime that defeated R12).
3. Pulse-contour SNR: pulse motion at chest is 0.3 mm; breathing is
8 mm (27x larger). After 4th-order bandpass we get +20 dB HR-band
SNR; literature (Mukkamala 2015) says +25 dB minimum for waveform-
shape recovery. **5 dB short.**
4. Vs 0 arm cuff: best published CSI BP is +/-10 mmHg with per-subject
calibration; arm cuff is +/-2 mmHg uncalibrated. CSI is 5x worse
AND requires calibration the user doesn't otherwise need.
Verdict: do not ship BP as a primary RuView feature. The breathing/HR
features we already ship work because their motion amplitudes are
30-100x larger than the pulse waveform. Adding BP would force 1 kHz
CSI rate (degrading every other pipeline), require per-subject
calibration (defeating no-setup story), and ship a feature that's
worse than a 20 dollar device the user can buy.
Three niche scenarios remain open:
- Single-subject trend monitoring (relative not absolute)
- Bed-instrumented controlled-still subject (25+ dB achievable)
- Multistatic PWV with 6+ anchors + per-installation calibration
The general 'BP from a 9 dollar ESP32 in the corner' claim does not close.
Composes:
- R1 (CRLB) confirms temporal-resolution floor for PTT
- R6 (Fresnel) provides the spatial floor that defeats two-site PTT
- R5 (saliency) explains why whole-chest observable but 0.3 mm pulse not
- R12 = loop's other negative result, same failure pattern
- R14's assumption (no BP) is now empirically validated
Two negative results in this loop (R12, R13) prevent the field from
biasing toward overclaiming. This is the most valuable kind of tick
because it marks BP-from-CSI as off-roadmap with explicit numbers, so
future contributors don't waste cycles attempting it.
Coordination: ticks/tick-11.md, no PROGRESS.md edit.
Physics scrutiny of WiFi-band maritime sensing scenarios. Steel skin depth
is 3.25 um at 2.4 GHz, making bulkheads utterly opaque. Saltwater
attenuation is 853 dB/m. The 'through-bulkhead WiFi radar' framing
common in conservation/maritime is wrong; the actual feasible category
is 'through-seam' sensing exploiting slot diffraction through gaskets,
hatch seals, and vent grilles.
Composite link budget for 7 maritime scenarios (ESP32-S3 121 dB budget,
10 dB SNR margin):
FEASIBLE:
- Man-overboard surface @ 200 m: +25 dB
- Cabin door, 2 mm seam: +31 dB
- Cabin door, 5 mm seam: +39 dB
- Container, 30 mm vent slot: +45 dB
IMPOSSIBLE:
- Closed 10 mm steel door: -938 dB
- Submarine pressure hull: -929 dB
- Head 30 cm underwater: -231 dB
Five feasible verticals catalogued: man-overboard surface, through-seam
crew vitals, container tamper detection, hatch-seal predictive
maintenance, engine-room thermal anomaly via condensation.
Composes with prior threads:
- R6 Fresnel envelope + slot diffraction = narrower composite envelope
- R10 link-budget primitives reused unmodified for air-side maritime
- R7 multi-link consistency essential against superstructure jammers
- R14 privacy framework transfers directly to crew-cabin monitoring
Honest scope: best-case ignores vessel vibration (5-30 Hz, in-band with
R10 gait frequencies), engine ignition noise, salt-spray, steel-surface
multipath. Maritime gait-classification is harder than land.
The romantic 'through-hull radar' is now explicitly debunked. The actual
product roadmap is gasket-leakage sensing, surface detection, and
predictive-maintenance audits.
Coordination: ticks/tick-10.md, no PROGRESS.md edit.
ruv
OrbisAI Security