Pure conversion from our wire-format `MdnsService` to the
`mdns_sd::ServiceInfo` shape the responder daemon consumes. No
socket binding, no daemon registration yet — that lands next iter
as a `runtime::spawn_mdns_responder(info)` JoinHandle returning
helper, same shape as `runtime::spawn_publisher`.
* `MdnsService::to_service_info(hostname, ipv4) ->
Result<ServiceInfo, mdns_sd::Error>`
* `mdns-sd = "0.11"` added — aligned with the workspace pin from
wifi-densepose-desktop so the lockfile doesn't fork dalek-like
surfaces.
3 new tests:
* to_service_info_carries_service_type_and_port — locks that
`_ruview-ha._tcp` (with or without mdns-sd's trailing-dot
normalisation) and the control port round-trip through the
conversion
* to_service_info_propagates_txt_records — every locked TXT
key from iter 4 (cog_id, mqtt_port, privacy, proto, node_id,
cog_version) reachable via `get_property_val_str` on the
converted ServiceInfo
* to_service_info_does_not_silently_drop_caller_hostname —
locks the caller-side responsibility for the .local. suffix.
mdns-sd 0.11 accepts bare hostnames (verified empirically by
initial test expecting it to reject — it didn't), so the
wrapper layer must do the trailing-dot dance. Documenting
that via a named test catches future bumps where the lib
starts mutating the value.
63/63 cog tests green (60 → 63).
ADR-116 P4 now ⁶⁄₇: ✅ mDNS record-builder, ✅ chain, ✅ JSONL, ✅
file persistence, ✅ Ed25519 signing, ✅ ServiceInfo conversion;
⏳ daemon register + embedded broker.
Co-Authored-By: claude-flow <ruv@ruv.net>
Closes the cryptographic-attestation gap in ADR-116 §2.2: every
witness event can now be signed by the Seed's Ed25519 key, with
verify available to any auditor holding the public key.
Module shape (`src/witness_signing.rs`, kept separate from
`witness::` so the hash chain stays usable without dalek linked
in — important for the wasm32 audit-verifier variant we'll ship
later):
* sign_event(event, &SigningKey) -> Signature
* verify_signature(event, &Signature, &VerifyingKey)
-> Result<(), SignatureVerifyError>
* signature_to_hex / signature_from_hex (128-char lowercase,
matches the witness hex convention)
* SignatureVerifyError::Invalid
* SignatureParseError::{Length, Hex}
Key design point: signature covers the SAME canonical bytes
witness::hash_event hashes. That means:
1. A signed event commits to the entire event content (kind,
payload, timestamp, seq, prev_hash) — no field can be
retroactively changed without invalidating both the hash AND
the signature.
2. The signature implicitly commits to the event's *chain
position* via prev_hash — splicing a signed event into a
different chain breaks verification.
Adds `ed25519-dalek = "2.1"` to cog-ha-matter (already in
workspace via ruv-neural, version kept aligned).
9 new tests:
* sign_and_verify_round_trip
* verify_rejects_signature_under_wrong_key
* verify_rejects_tampered_event (mutate payload after sign)
* verify_rejects_event_with_wrong_prev_hash (splice attack)
* signature_hex_round_trip
* signature_from_hex_rejects_wrong_length
* signature_from_hex_rejects_non_hex
* signature_is_deterministic_for_same_event_and_key
(locks Ed25519's determinism — catches future accidental
swap to a randomized scheme)
* different_events_produce_different_signatures
60/60 cog tests green (51 → 60). Key management is intentionally
out of scope here — the cog runtime reads the Seed's key from the
Cognitum control plane's secure store (separate concern).
ADR-116 P4 now ⁵⁄₆: ✅ mDNS record, ✅ chain, ✅ JSONL, ✅ file
persistence, ✅ Ed25519 signing; ⏳ responder + embedded broker.
Co-Authored-By: claude-flow <ruv@ruv.net>
Closes the witness audit-bundle surface. The hash-chain primitive
+ JSONL serializer from earlier iters only handled one event at a
time; this lands the file-stream surface that operations actually
need:
* `WitnessChain::write_jsonl(&mut impl Write) -> io::Result<()>`
— streams every event as one line + `\n`, empty chain writes
zero bytes
* `WitnessChain::read_jsonl(impl BufRead) -> Result<WitnessChain,
WitnessReadError>` — parses event-by-event AND runs chain-level
`verify()` on the loaded chain, catching reordered or replayed
prefixes that per-event hashing alone misses
Critical security property: `read_jsonl` calls `WitnessChain::verify`
on the loaded chain BEFORE returning Ok. A forged bundle assembled
from two valid chains pasted together would slip past the
per-event hash check (each event's `this_hash` is internally
consistent) but the cross-event `prev_hash` linkage detects the
seam. Test `read_jsonl_chain_verify_catches_reordered_events`
locks this — swap two events in a 2-event bundle, see Verify error.
Error surface (new `WitnessReadError` enum):
* `Io { line_no, msg }` — read failure mid-stream
* `Parse { line_no, source }` — per-event from_jsonl_line failure
* `Verify { source }` — chain-level verify failure
`line_no` is 1-indexed so an auditor sees the same number their
text editor shows. Blank lines tolerated for hand-edited bundles.
7 new tests:
* empty chain writes zero bytes
* write→read round-trips a 3-event chain
* exactly N newlines for N events; trailing newline present
* blank lines / leading newline tolerated
* parse error surfaces with correct line_no
* reordered events caught by chain-level verify
* no-trailing-newline still loads the final event
51/51 cog tests green (44 → 51).
Co-Authored-By: claude-flow <ruv@ruv.net>
Third P4 sub-unit: serialize/parse for the witness hash chain so
audit bundles can be written to disk and replayed.
Wire shape (one record per line, alphabetical field order locked):
{"kind":"...","payload_hex":"...","prev_hash":"...","seq":N,
"this_hash":"...","timestamp_unix_s":N}
Why alphabetical field order: auditors archive whole bundles and
hash them. A rebuild that reordered fields would silently
invalidate every archival hash — locking the order is what makes
the JSONL stable across compiler / serde-json upgrades.
Why hex everywhere: human-greppable, monospace-friendly, no base64
ambiguity, no Vec<u8> JSON-array ugliness. Same convention as
ADR-101's `binary_sha256`.
Critically, `from_jsonl_line` RE-VERIFIES `this_hash` against
the canonical bytes derived from the parsed fields. A tampered
bundle fires `WitnessParseError::HashMismatch` BEFORE the event
loads — the parser is itself an auditor.
New surfaces:
* `WitnessHash::from_hex` (with structured length/parse errors)
* `WitnessEvent::to_jsonl_line`, `from_jsonl_line`
* `WitnessParseError` enum: Json | MissingField | WrongType |
HashLength | HashHex | PayloadHex | PayloadLength | HashMismatch
* private `hex_encode` / `hex_decode` helpers (no `hex` crate dep)
10 new tests:
* jsonl round-trip preserves all fields
* jsonl line has no embedded \n / \r (one record per line)
* jsonl field order is alphabetical (byte-stable archival)
* parser rejects tampered payload via HashMismatch
* parser rejects non-hex characters in hash
* parser rejects missing field
* hex encode/decode round-trip across empty / single byte / 0xff /
UTF-8 / arbitrary bytes
* hex decode rejects odd-length input
* WitnessHash::from_hex round-trip
* WitnessHash::from_hex rejects wrong length
44/44 cog tests green (34 → 44).
ADR-116 P4 row enumerates 4 sub-units now: ✅ mDNS record-builder,
✅ witness chain primitive, ✅ witness JSONL persistence,
⏳ responder + embedded broker + Ed25519 signing.
Co-Authored-By: claude-flow <ruv@ruv.net>
Second P4 unit: an append-only SHA-256 hash chain for tamper-evident
audit logging. ADR-116 §2.2 promised this for healthcare /
education / shared-housing deployments — this lands the primitive
with no key dependency so the next iter can layer Ed25519 signing
on top without touching the chain itself.
Module shape:
* `WitnessHash([u8; 32])` newtype + `WitnessHash::GENESIS` sentinel
* `WitnessEvent { seq, prev_hash, ts, kind, payload, this_hash }`
— once committed, every field is immutable
* `WitnessChain` — `append`, `tip`, `verify`, `events`
* `canonical_bytes` — length-prefixed serialization that prevents
the classic concatenation forgery
(`abc|def` ≠ `ab|cdef`)
* `WitnessVerifyError` — auditor-friendly error with `at: usize`
on every variant (SeqGap, PrevHashMismatch, HashMismatch)
13 new tests covering both happy path and active tampering:
* genesis hash all-zeros
* empty chain tip is genesis
* canonical bytes length-prefixed (anti-forgery)
* canonical bytes start with prev_hash (wire-format lock)
* append links to prev_hash
* seq monotonic from 0
* verify passes on clean chain
* verify catches tampered payload (fires HashMismatch)
* verify catches broken prev_hash link
* verify catches seq gap
* hash hex is 64 lowercase chars
* first event prev_hash == GENESIS (auditor anchor)
* different payloads → different hashes
Hash-chain over Merkle is the right tradeoff for the cog's event
rate (a few/min steady, dozens during a fall) — linear scan is
fine and we save the Merkle complexity for a future tier when
chains span days.
34/34 cog tests green (21 → 34).
ADR-116 P4 row updated to enumerate the three P4 sub-units shipped /
pending: (a) mDNS record-builder ✅, (b) witness hash-chain ✅, (c)
responder + embedded broker + Ed25519 signing pending.
Co-Authored-By: claude-flow <ruv@ruv.net>
Opens P4 with the smallest extractable unit: a pure builder that
produces the wire-format `MdnsService` the responder will publish
next iter. Splitting the record-builder from the responder lets
us:
* lock the TXT-record surface with named unit tests so drift
between the cog and the HA-side YAML auto-discovery binding
fires a test instead of silently breaking deployments,
* swap the responder library (mdns-sd / zeroconf / pnet) without
touching content,
* include the advertisement in `--print-manifest` for Seed
integration tests that can't boot tokio.
TXT surface (sorted, RFC 6763):
| cog_id | "ha-matter" |
| cog_version | CARGO_PKG_VERSION |
| node_id | identity.node_id |
| mqtt_port | u16 stringified |
| privacy | "1" | "0" |
| proto | "ruview-ha/1" |
9 new tests:
* service_type locked to `_ruview-ha._tcp`
* instance_name carries node_id
* control_port advertises the *control plane*, not MQTT
* privacy flag is "1"/"0" (HA config flow reads it byte-stable)
* proto version locked to ruview-ha/1 (bump is deliberate)
* cog_id in TXT matches crate constant
* txt_records sorted for byte-stable mDNS responses
* **PII leak guard**: TXT must NOT carry hr_bpm, br_bpm, pose_*,
keypoint, ssid, lat, lon, mac, rssi — broadcasts in cleartext
so a future "let's add hr_bpm for convenience" patch fires
here, not in a privacy incident.
* required-keys lock — adding is fine, removing/renaming breaks
every deployed Seed.
21/21 cog tests green (12 → 21).
ADR-116 P4 flipped pending → in progress, with the responder /
embedded broker / witness chain enumerated as the remaining P4
sub-units.
Co-Authored-By: claude-flow <ruv@ruv.net>
P3 closes the publisher wiring loop. `main.rs` now:
1. builds `PublisherInputs` from CLI args via the pure helper
extracted last iter,
2. opens a `broadcast::channel::<VitalsSnapshot>(256)`,
3. calls `runtime::spawn_publisher(inputs, rx)` — a thin
wrapper around ADR-115's `publisher::spawn` that owns the
`Arc<MqttConfig>` wrap,
4. holds the tx side so the channel stays open until P3.5
wires the sensing-server bridge,
5. awaits Ctrl-C or unexpected publisher exit (logged at WARN).
Two new tests:
* `spawn_publisher_returns_live_handle_without_broker` — proves
the wiring compiles and the rumqttc event loop survives an
unreachable broker (it retries internally; we abort the handle
inside 100 ms). Catches breakage from a future refactor that
accidentally pre-validates host reachability.
* `default_state_channel_capacity_is_reasonable` — locks the
`DEFAULT_STATE_CHANNEL_CAPACITY = 256` default; a regression to
e.g. 1 would surface here instead of as a dropped frame in
production under bursty multi-Seed federation.
12/12 cog-ha-matter tests green (10 → 12).
ADR-116 phase table: P3 flipped from "in progress" to ✅ wiring done,
with the P3.5 follow-up (sensing-server `/v1/snapshot` WS bridge)
explicitly named.
Co-Authored-By: claude-flow <ruv@ruv.net>
Adds `runtime::build_publisher_inputs(host, port, privacy, identity)` —
the side-effect-free helper that turns the cog's CLI surface into the
`(MqttConfig, OwnedDiscoveryBuilder)` pair ADR-115's `publisher::spawn`
consumes. Keeps the tokio runtime wiring out of the pure unit so the
mDNS responder + Seed control plane (P4) can build the same inputs
from different sources without going through clap.
8 new tests lock the wire-format invariants:
* host/port round-trip into MqttConfig
* privacy_mode propagation (P1 dossier item 7, FDA Jan 2026)
* discovery_prefix defaults to "homeassistant"
* discovery carries node_id + sw_version + friendly_name
* via_device advertises COG_ID (ADR-101/102 device-registry shape)
* client_id includes node_id (lesson from ADR-115 iter 45-48 session
takeover post-mortem — two publishers sharing a client_id loop)
* tls defaults to Off for v1 LAN-only (lock against silent enablement)
* default_identity carries CARGO_PKG_VERSION + PID for uniqueness
Plus the existing 2 manifest tests → 10/10 green
(`cargo test -p cog-ha-matter --no-default-features --lib`).
Also lands the deep-researcher dossier (`docs/research/ADR-116-ha-...`)
that the ADR §3+§4 reference — it was produced last iter but only the
ADR was committed; this puts the source-of-truth into the tree so the
ADR's "8 sections, 30+ citations" claim is actually verifiable.
P3 status in the ADR phase table flipped from "pending" to "in progress"
with the helper named; next iter tokio::spawns publisher::run(...) in
main.rs and registers the mDNS responder.
Co-Authored-By: claude-flow <ruv@ruv.net>
Proposes `cog-ha-matter` as a Cognitum Seed cog packaging the
ADR-115 HA-DISCO + HA-MIND surfaces as a first-class Seed-installable
artifact, rather than configuration of an external sensing-server.
P1 — research dossier in progress (deep-researcher agent), output at
`docs/research/ADR-116-ha-matter-cog-research.md`.
Seed-native enhancements vs the ADR-115 sensing-server flag:
- Embedded mosquitto (optional, for Seeds without external broker)
- mDNS service advertisement (_ruview-ha._tcp)
- RuVector-backed semantic-primitive thresholds (SONA adaptation,
per-home learning rather than static YAML)
- Ed25519 witness chain for state transitions (regulated deployments)
- OTA firmware coordination for the mesh's ESP32-C6 nodes
- Multi-Seed federation via ADR-110 ESP-NOW substrate (≤100 µs
sync enables cross-Seed dedup of events like falls in shared rooms)
7 open questions tracked for the research dossier to answer:
Matter Bridge vs Matter Root, Thread Border Router feasibility,
HACS value-add, CSA cert cost/timeline, cog binary RAM budget,
ruvllm latency, HIPAA/FDA classification.
10 implementation phases scaffolded. Tracking issue to file once
research lands. PR for the cog binary in P2.
Co-Authored-By: claude-flow <ruv@ruv.net>
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.
Quantitative Cramer-Rao Lower Bound analysis for WiFi ranging via both
Time-of-Arrival and phase-based methods, with multistatic 4-anchor
position-error budget.
Headline (20 MHz HT20, 20 dB SNR, 100 averaged frames):
- ToA range CRLB: 4.1 cm
- Phase (5 deg noise): 0.17 mm
- Phase advantage: 240x (after ambiguity resolution)
4-anchor convex-hull room (GDOP 1.5):
- ToA position precision: 25 cm (room-pose-quality floor)
- Phase position precision: 1 mm (RTK-quality, ambiguity-resolved)
This is the strongest architectural lever this loop has surfaced for
ADR-029 (multistatic sensing). The current learning-based attention
approach has no provable precision floor; an explicit ToA-then-phase
pipeline sits within 2x of CRLB by Kay's theory.
Composes cleanly with R6:
- R6 gives the spatial sensitivity envelope (40 cm Fresnel at 2.4 GHz)
- R1 gives the ranging precision within it (1 mm phase, 4 cm ToA averaged)
- Independent, additive, together bound full multistatic geometry budget
Closes a gap R10 created: foliage drops SNR, which directly worsens
ToA CRLB. A 50 m foliage link at 5 dB SNR drops to ~1 m ToA precision.
R10's 100 m sparse-foliage range is *detectable* not *localisable*.
Honest scope:
- CRLB is a lower bound; real estimators sit 1-2x above it
- 5 deg phase noise assumes phase_align.rs is applied
- Multipath degrades CRLB by 2-5x even with MUSIC super-resolution
- Integer-ambiguity (cycle-slip) is unsolved per-subcarrier; needs
multi-subcarrier wide-lane unwrap
Coordination: ticks/tick-9.md, no PROGRESS.md edit.
The workspace DSP (vital_signs, multistatic, pose_tracker, tomography)
implicitly assumes a forward model that maps scatterer geometry to
per-subcarrier phase shifts. Nobody had written it down. This tick
makes it explicit.
Closed-form first-Fresnel-zone radius + point-scatterer path-delta +
per-subcarrier phase prediction over 802.11n/ac 20 MHz channels (52
subcarriers, 312.5 kHz spacing). Pure NumPy demo + JSON output for
downstream consumers.
Headline numbers:
- 5 m link first-Fresnel radius @ midpoint: 40 cm (2.4 GHz), 27 cm (5 GHz)
- Inside zone-1: phase spread <0.5 deg across 52 subcarriers (band-flat)
- Outside zone-1: phase spread up to 16 deg (band-dispersed)
This unifies R5 + R6: R5's experimentally measured band-spread top
subcarriers is exactly what the Fresnel forward model predicts for
zone-1 occupancy.
Closes the loop on three earlier threads:
- R7 (mincut adversarial) gets a precise definition of 'physically
inconsistent' instead of a learned classifier
- R10 (foliage range) needs to retract 100 m sparse estimate to ~70 m
to account for Fresnel-zone obstruction
- R12 (eigenshift negative result) gets its revision basis: PABS over
Fresnel-grounded forward operator
Honest scope: point-scatterer only, first Fresnel only, frequency-flat
reflectivity, LOS-only (no multipath). The scalar version is the right
first-order approximation; volume-integral / multi-zone / multipath
extensions catalogued as R6.1+R6.2 follow-ups.
Coordination: ticks/tick-8.md, no PROGRESS.md edit.
Speculative 10-20y vision thread covering three concrete vertical sketches:
* V1 stress-responsive lighting (5y) — breathing-rate baseline + warm-shift lights
* V2 adaptive HVAC for thermal-stress envelopes (10y) — published HVAC-personalisation 15-20% energy savings
* V3 conversational appliances respecting attention state (15y) — don't interrupt during focused work
Maps existing RuView components to each: 5 already shipped (breathing rate
detector, occupancy gates via cog-pose / cog-count, motion intensity, partial
RollingP95 baseline learner, MCP API via ADR-104), 4 still to build (full per-room
baseline learner, state classifier model, MCP vitals subscribe tool, consent UI).
Ethical framework drafted as binding constraints any product must honour:
1. Opt-in by default — sensing on only after active enable
2. Data stays on-device — per-second values never cross the building boundary
3. Override is one tap — physical kill switch must work without WiFi/cloud
6-row privacy threat model with mitigations: compromised appliance, MCP raw-signal
leak, adversarial poisoning (mitigated by R7 multi-link consistency), long-term
re-identification, insurance/employer access, non-consenting cohabitants.
Honest scope: clinical breathing-rate-as-stress literature is lab-condition adults;
real-home generalisation unproven. R14 is CSI-only (RSSI loses the per-subcarrier
shape needed for shallow-breathing-during-focus signature), bounds rollout to
ESP32-S3-class deployments.
Connections established to R5, R7, R8, ADR-103, ADR-104. Identifies ruview_vitals_subscribe
as the highest-leverage next MCP tool addition.
Coordination: ticks/tick-7.md, no PROGRESS.md touch.
ITU-R P.833-9 vegetation-attenuation model + ESP32-S3 link-budget
solver produce bounded sensing range estimates per frequency and
foliage density. Plus a biomechanics-grounded gait-frequency taxonomy
spanning bears (0.5 Hz) to mice (15 Hz).
Headline ranges (121 dB link budget, 10 dB SNR margin):
freq sparse moderate dense
2.4 GHz 99.6 m 12.0 m 4.1 m
5 GHz 19.9 m 5.2 m 2.1 m
The 2.4 GHz / sparse cell (~100 m) is the practical sweet spot —
10x camera-trap coverage, always-on rather than PIR-triggered.
Honest scope called out explicitly: this is feasibility math, not
field measurements. Animal cooperation, foliage flutter, regulatory
limits, and BSSID-fingerprint degradation in remote forest are all
real follow-up problems.
Vertical applications (10-20 year horizon) catalogued:
- Endangered-species population census
- Wildlife corridor verification
- Invasive-species early warning
- Anti-poaching (human gait well-separated from wildlife)
- Livestock-on-rangeland tracking
- Agricultural pest control
Cross-connects to:
- R5 (saliency is task-specific — per-species classifier needs own
saliency map, same lesson as R12)
- R8 (wildlife sensing wants CSI not RSSI for per-subcarrier shape)
- R9 (fingerprint K-NN primitive transfers to per-individual ID)
- R7 (multi-link consistency for corridor coverage)
Pure-NumPy, no framework deps. ITU model + binary search solver.
Coordination: tick avoided PROGRESS.md to prevent races (horizon-
tracker M3+ track concurrent at the time).
Files:
* examples/research-sota/r10_foliage_attenuation.py
* examples/research-sota/r10_foliage_results.json
* docs/research/sota-2026-05-22/R10-through-foliage-wildlife.md
* docs/research/sota-2026-05-22/ticks/tick-6.md
ruv