* feat(firmware): add the 16MB flash profile the C6 fleet runs on
The 4MB and display layouts have 1.875MB and 2MB OTA slots, sized for 4MB
and 8MB parts. A 16MB C6 (DevKitC-1 N16) has no layout in the tree at all,
so building for one meant hand-editing sdkconfig -- and a smaller table
written over a deployed 16MB node relocates NVS and destroys its
provisioning, which is why this belongs in the repo rather than in a
workstation's untracked sdkconfig.
Two 4MB OTA slots, plus a 64K coredump partition and an 8000K FAT volume
for on-node storage. Rollback is enabled so an OTA'd image that cannot
confirm itself is reverted by the bootloader.
Layered, not inherited: sdkconfig.defaults.esp32c6 keeps its 4MB layout so
the common 4MB devkit is never silently repartitioned.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01PVWMiHQifoYXL7uL3bphrZ
* feat(firmware): persistent on-node log and coredump-to-flash
A remote fault currently leaves no post-mortem. main.c decodes the reset
reason at boot and logs it to the CONSOLE -- which is exactly what a power
cycle destroys, and a power cycle is how a wedged node gets recovered.
The flash was already provisioned for this and the features were simply off:
partitions_16mb.csv has reserved a 64K `coredump` partition and an 8000K
`storage` FAT volume since the 16MB layout was written, neither had ever been
mounted or written, and the build defaulted to CONFIG_ESP_COREDUMP_ENABLE_TO_NONE.
- node_log.c/h: a 128 B-record ring on the storage volume. Boot records
(reset reason + the previous session's final uptime + a health snapshot),
periodic health samples, and event records. Ordering is boot_id + uptime_s
because these boards have no RTC and nothing can be timestamped absolutely.
Counters are stored RAW and differenced at read time, so a cadence change
never invalidates old records. Retention, not wear, binds: 128 B every
300 s is ~208 days in 8 MB, and the write rate is bounded explicitly.
- ap_rssi_dbm, the association link from esp_wifi_sta_get_ap_info. The
adaptive controller's rssi_median_dbm is a CSI statistic, not the uplink,
so a node with a bad uplink currently shows no signal for it anywhere.
- CONFIG_ESP_COREDUMP_ENABLE_TO_FLASH, complementary rather than a
substitute: a coredump catches a CRASH, the boot record catches a HANG
followed by a watchdog reset.
node_log_init failing is non-fatal by design -- the module disables itself
and every entry point becomes a no-op. A logging volume that will not mount
must never take the fleet down with it.
csi_collector gains two gate accessors. This build selects its frame gate at
compile time, so both return CSI_GATE_NOT_CONFIGURABLE rather than a
plausible number: the log keeps a field of fixed width and meaning either
way, and an explicit "not applicable" is stored instead of something a
reader would later reason from as a real setting.
Built with ESP-IDF v5.4 for esp32c6 using
defaults + .esp32c6 + .16mb. Verified from the resulting artifacts: 16MB
table with coredump and storage present, COREDUMP_ENABLE_TO_FLASH set,
rollback enabled, image 0x10abd0 bytes in a 4M slot. NOT flashed to hardware
from this branch -- the equivalent code was exercised on a node-3 pilot, but
that is not evidence for this build.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01PVWMiHQifoYXL7uL3bphrZ
* docs(adr-362): reading the on-node log is on-demand, never streamed
The log engine lands with no consumer, so the access pattern was open. Records
the decision to pull a node's log only when a human asks -- after a hang or a
crash, or while troubleshooting that node -- and to keep nothing server-side.
The reasoning that decided it: the ring already survives a power cycle on the
node (~208 days of retention), so a server copy duplicates a durability
property that is already met; and airtime is this fleet's binding constraint,
measured at 91% consumed by two slow nodes, so a periodic drain across nine
boards would spend exactly the resource whose exhaustion you would open the
log to investigate. An instrument must not perturb what it measures.
Leaves the decode-where question open on purpose, with the argument for a raw
proxy stated: decoding server-side defines the record layout in both C and
Rust, and the pilot already paid once for a host/firmware disagreement about a
field's meaning.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01PVWMiHQifoYXL7uL3bphrZ
---------
Co-authored-by: Joe <joe@GitDev.hedgehog>
Co-authored-by: claude-flow <ruv@ruv.net>
A-B-A capture from the overnight run, ten 30 s windows per arm: pairing
fraction rises 0.5668 -> 0.7287 (Welch t=13.26, p<0.0001) when the fleet is
filtered to one transmitter, but paired observations/s falls 44% because
tx/s falls 56%. Fraction was the wrong figure of merit; not adopted.
Firmware changes (persistent on-node log, live filter_mac, and the node-3
pilot fixes) that produced this capture are held back pending a port against
main's restructured firmware/main/ tree (config_api.c and ota_update.c are
gone there).
Claude-Session: https://claude.ai/code/session_01PVWMiHQifoYXL7uL3bphrZ
Co-authored-by: Joe <joe@GitDev.hedgehog>
Co-authored-by: claude-flow <ruv@ruv.net>
Records why device-free position kept failing here, measured rather than
argued, and the join key built in response. The implementing PRs land without
this and are harder to read for it.
**Phase is unusable on this hardware.** The bistatic tier needed a signed
per-link radial velocity, which requires the common-mode component of CSI
phase. Measured across three ESP32-C6 nodes over ~40,000 frames, the
frame-to-frame change in common-mode phase is statistically indistinguishable
from uniform random: resultant length R = 0.011-0.032 against a 0.000
reference, sd 1.78-1.81 against pi/sqrt(3) = 1.814, no lag-1 autocorrelation.
A second, unwrap-free estimator agreed.
The mechanism is packet-detection timing quantization. Common-mode phase is
-2*pi*f_c*tau, and one ADC sample of jitter at 20 MHz is about 758 rad -- some
120 full wraps, re-randomized every packet. Not calibratable. The bistatic tier
is default-off as a result.
**Amplitude works but had no parallax.** The three AP->node links leave a single
distant transmitter inside a 36.5 degree fan; scalar per-node energy weighting
closed with a clean negative result -- magnitude responds to proximity,
direction does not.
What follows from both: a position tier needs several transmitters seen from
several receivers, and fusing those requires knowing that two nodes observed
the SAME transmission. Arrival timestamps cannot say so -- the sink sees network
jitter, not capture time -- and the per-node sequence counter is private to each
node. Hence (tx_mac, rx_seq): the 802.11 sequence control field is assigned by
the transmitter and is identical at every receiver, so it names one
transmission without any coordination between receivers, no shared clock and no
negotiation.
Status is Proposed, deliberately. The measurement layer is implemented and
validated on hardware; localization is NOT built, and the ADR says so along
with the rest of its known limitations -- peer links are ~10x weaker than data
frames, three links is below the threshold for tomographic localization
regardless of quality, and no position tier consumes the link table.
References only ADR-018, ADR-060 and ADR-110, all already present here.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01BHNNWbmKvxXrVaEDwXEBNo
Points v2/crates/ruforecast at ruvnet/RuForecast@a802067f, the tip of
fix/governance-and-spend-enforcement (ruvnet/RuForecast PR #2), which closes
14 code-review findings against the training stack merged as #1766 -- most
critically, ADR-349's governance-verification and spend-approval-record
requirements were specified but never actually enforced by the fal.ai
hosted path; they are now.
Adds ADR-354 recording this as a RuView-level integration decision and
pointing to the submodule's own ADR-350 for the full technical record,
since that repository is now the source of truth for the forecast
subsystem's decision history.
Depends on ruvnet/RuForecast#2 merging with green CI first; see that PR for
status before merging this one.
Trains a real fal.ai LoRA fine-tune (fal-ai/flux-lora-fast-training) on
frames extracted from the real fal.ai-generated room-visualization MP4s
already captured this session, so display-layer generation has a specific
trained style target instead of prompt engineering against a stock model.
Architecture boundary: this model only ever produces supplementary
synthetic visual/pixel output. It has no path into measured/derived RF,
pose, vitals, identity, or confidence values, which remain local and
authoritative.
Real run: request 01a060b2-c940-7972-abf9-ea48847eb2ae, 1000 steps, 27
training images, ~$2.04 spend, validated with a real inference call
against the trained LoRA (assets/fal-visual-teacher-sample.png).
* feat(forecast): add independent Rust training stack
Signed-off-by: Codex <codex@openai.com>
* docs(forecast): record informal HPO exploration note (unaccepted)
Records an exploratory Darwin Mode numeric-genome hyperparameter search
against the tiny_ci synthetic accuracy protocol: WQL improved 0.257 -> 0.161
-> 0.153 over two search rounds, staying ahead of both baselines throughout.
Explicitly scoped as informal/exploratory (not a frozen leakage-free report,
not eligible for the evidence ledger, not validated for large_linux or any
real dataset) per this doc's own evidence-tagging discipline.
* feat(forecast-core): add per-horizon weighted quantile loss
weighted_quantile_loss collapses the whole horizon into one aggregate
number, hiding whether error grows with lead time. Add a sibling
function using the identical per-cell pinball formula and domain
checks, just reduced per horizon step instead of globally. A unit
test reconstructs the aggregate from the per-step numerators/
denominators to prove the two functions agree exactly, not just
approximately.
* feat(forecast-model): add evaluation-only local activation
Adds activate_for_evaluation and build_eval_input, gated behind the
cpu feature. activate_for_evaluation self-signs an unsigned candidate
with a fixed, publicly-known, non-secret Ed25519 key so a CLI operator
can run inference against their own just-trained candidate without a
real release signature -- explicitly never a production trust path,
documented as such in the module doc comment. The schema-digest check
in ArtifactActivationPolicy still applies in full; only signing is
relaxed. build_eval_input constructs a single-window ModelInput for
CPU inference from raw context-major values/mask arrays, matching the
training batch builders exact time-feature/descriptor encoding.
Six unit tests cover: malformed-candidate rejection, digest-mismatch
rejection (proving the schema check has teeth even on this relaxed
path), getting past the policy gate with a matching digest, and
eval-input shape validation.
* feat(forecast-train): add evaluate and prepare-synthetic-dataset CLI
Turns this sessions throwaway HPO scripts into real, tested CLI
surfaces, replacing two example binaries that bypassed the CLI/TOML
training path entirely.
prepare-synthetic-dataset generates a larger, configurable synthetic
training shard (default 24 windows) plus a matching train-local.toml
with the given OptimizerSpec hyperparameters baked in, and a separate
held-out test.jsonl -- the same synthetic-only, local-validation-only
posture as prepare-local-example, just bigger and configurable.
evaluate scores a trained (unsigned) candidate against held-out
windows and the LastValue/SeasonalNaive baselines: overall weighted
quantile loss, a per-horizon breakdown, 80% interval coverage, and
missingness, for the model and both baselines. Explicitly lists what
docs/benchmarks/ruforecast.mds full accuracy protocol additionally
asks for that this does not cover (abstention coverage, selective
risk, site/device slices, interference regime, RuVector-retrieval
ablation) rather than silently omitting them -- each needs
infrastructure a single-entity synthetic fixture does not have.
Together the three real commands (prepare-synthetic-dataset,
train-local, evaluate) reproduce the exact WQL numbers the old
library-bypassing example scripts produced for the same
hyperparameters, confirmed by re-running the harness/ruview HPO
dry-run end to end against the new CLI path.
New integration test trains a real candidate via smoke, evaluates it
against held-out synthetic windows, and asserts the full report shape
and an empty-input rejection.
* feat(forecast-train): add prepare-synthetic-dataset --seed + Autogenous bridge
--seed (default 0, backward compatible) makes prepare-synthetic-dataset's
generator deterministic per offset: same seed -> byte-identical corpus
across runs (needed to train two genomes on the SAME corpus for a fair
comparison); different seeds -> genuinely independent corpora (needed for
honest multi-seed/multi-judge evaluation upstream, both in
harness/ruview/flywheel/ruforecast/gate.mjs's fitness function and in the
new v2/crates/ruforecast-autogenous-bridge crate added here).
ruforecast-autogenous-bridge is a LOCAL-DEV-ONLY (excluded from the v2
workspace, publish = false) bridge from this crate's real evaluate CLI
into ruvnet/autogenous's new regression-candidate promotion path (separate,
unpushed branch feat/regression-candidate-kind): runs N independent
train+evaluate judges on genuinely distinct synthetic corpora, signs
receipts, and gets a real cryptographically-verified PROMOTE/REJECT
decision -- defense in depth on top of, not a replacement for, Darwin's own
promotion gate. Path-depends on a sibling autogenous checkout that does not
exist in CI; build/run directly via `cargo build --manifest-path
crates/ruforecast-autogenous-bridge/Cargo.toml`.
cargo test -p ruview-forecast-train --no-default-features --features
cpu,cli: all green (unaffected existing tests + this backward-compatible
addition).
* docs(forecast): retract round-2 HPO result, record honest multi-seed finding
The earlier "Informal HPO exploration note" claimed a real improvement
(WQL 0.257 -> 0.153) from a 3-round hyperparameter search. That search
evaluated every candidate against one fixed synthetic corpus (seed 0) for
every round -- textbook overfitting. Independent verification against two
fresh corpora (via the new ruforecast-autogenous-bridge crate) showed the
"winner" losing to the baseline on both.
Fixed the root cause in harness/ruview/flywheel/ruforecast/gate.mjs:
candidates are now scored against three independent corpora, worst-case
across them, not one fixed corpus.
Re-ran the search under the fix. It found a new winner that genuinely beat
baseline on all three of its own search seeds -- and that winner ALSO lost
independent verification on fresh seeds. Two independent search rounds,
pre- and post-fix, both produced an illusory "winner." The honest reading:
at this dataset scale (24 synthetic windows) held-out WQL varies enormously
by which corpus is drawn, regardless of hyperparameters -- confirmed
directly by the baseline genome's own primary swinging from 0.83 to a full
regression across the three fixed search seeds with unchanged
hyperparameters. No RuForecast hyperparameter configuration has been shown
to reliably beat the trivial baselines out-of-sample at this scale.
Also fixes a real design inconsistency surfaced by this exploration: the
Autogenous regression-candidate promotion verifier
(envelope::regression::verify_regression_promotion, separate unpushed
ruvnet/autogenous branch feat/regression-candidate-kind) required all
judges to share one corpus_id, which conflicts with this kind's
intentional cross-corpus judge design. Corrected there (commit bfa4c48);
did not change either REJECT verdict, which were already driven by the
real NotBetterThanParent signal on their own.
Append-only: the original round-2 row is kept, read together with this
new amendment section, per this doc's own evidence-ledger discipline.
* refactor(forecast): extract RuForecast to ruvnet/RuForecast submodule
Mirrors the v2/crates/worldgraph pattern: RuForecast becomes its own
independent public repo/workspace (ruforecast-core/model/train), mounted
at v2/crates/ruforecast as a git submodule, with v2/Cargo.toml path-depping
into its sub-crates and excluding the submodule from the v2 workspace.
Full v2 --workspace check passes; the ruforecast CLI builds and runs
correctly from its new location. Real git history for the extracted
crates (7 commits) was preserved via git-filter-repo, not squashed.
* feat(autogenous-bridge): real-data independent verification tool
real_data_verify.rs: signs two real, temporally-independent judge
measurements (different train/test split boundaries on the same real
household vitals corpus, not synthetic seeds) through the real
Autogenous regression-candidate promotion path, and gets a genuine
cryptographically-checked PROMOTE/REJECT verdict.
Result recorded (see docs/benchmarks/ruforecast.md): REJECT. One judge
nominally beat the trivial baseline but by less than the 0.01
non-inferiority margin; the other judge lost outright. Consistent with
every synthetic-data search this session -- no configuration has yet
been shown to reliably beat trivial baselines out-of-sample, now
including a real 6390-sample household corpus.
Bumps the ruforecast submodule to pick up the evaluate real-gap fix.
* docs(forecast): record real-household-data result (REJECT, signed)
6390 real vital-signs samples, two independent temporal splits,
independently verified via the real Autogenous regression-candidate
promotion path. Signed verdict: REJECT -- neither split cleared the
non-inferiority margin. Same conclusion as every synthetic search this
session, now confirmed with real data too: more real data is the
credible next lever, not further search on this scale of fixture.
* chore(forecast): point ruforecast submodule at published main (post gap-tolerance fix)
* ci(forecast): fix ruforecast-ci.yml for the new v2/crates/ruforecast submodule layout
The RuForecast crates were extracted into a standalone submodule (v2/crates/ruforecast, mirroring the existing v2/crates/worldgraph pattern) and are no longer members of the v2 workspace. The CI workflow still referenced the old in-tree package names/paths (ruview-forecast-core/model/train under v2/), which broke every forecast job with "cannot specify features for packages outside of workspace".
Fixed every job to target the submodule: working-directory -> v2/crates/ruforecast, -p ruview-forecast-* -> -p ruforecast-*, all hardcoded Cargo.toml/source paths in the Python assertion and clean-room-scan blocks, the Swatinem/rust-cache workspaces input, the artifact-tree output paths, and the two levels of relative path (../ -> ../../) in the informational-benchmark steps whose working directory moved one level deeper.
Also collapsed the paths: trigger filters internal-crate globs (v2/crates/ruview-forecast-*/**) down to the single v2/crates/ruforecast path, since GitHub Actions path filters only ever see a submodule gitlink change as one entry in the parent tree, never its internal file paths -- the old globs could never have matched anything.
Includes a real cargo fmt fix (submodule commit d9902f9) for formatting drift left over from the earlier real-data gap-tolerance fix, which the contract job's fmt --check step would otherwise have failed on.
All four forecast CI jobs' real commands verified locally before push: cargo test/check for CPU, CUDA/WGPU compile-check, the contract job's Python assertion block, the hosted-boundaries clean-room scan, and cargo fmt --check.
* docs(forecast): record real BIDMC cross-entity holdout result (REJECT)
Two independent real-patient partitions (34/16 and 24/26 splits, 53 total
ICU patients from PhysioNet BIDMC, Open Data Commons Attribution License
v1.0) both show the model losing to trivial baselines by a decisive margin
(+69% and +601% worse WQL). First genuine cross-entity real-data test this
project has run; same conclusion as every prior synthetic and single-household
test. Full Autogenous signed verification was not run for this entry -
flagged explicitly in the note.
* chore(forecast): point ruforecast submodule at published main (example feature-gate fix)
* chore(forecast): point ruforecast submodule at published main (clippy fix)
---------
Signed-off-by: Codex <codex@openai.com>
ADR-262 §8 question 5 left the second modality open, asking whether it should
be rvcsi. This answers ultrasonic instead, because the cost collapsed:
rufield-adapters now ships UltrasonicReplayAdapter, the first adapter for
Modality::Ultrasonic (registry code 7, empty since v0.1), which parses,
validates and signs BatVu range profiles upstream. RuView only has to decide
what it will put on a wire.
Bumps vendor/rufield 43b1df3 -> 9955672. Two struct literals in bridge.rs gain
fields added upstream (Observation: track_id, attributes, identity_evidence,
channel_sounding_provenance; SensorDescriptor: coordinate_frame, position_m,
orientation_xyzw). All left empty, each for a stated reason rather than a
convenient default — the pose fields in particular, because a CSI link has no
boresight and §6 makes no validated room-coordinate claim. The nine existing
P1 gates pass unchanged.
The decision this module makes is structural rather than a runtime refusal.
The adapter's full per-bin frame is P0 and would be dropped by the egress gate
after all the work of parsing and signing it; its 32-bin coarse reduction is
P1 and egress-safe. So the module does not offer the choice — it configures
the coarse mode, because a consumer cannot un-coarsen a coarse profile whereas
a check can be reordered. The gate still runs and is asserted to drop nothing.
12 gates in tests/ultrasonic_gates.rs, including the honest negative result: an
ultrasonic scan produces no fused inferences at all, and both independent
reasons are pinned. The adapter declines to populate `presence` — one
transducer pair cannot distinguish a person from a coat over the back of a
chair — and the engine's feature vocabulary is entirely statements about a
body, so range_m has nothing to drive.
The fixture is BatVu's own emitter output, byte-identical to the one in
ruvnet/rufield, so schema drift fails a build in one of three repositories
rather than an ingest in a deployment.
Not wired into the running server; P1 shipped as a library before P3 wired it
in, and this follows the same staging.
New leaf crate v2/crates/ruview-offaxis implementing ADR-324's projection
core from the published math only (Kooima 2008 generalized perspective
projection; Casiez 2012 one-euro filter) — no code from the unlicensed
prior-art repo. Dependency-free native core; wasm-bindgen surface gated to
wasm32 (cdylib+rlib, ~54 KB wasm after bindgen).
- projection: Screen (3 corners, any orientation) + off_axis() -> typed
errors, never NaN matrices; column-major f64 (three.js Matrix4 layout).
Tests pin the defining invariants: screen corners -> NDC corners for a
grid of eye positions and tilted screens; screen-plane points are
eye-invariant; centered eye reduces to the symmetric frustum; near/far
map to NDC -1/+1.
- filter: one-euro with injected timestamps (no clock in crate);
monotonicity/convergence/NaN-rejection tests.
- rf: field-peak extraction mirroring field_localize.rs constants
(X_SCALE 0.6, Z_SCALE 0.5, PEAK_THRESHOLD 0.35) and the Tier B
coarse-parallax stage (deadband, gain, hard clamp) so over-claiming is
impossible at the API level. No accuracy numbers asserted.
- wasm: OffAxisCamera + RfParallax bindgen classes; per-frame updates hold
last good state instead of throwing.
- benches (criterion): full Tier B frame ~598 ns; argmax scan optimized
-18%/-33% (20x20/100x100). MEASURED table + reproducer in README.
- examples/three.js/demos/07-off-axis-window.html: demo with SYNTHETIC
mouse simulator and labeled RF Tier B mode ('coarse body parallax - not
head tracking'), physical calibration panel, /ws/sensing input, and a
build-instructions overlay when the local pkg/ output is missing
(generated artifacts stay uncommitted; .gitignore entry added).
- Validated 23 unit tests + doctest, clippy clean, wasm32 release build,
Node smoke test of the bindgen output, and a headless-Chromium run of
the demo (engine load, eye response, mode labels, ws failure path).
- ADR-324: header + section 2.5 amendment recording the Rust/WASM core.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01BU3NcEgTpAVvu5QGtw4czT
Deep-research ADR answering whether icurtis1/off-axis-sneaker can be used
with RuView. Adopts the head-coupled perspective technique (Kooima
generalized off-axis projection) via a clean-room implementation — the
upstream repo is unlicensed, so no code or assets are reused. Defines a
tiered integration: webcam-fine tracking with RF presence gating and
multi-person arbitration (Tier A), an explicitly labeled RF-only coarse
body-parallax mode (Tier B), and evidence-gated future metric RF head
positioning (Tier C). No server changes; existing /ws/sensing and
/api/v1/stream/pose streams only. Indexed in the ADR README.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01BU3NcEgTpAVvu5QGtw4czT
Fix breathing confidence, Windows desktop launch and clean UI builds, contributor-harness line-ending integrity, runtime secret hygiene, and remove the six ADR-299 CSI/person-data files from the current tree.
The higher-ceiling primitives on the fused world state. Six crates, all
deterministic SYNTHETIC/L0 model scaffolds (a twin predicts, it never measures);
70 tests + 6 doctests, verified green independently.
ruview-twin (ADR-312): per-deployment RF twin — radio geometry, a documented
synthetic log-distance + wall-attenuation propagation model, per-link expected
distributions, and the load-bearing delta(observed,expected) that localizes a
physical change (moved node / new reflector) to specific links. 8 tests.
ruview-infogain (ADR-311): Value(sensor) = expected uncertainty reduction /
weighted cost; pure bounded-greedy selection under a multi-dimension budget;
unknown-value candidates handled explicitly (defer/probe, never silent zero). 15.
ruview-active (ADR-306): closed-loop control vocabulary (channel/bandwidth/
cadence/antenna as validated ranges); step() proposes the next measurement to
reduce uncertainty, widening exploration when the last response is UNKNOWN;
emits a plan, never RF. 13.
ruview-placement (ADR-305): floorplan + inventory -> ranked placement via the
twin's propagation model; blind-spot flags; predicted-vs-observed adjustment. 11.
ruview-memory (ADR-309): learns per-zone normal physics; anomalies are
significant deltas vs baseline emitted as evidence records; UNKNOWN before a
baseline exists (no false positives). 14.
ruview-counterfactual (ADR-310): scores hypotheses under the twin — empty-room
vs occupied, one person vs two; UNKNOWN when indistinguishable. 8.
Flips ADR-305/306/309/310/311/312 to implemented. Completes all three phases of
the ADR-297 perception-substrate program. No hardware/MEASURED claims.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_015TcKegTS7QqhWPC2L2SzaS
The layer that turns the certificate spine into a modality-agnostic perception
substrate. Four crates, all deterministic and green independently (43 tests).
ruview-hal (ADR-317): one abstraction mapping any modality (CSI/802.11bf/BLE/
UWB/mmWave/acoustic/camera/lidar/IMU/custom) to a canonical ontology Observation.
SensorHal trait + two SYNTHETIC/L0 reference adapters; malformed input yields a
degraded UNKNOWN observation, never a panic; synthetic can never alias measured.
8 tests.
ruview-groundtruth (ADR-300): reference sensors as a formal VALIDATION plane
(never an estimator input, enforced by the type boundary); modality-agnostic
ReferenceSeries, deterministic cross-correlation alignment, AgreementReport with
mandatory SessionScope, emitting per-context ruview-evidence records; Measured
requires reference + coverage + reproducer. 15 tests.
ruview-track (ADR-304): privacy-preserving persistent tracks (opaque person ids,
coarse non-reversible features, no civil-identity binding); ambiguous detections
stay tentative rather than misassigned; cross-zone hand-off. 8 tests.
ruview-fusion (ADR-308): multiple HalObservations -> one probabilistic WorldState,
uncertainty-aware (confidence-weighted, not naive averaging); irreconcilable
conflict or insufficient coverage yields UNKNOWN, not a confident average.
9+ tests incl. irreconcilable_conflict_yields_unknown.
Flips ADR-300/304/308/317 to implemented; registers the four crates as workspace
members. SYNTHETIC/L0 throughout; no hardware/MEASURED claims.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_015TcKegTS7QqhWPC2L2SzaS
Elevates decision policy (action authorization) into phase 1 (ADR-318): a
fail-closed gate that authorizes a governed action only when the capability
certificate class, freshness, uncertainty ceiling, evidence floor, and live
domain state (KNOWN, not DEGRADED/UNKNOWN) all satisfy the action class —
convenience vs security vs safety-critical. UNKNOWN denies high-assurance
actions; every decision is the terminal witness-chain stage.
Amends ADR-297 with: the epistemic-reliability pipeline as the product thesis;
four non-negotiable rules (UNKNOWN first-class; certificates bind
cryptographically; one canonical downstream semantics; benchmarks expose
worst-domain + CIs); the certificate-staleness guard (certificates conditional
on a continuously evaluated domain signature; VALID->DEGRADED->UNKNOWN
auto-degrade triggers recalibration); the three-primitive commercial framing
(Runtime / Certify / Trust-Fleet); and acceptance test B (drift invalidation
before a false inference reaches an actuator).
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_015TcKegTS7QqhWPC2L2SzaS
Frames the calibration/evidence/trust/deployment layer as a 20-primitive
phased program with a dependency DAG and phase assignments. Phase 1 is the
certificate spine (spatial ontology, authenticated identity, witness chain,
calibration cert, OOD gating, evidence engine, capability certificate,
multi-domain benchmark scorecard) — the acceptance test decomposed and
buildable without new hardware. Phase 2/3 are integration and research-forward
primitives. Child ADRs 298-317 follow.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_015TcKegTS7QqhWPC2L2SzaS
Turns the review's code-implementable P0/P1 items into ADRs: source
provenance state machine (synthetic never presents as live), UDP data-plane
bind hardening (loopback default + allowlist, step one), multi-node semantic
correctness (per-node inference, node-keyed rate limiter, stale state), model
release sanity gates (block degenerate/mislabeled heads), and CSI data-incident
repo controls. Also fixes the stale .gitignore rule so the active recordings
directories and CSI globs are covered going forward.
Tree removal of existing recordings, history rewrite, and withdrawal of the
published presence head are gated on maintainer sign-off (outward-facing /
destructive) and intentionally not done here.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_015TcKegTS7QqhWPC2L2SzaS
Adds wifi-veil (pinned git rev, dependency-free, MIT/Apache-2.0) to the
workspace and gates it behind a new 'veil' feature in wifi-densepose-bfld.
The bfld::veil module exposes deterministic attacker-vs-protector shield
assessments (re-ID collapse, throughput ratio, energy-conservation audit)
with a mandatory SYNTHETIC/L0 evidence label. Advisory only: no RF
emission, no frame mutation, BFLD invariants I1-I3 untouched. Default
build unchanged; 6 new feature-gated tests pass.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_015TcKegTS7QqhWPC2L2SzaS
Three ADRs closing the highest-impact gaps from the 2026 SOTA research
sweep: public-benchmark comparability (Widar3.0 ingest + leakage-guarded
split protocols), wideband 802.11ax CSI ingest (FeitCSI/AX210), and a
vitals ground-truth rig (reference ingest, alignment, Bland-Altman
agreement, evidence grading). Implementations follow in this branch.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_015TcKegTS7QqhWPC2L2SzaS
Take VEIL from the synthetic Rust reference model toward real WiFi silicon
across multiple hardware providers, around one shared, host-validated core.
Answers the questions "can OpenWRT / open WiFi software implement this?" and
"can ESP32 help scramble signals?" with an honest per-platform feasibility map.
Portable C shield core (firmware/privshield/core/) — VALIDATED (host test):
- veil_shield.{h,c}: keyed Givens-rotation obfuscation of the identity-bearing
"fine" subspace, C99, no malloc / no libc I/O, only <math.h>. SplitMix64 key
schedule byte-identical to the Rust crate, so on-air behavior is consistent
everywhere and every adapter links the same math.
- make test passes: energy conservation (orthogonal => "not jamming"),
reversibility (recover inverts apply), wrong-key-fails, and PRNG stream parity
with the Rust crate. This is build/host evidence, NOT silicon.
Per-provider adapters (all SYNTHETIC / L0, build-only, TODO(hw) markers):
- openwifi/ grade B (ceiling A, effort D): only open PHY/MAC (FPGA) that can
host the full keyed rotation + inverse; needs new HDL + 2nd TX chain. Carries
the P5 measurement protocol (MEASUREMENT.md) for the first MEASURED result.
- openwrt/ grade C: per-packet keyed unitary is blob-blocked on commodity APs;
coarse compliant knobs (TX antenna map, sounding-cadence jitter) reachable
from userspace/hostapd; ath9k is the one credible driver-patch route.
- nexmon/ grade C: reading the compressed-BF angles is solved (nexmon_csi /
Wi-BFI); shaping the transmitted report is research-grade (D11 ucode-adjacent).
- esp32/ grade F (self) / B (supporting): cannot shape its own BF feedback
(closed esp-phy-lib blob); legitimate as a sensing detector and external-RIS
controller — the honest way ESP32 "helps scramble", via an external surface.
Docs:
- firmware/privshield/README.md: architecture, layout, and the feasibility matrix.
- ADR-290: the E2E hardware program, PROOF discipline, and per-provider decision;
added to docs/adr/README.md index.
Compliant waveform controls only, never jamming. No adapter has run on silicon;
no MEASURED claim is made (that is roadmap P5, gated on a captured log).
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01WEXNqzs7UsfNFBcP5yW21p
A dependency-free native binary (`src/bin/veil.rs`) — the in-repo counterpart to
the npm metaharness — that drives the same crate API the tests use:
- Interactive ANSI dashboard (TUI): live status, re-ID off/on vs chance,
throughput, compliance (energy 1.000× / not jamming), a block-sparkline
collapse curve, config, and PASS/OUT-OF-SPEC verdict. Command-driven redraw
loop (std-only, no crossterm/ratatui): on/off, passes/bits/n/snr,
metric euclid|cosine, preset scif|board|ward|hotel, optimize, proof.
- Scriptable subcommands: report, sweep, optimize, adaptive <N>, proof, doctor
(exit 0 = healthy). Auto-picks TUI on a terminal, one-shot report when piped;
honors NO_COLOR.
Std-only, so it builds with no extra deps and runs in any pipe/CI. The wasm leaf
story is unchanged (validated with `--lib`; the bin is native-only). All
readouts are SYNTHETIC/L0 and never relabeled.
Validated: 38 tests + doctest pass, clippy --all-targets -D warnings clean,
rustfmt clean, wasm --lib builds; all subcommands + a scripted TUI session
exercised. Documented in the crate README and ADR-288.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01WEXNqzs7UsfNFBcP5yW21p
Two additions on top of the hyper-optimized VEIL shield.
1) Adaptive optimization (v2/crates/wifi-densepose-privshield/src/optimize.rs):
- optimal_bits_across_snr / model_optimal_bits_for_snr: the throughput-
optimal feedback resolution shifts with SNR (unconstrained optimum 4 bits
at 5-10 dB, 3 bits at 20-40 dB); within the spec {5,7,9} set it stays 5,
which is why the shipped shield is SNR-stable.
- adaptive_shield / min_passes_for_n: derive a shield for a specific
deployment. Finding: the collapse budget is N-independent in this model
(48 passes collapses N in {8,64} alike) — it is set by the fine-subspace
dimension, not the candidate count. Defaults unchanged, so the proof
witness is untouched. 38 tests + doctest pass; clippy -D warnings clean.
2) npm metaharness harness/wifi-densepose-privshield/ (ADR-289), mirroring
wifi-densepose-sar-harness (ADR-286) with two improvements:
- @metaharness/* imported dynamically inside the commands that need them, so
`guidance` and `--help` run with ZERO dependencies installed (offline / pre
`npm install`).
- a dependency-free VEIL `guidance` command: a source-cited, evidence-
labelled, read-only capability map (topics: overview, threat,
countermeasure, compliance, optimization, experiment).
Standard router + flywheel (SYNTHETIC) + Darwin wiring, tailored to VEIL
task axes and policy levers. Tests: smoke + router + flywheel (need install)
and guidance (offline). .harness manifest generated with real per-file
hashes. Validated offline: cli syntax, --help, guidance topics, exit codes,
graceful degradation when deps are absent.
Docs: research bundle 08 gains a per-deployment adaptivity section; 07 and the
crate README point at the harness; ADR-289 added and indexed.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01WEXNqzs7UsfNFBcP5yW21p
ruv