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* docs(tutorials): add Pi 5 + Hailo cluster rvcsi tutorial
Field-tested walkthrough for building a 4-node Raspberry Pi 5 + 2×
Hailo-8 multistatic Wi-Fi CSI cognitive RF observer using rvcsi. Built
against the v0-appliance v0.5.0-cognitive-rf-observer milestone — 446k+
observed fingerprints, 16 stable RF states, 2nd-order Markov running at
39% top-1 ceiling (1.06× over 1st-order, 16× chance baseline).
Covers:
- Pi 5 + Hailo hardware bring-up (BOM ~$580 + workstation)
- nexmon_csi native ARM build recipe (cross-compile is a dead end)
- Per-node services + per-host topology (15 expected services across 4 hosts)
- Workstation pipeline: 3 daemons + 7 timers, brain HTTP + SQLite
- 12 brain categories from spatial-vitals through rfmem-fleet
- cog-query CLI: 34 subcommands, 4 JSON modes, --post for 2
- Calibration recipe: walk → cluster → warm-start IDs → Markov chain
- 13-axis anomaly detector w/ composite info score (1.0–8.0)
- Fleet-health triad: check-drift + replica-status + fleet-status
- Troubleshooting table for the painful lessons (clock skew, cp -r footgun,
self-loop dominance in Markov argmax, etc.)
Pairs with a detailed cookbook gist (linked from intro + steps 3, 4,
and the Reference section):
https://gist.github.com/ruvnet/88e7b053c41cb4f4af7a7ec4af873017
Co-Authored-By: claude-flow <ruv@ruv.net>
* docs(tutorials): clarify rvcsi naming + add ADR-207 cutover note
Two amendments per ADR-207's "naming defect — fix immediately regardless"
action item:
1. Intro callout: when the tutorial was first written, "rvcsi" was a
naming convention only (no upstream library dep). As of 2026-05-13
the v0-appliance accepted ADR-207 Option D and shipped a Rust
binary built on the real rvcsi-runtime. Both stacks can coexist on
a mixed cluster during cutover.
2. Per-node services section: explicit note that cog-csi-emitter +
cog-csi-adapter + cog-rvcsi-stream are being consolidated into one
cog-rvcsi-pi Rust binary, with deploy + rollback commands and
scope (per-Pi cutover, mixed clusters OK).
The tutorial's overall instructions remain correct for both pre- and
post-cutover deployments — fleet-status, the operator surface, and
the architectural model are unchanged.
Co-Authored-By: claude-flow <ruv@ruv.net>
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| cognitum-seed-pretraining.md | ||
| pi5-cluster-cognitive-rf-observer.md | ||