docs: add WiFlow reproduction protocol (#1787)

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rUv authored and GitHub committed 2026-09-05 09:42:43 -04:00
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# WiFlow Reproduction Protocol
Status: Proposed research protocol
Tracks issue #1786.
## Objective
Determine whether a CSI optical flow style representation improves reusable camera free motion intelligence in RuView rather than only improving a proxy flow metric.
## Required capture metadata
Every run records hardware family, firmware, antenna count and geometry, channel width, center frequency, packet rate, timestamp source, synchronization method, room identity, participant identity class, label source, calibration, packet loss, missing subcarriers, preprocessing version, model commit, accelerator, software versions, power mode, and random seeds.
## Baselines
1. current RuView CSI preprocessing plus strongest task specific sensing head
2. WiFlow style motion field representation
3. simpler temporal derivative or phase and amplitude motion baseline
All conditions use identical train, validation, and held out environment splits.
## Metrics
Primary intermediate metrics:
* endpoint error or equivalent flow error
* directional consistency
* temporal stability
* uncertainty calibration
Required downstream metrics:
* tracking quality
* occupancy or presence quality
* pose or activity metric where available
* spatial state consistency in RuField or WorldGraph
Systems metrics:
* p50 and p95 inference latency
* peak memory
* CPU, GPU, or accelerator utilization
* energy per inference where measurable
* bytes per observation and sustained bandwidth
## Stress tests
Test unseen rooms, unseen participants, changed antenna geometry, a second RF hardware family, packet loss, burst loss, missing subcarriers, lower packet rate, clock jitter, and partial calibration failure.
## Promotion gate
The representation graduates only when the same learned representation improves at least two downstream RuView tasks on held out environments, or reaches equivalent downstream quality with materially lower edge cost.
A better optical flow proxy score alone is insufficient.
## Security and privacy
Visual or LiDAR labels may be used as privileged training evidence but must not become a runtime dependency for camera free deployment claims. Dataset provenance and consent requirements remain explicit.
## Rollback
The experiment is isolated behind a representation interface. Existing RuView sensing heads remain the production fallback.