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rUv 9bbe95648c feat: ADR-024 Contrastive CSI Embedding Model — all 7 phases (#52 )

Full implementation of Project AETHER — Contrastive CSI Embedding Model.

## Phases Delivered
1. ProjectionHead (64→128→128) + L2 normalization
2. CsiAugmenter (5 physically-motivated augmentations)
3. InfoNCE contrastive loss + SimCLR pretraining
4. FingerprintIndex (4 index types: env, activity, temporal, person)
5. RVF SEG_EMBED (0x0C) + CLI integration
6. Cross-modal alignment (PoseEncoder + InfoNCE)
7. Deep RuVector: MicroLoRA, EWC++, drift detection, hard-negative mining, SEG_LORA

## Stats
- 276 tests passing (191 lib + 51 bin + 16 rvf + 18 vitals)
- 3,342 additions across 8 files
- Zero unsafe/unwrap/panic/todo stubs
- ~55KB INT8 model for ESP32 edge deployment

Also fixes deprecated GitHub Actions (v3→v4) and adds feat/* branch CI triggers.

Closes #50

2026-03-01 01:44:38 -05:00

3.9 KiB

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wifi-densepose-wifiscan

Multi-BSSID WiFi scanning for Windows-enhanced DensePose sensing (ADR-022).

Overview

wifi-densepose-wifiscan implements the BSSID Acquisition bounded context for the WiFi-DensePose system. It discovers and tracks nearby WiFi access points, parses platform-specific scan output, and feeds multi-AP signal data into a sensing pipeline that performs motion detection, breathing estimation, attention weighting, and fingerprint matching.

The crate uses #[forbid(unsafe_code)] and is designed as a pure-Rust domain layer with pluggable platform adapters.

Features

BSSID registry -- Tracks observed access points with running RSSI statistics, band/radio type classification, and metadata. Types: BssidId, BssidObservation, BssidRegistry, BssidEntry.
Netsh adapter (Tier 1) -- Parses netsh wlan show networks mode=bssid output into structured BssidObservation records. Zero platform dependencies.
WLAN API scanner (Tier 2, wlanapi feature) -- Async scanning via the Windows WLAN API with tokio integration.
Multi-AP frame -- MultiApFrame aggregates observations from multiple BSSIDs into a single timestamped frame for downstream processing.
Sensing pipeline (pipeline feature) -- WindowsWifiPipeline orchestrates motion detection, breathing estimation, attention-weighted AP selection, and location fingerprint matching.

Feature flags

Flag	Default	Description
`serde`	yes	Serialization for domain types
`pipeline`	yes	WindowsWifiPipeline sensing orchestration
`wlanapi`	no	Tier 2 async scanning via tokio (Windows WLAN API)

Quick Start

use wifi_densepose_wifiscan::{
    NetshBssidScanner, BssidRegistry, WlanScanPort,
};

// Parse netsh output (works on any platform for testing)
let netsh_output = "..."; // output of `netsh wlan show networks mode=bssid`
let observations = wifi_densepose_wifiscan::parse_netsh_output(netsh_output);

// Register observations
let mut registry = BssidRegistry::new();
for obs in &observations {
    registry.update(obs);
}

println!("Tracking {} access points", registry.len());

With the pipeline feature enabled:

use wifi_densepose_wifiscan::WindowsWifiPipeline;

let pipeline = WindowsWifiPipeline::new();
// Feed MultiApFrame data into the pipeline for sensing...

Architecture

wifi-densepose-wifiscan/src/
  lib.rs          -- Re-exports, feature gates
  domain/
    bssid.rs      -- BssidId, BssidObservation, BandType, RadioType
    registry.rs   -- BssidRegistry, BssidEntry, BssidMeta, RunningStats
    frame.rs      -- MultiApFrame (multi-BSSID aggregated frame)
    result.rs     -- EnhancedSensingResult
  port.rs         -- WlanScanPort trait (platform abstraction)
  adapter.rs      -- NetshBssidScanner (Tier 1), WlanApiScanner (Tier 2)
  pipeline.rs     -- WindowsWifiPipeline (motion, breathing, attention, fingerprint)
  error.rs        -- WifiScanError

Crate	Role
`wifi-densepose-signal`	Advanced CSI signal processing
`wifi-densepose-vitals`	Vital sign extraction from CSI
`wifi-densepose-hardware`	ESP32 and other hardware interfaces
`wifi-densepose-mat`	Disaster detection using multi-AP data

License

MIT OR Apache-2.0

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