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
3.9 KiB
3.9 KiB
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=bssidoutput into structuredBssidObservationrecords. Zero platform dependencies. - WLAN API scanner (Tier 2,
wlanapifeature) -- Async scanning via the Windows WLAN API withtokiointegration. - Multi-AP frame --
MultiApFrameaggregates observations from multiple BSSIDs into a single timestamped frame for downstream processing. - Sensing pipeline (
pipelinefeature) --WindowsWifiPipelineorchestrates 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
Related Crates
| 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