ADR-039: ESP32-S3 Edge Intelligence Pipeline

Status: Accepted (hardware-validated on RuView ESP32-S3) Date: 2026-03-02 Deciders: @ruvnet

Context

WiFi-DensePose captures Channel State Information (CSI) from ESP32-S3 nodes and streams raw I/Q data to a host server for processing. This architecture has limitations:

Bandwidth: Raw CSI at 20 Hz × 128 subcarriers × 2 bytes = ~5 KB/frame = ~100 KB/s per node. Multi-node deployments saturate low-bandwidth links.
Latency: Server-side processing adds network round-trip delay for time-critical signals like fall detection.
Power: Continuous raw streaming prevents duty-cycling for battery-powered deployments.
Scalability: Server CPU scales linearly with node count for basic signal processing that could run on the ESP32-S3's dual cores.

Decision

Implement a tiered edge processing pipeline on the ESP32-S3 that performs signal processing locally and sends compact results:

Tier 0 — Raw Passthrough (default, backward compatible)

No on-device processing. CSI frames streamed as-is (magic 0xC5110001).

Tier 1 — Basic Signal Processing

Phase extraction and unwrapping from I/Q pairs
Welford running variance per subcarrier
Top-K subcarrier selection by variance
Delta compression (XOR + RLE) for 30-50% bandwidth reduction (magic 0xC5110005, reassigned from 0xC5110003 by ADR-069)

Tier 2 — Full Edge Intelligence

All of Tier 1, plus:

Biquad IIR bandpass filters: breathing (0.1-0.5 Hz), heart rate (0.8-2.0 Hz)
Zero-crossing BPM estimation
Presence detection with adaptive threshold calibration (1200 frames, 3-sigma)
Fall detection (phase acceleration exceeding configurable threshold)
Multi-person vitals via subcarrier group clustering (up to 4 persons)
32-byte vitals packet at configurable interval (magic 0xC5110002)

Architecture

Core 0 (WiFi)                    Core 1 (DSP)
┌─────────────────┐              ┌──────────────────────────┐
│ CSI callback     │──SPSC ring──▶│ Phase extract + unwrap   │
│ (wifi_csi_cb)    │   buffer     │ Welford variance         │
│                  │              │ Top-K selection           │
│ UDP raw stream   │              │ Biquad bandpass filters   │
│ (0xC5110001)     │              │ Zero-crossing BPM         │
└─────────────────┘              │ Presence detection        │
                                 │ Fall detection             │
                                 │ Multi-person clustering    │
                                 │ Delta compression          │
                                 │ ──▶ UDP vitals (0xC5110002)│
                                 │ ──▶ UDP compressed (0x05)  │
                                 └──────────────────────────┘

Wire Protocols

Vitals Packet (32 bytes, magic 0xC5110002):

Offset	Type	Field
0-3	u32 LE	Magic `0xC5110002`
4	u8	Node ID
5	u8	Flags (bit0=presence, bit1=fall, bit2=motion)
6-7	u16 LE	Breathing rate (BPM × 100)
8-11	u32 LE	Heart rate (BPM × 10000)
12	i8	RSSI
13	u8	Number of detected persons
14-15	u8[2]	Reserved
16-19	f32 LE	Motion energy
20-23	f32 LE	Presence score
24-27	u32 LE	Timestamp (ms since boot)
28-31	u32 LE	Reserved

Compressed Frame (magic 0xC5110005, reassigned from 0xC5110003 by ADR-069):

Offset	Type	Field
0-3	u32 LE	Magic `0xC5110005`
4	u8	Node ID
5	u8	WiFi channel
6-7	u16 LE	Original I/Q length
8-9	u16 LE	Compressed length
10+	bytes	RLE-encoded XOR delta

Configuration

Six NVS keys in the csi_cfg namespace:

NVS Key	Type	Default	Description
`edge_tier`	u8	2	Processing tier (0/1/2)
`pres_thresh`	u16	0	Presence threshold × 1000 (0 = auto)
`fall_thresh`	u16	2000	Fall threshold × 1000 (rad/s²)
`vital_win`	u16	256	Phase history window
`vital_int`	u16	1000	Vitals interval (ms)
`subk_count`	u8	8	Top-K subcarrier count

All configurable via provision.py --edge-tier 2 --pres-thresh 0.05 ...

Additional Features

OTA Updates: HTTP server on port 8032 (POST /ota, GET /ota/status) with rollback support
Power Management: WiFi modem sleep + automatic light sleep with configurable duty cycle

Consequences

Positive

Fall detection latency reduced from ~500 ms (network RTT) to <50 ms (on-device)
Bandwidth reduced 30-50% with delta compression, or 95%+ with vitals-only mode
Battery-powered deployments possible with duty-cycled light sleep
Server can handle 10x more nodes (only parses 32-byte vitals instead of ~5 KB CSI)

Negative

Firmware complexity increases (edge_processing.c is ~750 lines)
ESP32-S3 RAM usage increases ~12 KB for ring buffer + filter state
Binary size increases from ~550 KB to ~925 KB with full WASM3 Tier 3 (10% free in 1 MB partition — see ADR-040)

Risks

BPM accuracy depends on subject distance and movement; needs real-world validation
Fall detection heuristic may false-positive on environmental motion (doors, pets)
Multi-person separation via subcarrier clustering is approximate without calibration

Implementation

firmware/esp32-csi-node/main/edge_processing.c — DSP pipeline (~750 lines)
firmware/esp32-csi-node/main/edge_processing.h — Types and API
firmware/esp32-csi-node/main/ota_update.c/h — HTTP OTA endpoint
firmware/esp32-csi-node/main/power_mgmt.c/h — Power management
rust-port/.../wifi-densepose-sensing-server/src/main.rs — Vitals parser + REST endpoint
scripts/provision.py — Edge config CLI arguments
.github/workflows/firmware-ci.yml — CI build + size gate (updated to 950 KB for Tier 3)

Tier 3 — WASM Programmable Sensing (ADR-040, ADR-041)

See ADR-040 for hot-loadable WASM modules compiled from Rust, executed via WASM3 interpreter on-device. Core modules: gesture recognition, coherence monitoring, adversarial detection.

ADR-041 defines the curated module collection (37 modules across 6 categories). Phase 1 implemented modules:

vital_trend.rs — Clinical vital sign trend analysis (bradypnea, tachypnea, apnea)
intrusion.rs — State-machine intrusion detection (calibrate-monitor-arm-alert)
occupancy.rs — Spatial occupancy zone detection with per-zone variance analysis

Hardware Benchmark (RuView ESP32-S3)

Measured on ESP32-S3 (QFN56 rev v0.2, 8 MB flash, 160 MHz, ESP-IDF v5.2).

Boot Timing

Milestone	Time (ms)
`app_main()`	412
WiFi STA init	627
WiFi connected + IP	3,732
CSI collection init	3,754
Edge DSP task started	3,773
WASM runtime initialized	3,857
Total boot → ready	~3.9 s

CSI Performance

Metric	Value
Frame rate	28.5 Hz (measured, ch 5 BW20)
Frame sizes	128 / 256 bytes
RSSI range	-83 to -32 dBm (mean -62 dBm)
Per-frame interval	30.6 ms avg

Memory

Region	Size
RAM (main heap)	256 KiB
RAM (secondary)	21 KiB
DRAM	32 KiB
RTC RAM	7 KiB
Total available	316 KiB
PSRAM	Not populated on test board
WASM arena fallback	Internal heap (160 KB/slot × 4)

Firmware Binary

Metric	Value
Binary size	925 KB (0xE7440 bytes)
Partition size	1 MB (factory)
Free space	10% (99 KB)
CI size gate	950 KB (PASS)
WASM3 interpreter	Included (full, ~100 KB)
WASM binary (7 modules)	13.8 KB (wasm32-unknown-unknown release)

WASM Runtime

Metric	Value
Init time	106 ms
Module slots	4
Arena per slot	160 KB
Frame budget	10,000 µs (10 ms)
Timer interval	1,000 ms (1 Hz)

Findings

Fall detection threshold too low — default fall_thresh=2000 (2.0 rad/s²) triggers 6.7 false positives/s in static indoor environment. Recommend increasing to 5000-8000 for typical deployments.
No PSRAM on test board — WASM arena falls back to internal heap. Boards with PSRAM would support larger modules.
CSI rate exceeds spec — measured 28.5 Hz vs. expected ~20 Hz. Performance headroom is better than estimated.
WiFi-to-Ethernet isolation — some routers block UDP between WiFi and wired clients. Recommend same-subnet verification in deployment guide.
sendto ENOMEM crash (Issue #127) — CSI callbacks in promiscuous mode fire 100-500+ times/sec, exhausting the lwIP pbuf pool and causing a guru meditation crash. Fixed with a dual approach: 50 Hz rate limiter in csi_collector.c (20 ms minimum send interval) and a 100 ms ENOMEM backoff in stream_sender.c. Binary size with fix: 947 KB. Hardware-verified stable for 200+ CSI callbacks with zero ENOMEM errors.