docs: move ESP32 independent operation note to hardware section

Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv 2026-03-03 16:25:21 -05:00
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**See through walls with WiFi.** No cameras. No wearables. Just radio waves.
WiFi DensePose turns commodity WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection — all without a single pixel of video. By analyzing Channel State Information (CSI) disturbances caused by human movement, the system reconstructs body position, breathing rate, and heartbeat using physics-based signal processing and machine learning. The [server](#-quick-start) is optional for visualization and aggregation — the [ESP32 runs edge intelligence independently](#esp32-s3-hardware-pipeline), performing on-device presence detection, vital signs, and fall detection without any host connection.
WiFi DensePose turns commodity WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection — all without a single pixel of video. By analyzing Channel State Information (CSI) disturbances caused by human movement, the system reconstructs body position, breathing rate, and heartbeat using physics-based signal processing and machine learning.
[![Rust 1.85+](https://img.shields.io/badge/rust-1.85+-orange.svg)](https://www.rust-lang.org/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
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> | **Any WiFi** | Windows, macOS, or Linux laptop | $0 | No | RSSI-only: coarse presence and motion |
>
> No hardware? Verify the signal processing pipeline with the deterministic reference signal: `python v1/data/proof/verify.py`
>
> The [server](#-quick-start) is optional for visualization and aggregation — the [ESP32 runs edge intelligence independently](#esp32-s3-hardware-pipeline), performing on-device presence detection, vital signs, and fall detection without any host connection.
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