This is an open-source (GPLv3) project that uses Wi-Fi signal analysis to detect motion using CSI data, and it has already garnered almost 2,000 stars in two weeks.
Key technical details:
- The system does NOT use Machine Learning, it relies purely on Math. — Runs in real-time on a super affordable chip like the ESP32. - It integrates seamlessly with Home Assistant via MQTT.
I use a single ESP32 in STA/AP mode which sniffs ACK packets with a specific destination mac, which come from any server on my WiFi network (uses a special sniffing mode IIRC). This way I can receive regular CSI packets originating from a fixed location and doesn't need another device running.
I'll have to look at this code, maybe I just overlooked the obvious or my requirements were too high!
1. Instead of STA/AP mode on a single ESP32, ESPectre uses the natural traffic between your existing router and an ESP32-S3 in station mode. To ensure a stable, continuous CSI packet rate, I implemented a traffic generator that sends ICMP pings to the gateway at a configurable rate (default: 20 pps). This provides bidirectional traffic (request + reply) that reliably triggers CSI generation, giving you predictable packet timing without relying on ambient network traffic or special sniffing modes.
2. Rather than applying filters directly to raw CSI, ESPectre uses Moving Variance Segmentation (MVS) on unfiltered spatial turbulence (std dev of subcarrier amplitudes).
3. The filters are applied to features, not to the segmentation signal itself. This preserves motion sensitivity while cleaning up the feature data
I found that having a stable transmitter (the router) combined with controlled traffic generation provides more consistent multipath patterns and predictable CSI timing, which makes the segmentation more reliable.
Sounds like your MVS approach is a sliding window variance of the cross channel variance, with some adaptive thresholding. My pre-processing has generally been an EWMA de-meaning filter followed by some type of dimensionality reduction and feature extraction (kernel or hand-crafted, like raw moments), which I think fits into your overall architecture.
I'll have to look more closely at your work, thanks for sharing!
You're spot on about the MVS approach. It's essentially a sliding window variance of the spatial turbulence (std dev across subcarriers), with adaptive thresholding based on the moving variance of that signal.
If you're interested in the MVS details, I wrote a free Medium article that walks through the segmentation algorithm step-by-step with visualizations. Links are in the README.
Your approach is actually quite similar to what I'm doing, just in a different order:
- My flow: Raw CSI → Segmentation (MVS) → Filters (Butterworth/Wavelet/Hampel/SG) → Feature extraction
- Your flow: Raw CSI → EWMA de-meaning → Dimensionality reduction → Feature extraction
The main difference is that I segment first to separate IDLE from MOTION states (keeping segmentation on raw, unfiltered CSI to preserve motion sensitivity), then only extract features during MOTION (to save CPU cycles).
Thanks for the thoughtful feedback! Always great to exchange notes with someone who's been in the trenches with CSI signal processing
- It monitors CSI from that specific node (the one it's associated with)
- If the ESP32 roams to a different mesh node, it will start monitoring CSI from the new node
The system doesn't care about the router's internal mesh topology, it just needs a stable connection to receive CSI data from the associated access point.
tetris11•2h ago
Am I right in understanding that only a single ESP32 device is needed (plus a router)?
pmontra•2h ago
Is the author reads this, how does the system cope with multiple rooms in the same house, maybe a two or three storeys house?
francescopace•1h ago
You need one sensor for each area you want to monitor independently. With devices more capable than the ESP32‑S3, the coverage would likely be greater.
The ESP32‑C6, in particular, offers significantly better performance. Check out this comparison video from Espressif: https://www.youtube.com/watch?v=JjdpzM6zVJ8
yoavm•36m ago
francescopace•21m ago
That said, ESP32 boards are very inexpensive, you can find them online for around €1 or even less.