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ESPectre

Motion detection based on Wi-Fi spectre analysis

Details

External ID
45953977
Source
HN
Company
—
Product
ESPectre
Website domain
github.com
Launched
Nov. 17, 2025
Cohort
—
Upvotes
215
Upvotes percentile
0.9563318777292577
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hi everyone, I'm the author of ESPectre.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.

Enrichment

Theme
open-source hardware and embedded electronics
Vertical
Security
Function
Hardware & robotics
Audience
B2B
AI stance
Not AI
Project type
Commercial product
Normalized one-liner
motion detection using wi-fi analysis
Manually corrected
False

Could you build this?

No It involves embedded C/C++ firmware, low-level ESP32 Wi-Fi PHY layer CSI (Channel State Information) data extraction, and specialized digital signal processing algorithms.

What it would actually take: Building this requires developing firmware for the ESP32 (using ESP-IDF) to capture raw 802.11 CSI subcarrier metrics. The core difficulty lies in advanced digital signal processing (noise filtering, phase sanitization, Doppler shift estimation, and statistical thresholding) executed in real time on resource-constrained microcontrollers. It demands specialized knowledge of RF physics, embedded systems programming, and signal processing.

Discussion

20 comments analyzed.

Competitors mentioned: Leap Motion (for gesture/motion sensing), TOMMY (Wi-Fi sensing motion detection), Xbox Kinect LIDAR

Concerns raised: Wi-Fi mesh roaming issues - ESP32 may lock to wrong access point, monitoring wrong room space, CSI accuracy limited to centimeters, not sub-millimeter precision, PWM frequency updates at 20-50 Hz may cause zipper noise artifacts, Privacy implications - surveillance capability could be misused by state actors, Binary motion detection cannot ignore cats or prioritize size over speed on-device

Feature requests: Advanced ML-based classification (cat vs. human vs. fall detection) on device, Lock ESP32 to specific mesh node MAC address to prevent roaming, Logarithmic pitch mapping with smoothing/lerping to avoid zippering, Configurable beamforming and router power settings for stability

Competitors

Other products that read as similar to this one — 17 launches clear the similarity bar, closest 8 shown.

Attention rank: #2 of 18 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Looks like the first mover among its competitors.

Other launches for this product

Same idea, different domain

Nobody's really built a hardware & robotics tool for Horizontal yet.