Pulse — Real-time Vibration Anomaly Detector

A $15 edge AI device that detects abnormal vibration in machinery using TinyML on STM32L4 — no cloud, no internet required

Ayush Kothari

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Description

Motors, fans, pumps and compressors always give warnings before they fail — subtle changes in vibration that nobody catches until it's too late.
Pulse is a palm-sized embedded device that learns your machine's normal vibration signature in ~30 seconds and alerts you in real-time when something changes. No cloud. No internet. No subscription. Everything runs on a STM32L412RB microcontroller with 40KB RAM.
Built with Zephyr RTOS and STMicroelectronics NanoEdge AI. Training data persists to onboard flash with CRC32 validation — so Pulse remembers what it learned even after a power cycle.
Currently tested on a Xiaomi air purifier fan. Looking for people with real industrial equipment — motors, pumps, CNC machines — to test this further.
https://github.com/Ayushkothari96/pulse

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[View on GitHub](https://github.com/Ayushkothari96/pulse)

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Pulse-First public release — tested on air purifier
Ayush Kothari • 03/15/2026 at 09:34 • 0 comments

First public release — tested on air purifier

Got the project to a point where I'm happy sharing it publicly.
Tested anomaly detection on a Xiaomi air purifier fan —
attaching the STM32 + LIS2DH12 directly to the casing and
introducing a physical disturbance (tapping/scratching) gets
detected within one inference cycle (~600ms).

Flash persistence is working reliably — training data survives
power cycles with CRC32 validation on the header.

Next goal: find someone with an industrial motor or pump to
test on real machinery.