# DanielRapp/doppler

:wave: Motion detection using the doppler effect

Repository: https://github.com/DanielRapp/doppler
Canonical: https://ross.abutalabs.com/products/doppler
Homepage: https://danielrapp.github.io/doppler/
Language: JavaScript
License: MIT
License Family: permissive
Last push: 2017-03-29T18:46:15+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4196, "days_push": 3444, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2393, forks 176 (observed 2026-08-28T04:06:43.455764+00:00)

## What it is
A JavaScript library that detects hand motion using the doppler effect, emitting an inaudible ~20kHz tone from speakers and measuring frequency shifts via the microphone. It is a web implementation of Microsoft's SoundWave paper requiring no special hardware.

## Use cases
- detect hand gestures with just a microphone and speakers
- implement touchless motion control in the browser
- reproduce the SoundWave doppler motion sensing paper
- build a web demo of ultrasound-based motion detection
- measure doppler shift from microphone input in JavaScript

## When to choose
- you want hardware-free motion sensing in a Chrome-based web app
- you're experimenting with audio-based gesture interfaces or academic reproduction

## When to avoid
- you need robust, production-grade motion detection
- you must support Firefox or other browsers lacking echoCancellation control
- you need an actively maintained library

## Facets
- artifact type: library
- maturity: abandoned
- function: audio-processing, machine-learning
- domain: computer-vision, web-development
- platform: browser
- tags: doppler-effect, motion-detection, web-audio, microphone, soundwave-paper, gesture-recognition, algorithms, javascript

## Member repositories
- DanielRapp/doppler (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:43.455764+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:34:25.049512+00:00, confidence not recorded.
  - readme: https://github.com/DanielRapp/doppler (fetched 2026-08-28T04:06:43.455764+00:00, sha 83512ea8c290)
  - homepage: https://danielrapp.github.io/doppler/ (fetched 2026-08-29T10:15:19.743912+00:00, sha 4b123222220c)
- Data as of 2026-08-30T08:39:29.467469+00:00.