Ross ROSS = Recommend OSS · open-source software intelligence for agents

ronibandini/reggaetonBeGone

Detects reggaeton genre with Machine Learning and sends packets to disable BT speakers (hopefully) observed · 2026-09-03

github.com/ronibandini/reggaetonBeGone · homepage · Python · MIT (permissive) observed · 2026-09-03

Health v2 · maintenance only

70/100

  • Activity 99
  • Release rhythm 35
  • Longevity 66

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 925
  • days_rel: n/a
  • days_push: 11
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1005 stars · 118 forks observed · 2026-09-03

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Raspberry Pi-based edge machine learning device that continuously samples ambient audio and uses an Edge Impulse audio classification model to detect reggaeton music. When detection confidence exceeds a threshold, it triggers a Bluetooth test routine against a configured nearby speaker, inspired by TV-B-Gone.

Use cases

  • detect reggaeton music playing nearby with machine learning
  • classify music genre from ambient audio on a Raspberry Pi
  • run Edge Impulse audio inference on edge hardware
  • build a TV-B-Gone style device for Bluetooth speakers
  • experiment with Bluetooth routines triggered by audio classification
  • display ML inference confidence on an OLED screen

When to choose

  • you want a fun maker project combining edge ML, Raspberry Pi, and Bluetooth experimentation
  • you need local audio genre classification on ARM hardware without cloud services
  • you want a hardware reference for Edge Impulse .eim models with OLED and button peripherals

When to avoid

  • you need a reliable or legal way to disable other people's Bluetooth speakers
  • you need production-grade audio classification or general music genre recognition
  • you want a portable solution without a Raspberry Pi (the author's Pocket Gone is simpler)
  • you need supported, maintained software rather than an experimental novelty build

Facets

application · maturity experimental

machine-learning audio-processing speech-recognition security machine-learning hardware developer-tools python embedded edge-ml raspberry-pi edge-impulse bluetooth music-genre-classification audio-classification oled-display novelty-project audio linux

2 sources

Member repositories

RepositoryRoleHealth v2
ronibandini/reggaetonBeGonemain70

For agents

markdown · JSON · MCP: product_card(name="ronibandini/reggaetonBeGone")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem