Ronquy — On-Device Snore Detection

Private product. This is proprietary work; the app is private. This page describes the architecture and intent without exposing internal logic.

Ronquy detects snoring on-device, all night, with no audio ever leaving the phone. A real YAMNet model runs through TFLite (react-native-fast-tflite) inside a native overnight loop that captures audio and runs inference locally for ~8 hours. The heavy, time-critical path is native, not a JavaScript shim. Only derived events are stored; the audio itself never leaves the device.

Why it matters

Privacy is the product. A snore tracker that never uploads your sleep audio is fundamentally more trustworthy than one that does — and doing the inference on-device also means it works offline and costs nothing per night to run. An optional cloud mode (FastAPI + Postgres + own auth) lets a user register and sync results across devices, but the detection itself is fully local.

What it demonstrates

• A hard mobile-ML pattern end to end: a native, battery-aware, all-night audio + inference loop with a real model on-device (no mock).
• A privacy-first design where the sensitive data never leaves the phone.
• A cross-platform app shipped as a standalone build, with an optional own-auth cloud backend.