adrianagaler/Snoring-Detection

The project is a classic TinyML demonstration repo, likely originating from academic or hobbyist exploration. With a velocity of zero and an age of nearly 2,000 days, it is functionally stagnant. While it has 67 stars—indicating historical relevance for those learning edge AI—it lacks any modern moat. Snoring detection is a 'commodity' capability in the TinyML space; platforms like Edge Impulse provide more robust, automated workflows for this exact use case, and frontier labs (Apple, Google, Fitbit) have already integrated sophisticated, power-efficient snore detection into their health ecosystems. The model likely uses a standard CNN or RNN architecture applied to MFCC features, which is easily reproducible. Defensibility is minimal as it relies on public datasets and standard TFLite Micro deployment patterns. It serves better as a historical reference or educational template than a competitive commercial or infrastructure project.