Minut technology
Patented privacy-first sound recognition
AudioID is Minut's proprietary machine learning technology that identifies real disturbances and critical sounds. Engineered for absolute privacy, it processes sound patterns directly on the device, ensuring conversations are never recorded or recognized, and raw audio never leaves the room.
50+
sound classes AudioID is trained to recognize
Inside the R&D
Traditional decibel monitoring measures how loud a space is, but cannot determine what made the sound.
That’s why Minut’s team of engineers trained AudioID on over 50 sound classes, so our sensors can separate real disturbances, like a loud party or a safety alarm, from the ambient noise of everyday life.
Sound recognition
Using convolutional neural networks, AudioID identifies the signatures of standard household safety alarms, like fire and CO alarms, and breaking glass, in real time.
Trained on thousands of data points, including look-alike sounds, it’s precise enough to tell breaking glass from a dishwasher being emptied.
Living room
Safety alarm pattern detected
Kitchen
Breaking glass detected
Kitchen
Dishwasher being emptied

Sound suppression
Standard noise monitors measure loudness alone, so a windy night or a vacuum cleaner can register as a disturbance or party. AudioID is trained to recognize the specific sounds that matter.
Engineered for the elements.
AudioID is trained to tune out environmental and weather noise, delivering reliable noise alerts inside, and out.
Edge processing
Sounds are processed in real time on the sensor and immediately discarded. Only privacy-safe data is sent to the cloud: never voices, never recordings.
Minut sensor
Detect
The microphone picks up a sound in the room.
Transform
AudioID turns it into an anonymous sound signature on the sensor.
Discard
The raw audio is deleted immediately. It is never stored or sent.
Minut cloud
Receives only event labels and noise levels.
Minut user


Where you’ll find it

