First post in the community - so hi folks!
Honestly not really blown away by the sense yet, its detected the fridge (and only when its pump is on, not on standby, so I can’t set an alert if the fridge is actually off when an alert would actually be useful).
I have read numerous posts asking for the ability to help sense detect devices, and the response from the Sense folks don’t seem to really close the issue for me.
Right now the device is looking at delta change, power signals and using an AI model to process these signals. There is no reason why there wouldnt be the ability to teach sense your devices. An Analogy of people in a photograph was used here but honestly that doesn’t hold. identifying a face is actually VERY easy, so not overly comparative to this.
My question is if you had exactly the same noise (background) and you switched a device on and off, only that device, while Sense was in ‘listening mode’. It should be able to get a better idea of that device. Then switch a different set of devices on and repeat the on & off of the target device - the AI at this point should be identifying the common signature across (this could be repeated on a different day, and different time - as each time the single device is switched on & off the AI model should be removing anything else that isn’t the same).
In the photo of people scenario it would be like looking for Mike in a crowd, but the crowd keeps changing, and eventually when there are enough different crowds Mike would be the only common denominator (couple that with the EXTENSIVE data Sense is providing their data scientists) i’m struggling to see why this is not possible.
The complicated part should really be the always on - as by definition these devices contribute to the noise and there isn’t the ability to disambiguate so readily (without a listening mode exercise) OR devices that are only switched on rarely as requires a lot more data samples during usage to single out.