One of the biggest benefits of the smart plug would seem to be allowing the users to label the device that’s creating the specific electrical draw. It would seem that having a pre-classified data electrical load would make it easier to identify similar devices? Instead of having to use ML to infer what a particular device might be, you would have a pre identified load that should be able to be used as a baseline for identifying similar loads, no?
If you’ve already profiled the electrical draw of the smart plugs (since it’s not zero) you shouldn’t in theory be able to cancel out the draw from the smart plug itself, record the draw from the device with the label and then use that as the identifying mechanism. Sure, you might have to leave the smart plug in place for X timeframe ( a month maybe?) to be able to learn enough about the patterns of that particular device (gather enough data sample) to be able to identify it when the smart plug is removed.
Using this methodology, you should also be able to start getting a better handle on always on devices as they would actually be labeled by the customer.
I’d love to run around my house moving smart plugs for the next year to be able to help teach Sense to better identify devices in my environment. I’m not so enthused about having to buy a smart plug for every device that I would like to have detected properly. Especially when I’m a Apple Homekit user and the TP link option isn’t even compatible with my smart home system.
Hope this helps!