We should be able to TRAIN this!



Thanks. I’m betting the variable speed motors are the challenge. My old school Liftmaster garage doors are picked up by Sense like clockwork. They are one model year to early to be IoTable via SmartIQ.

I agree completely with you that Sense needs take a new tack, though on training, not detection. They need smarter feedback both from humans when detection goes askew, and from smart controllers when known devices are turned on/off. The trick with the former is to do it in a very structured way, so humans give Sense unambiguous training information. And the hard thing about the latter is building robust integrations with the dozens of automation APIs that users are likely to encounter.

I think we’ll see increased progress on the detection side for harder devices as the training feedback improves.


@jackfurr, is the pool pump literally always-on? Can you turn it off at night and then it back on every morning? …maybe even a timer for 3, 4 , 6, or 8 hours off? I’ve owned a few pools and that is what I did only to save energy costs, yet I could keep my pool levels balanced… Power cycling could help a lot with pool pump detection, but while the pump is off Sense may find other devices.
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Thanks for weighing in on this @mstraka606 and @kevin1 -

We did talk a bit in the webinar about the initiatives towards device detection, training possibilities, and integrations to support those efforts, which are absolutely the focus for us in 2018. Some of the work we’re doing to support integrations involves a pretty high development effort up front, but will mean that integrations with devices like smartplugs, connected thermostats, etc. will be much easier to implement down the road.

While the data science and engineering teams are knee deep in getting frameworks in place for these kinds of major detection improvements, there are smaller, parallel teams making sure the web and mobile apps are up-to-date and continuing to add new features, but know that the majority of our resources are focused on helping to make big strides in device detection and integrations this year.

Thanks to all of you for your patience and persistence as we keep working on things, and please keep the feedback coming!



Brad awesome response. I’m very excited to hear about this focus. I can predict much improved performance! Thanks again for this new information.