We are trying to improve specific device models, and we need your help!
If you charge your Electric Vehicle at home, please help us improve our device detection by filling out this survey.
We’ll be doing this over an increasing set of devices (and will soon create a survey to get your vote on what to work on next!).
I filled out your survey and I do have a Chevrolet volt that I charged every day
I have owned a Model S85 for 2 years now. Ask away…
Why can’t we do this with all of our devices? If I give you a list of makes and model numbers, would that help you reduce the learning effort of my devices?
I have a 2016 Hyundai Sonata PHEV that I charge with a 120v outlet.
Had to help since the survey form is no longer available.
I have asked this so many times I can’t count them, the answer varies but in the end its coming is what the response boils down to.
I even provided a excel spreadsheet with over 20 pieces of equipment listed including make and model number and any power information I could find like voltage, starting and running amps for motors, when the equipment usually runs and if complimentary equipment runs simultaneously like the heat pump and the air handler (fan and electrostatic air cleaner) which are on separate breakers, etc.
If they had a table that each user could fill out with information like that to me it seems it would help.
If they are looking at the signatures of equipment to determine what it is then if they knew (based on user input) that 100 people have the same model AC unit or Heat Pump then they could monitor those 100 people specifically for that piece of equipment and put together an algorithm that would detect that equipment faster and more accurately. At least it seems to me that’s how it would work. I know there are differences in everyone’s electrical layout and the list of equipment found in each home will be unique and that causes problems as far as identifying a particular piece of equipment. But wouldn’t it help to know what model AC unit you’re trying to ID in place of only knowing that there is an AC unit somewhere in the mix of traces feeding back to be analyzed.
@sparc, I apologize if you’ve felt unheard in any way with regards to this request. This is something we’re planning on building into the app in the coming months. We want to make sure that when we do release the feature, we’re in a place to able to make use of all the great information that we know will be shared. We’ve started moving towards this by recently adding the ability to add make/model information to devices that have been detected.
+1 on this idea. Have a set of trusted users who can feed in a wealth of information. E.g. I see the spikes and drops in consumption and I know exactly what those devices are. Why can’t I self-classify them for my own edification because that is right for me. Once Sense has validated the signatures, they can move the data into their crowdsourced database.