Why Sense needs time to detect device
Sense detects fluctuations in electrical energy use and our software utilizes machine learning to distinguish one appliance from another. The nature of machine learning requires a lot of data before accurate models can be formed which is why it takes time for device detection to improve. Sense needs to see your devices in its typical operating context in order to accurately identify them. Our data science team is constantly working to confirm and push out our device models to ensure they will take into account the variation between home to home, and even the same device running at different times.
###I can see the device’s graph when I turn it on and off, why can’t I tag it?
Device detection is very much like trying to single out one person’s voice while 30 people are talking at the same time. We might hear the gist of what they’re saying, but we may not know what they sound like when they’re the only one speaking. Here’s a video of one of our data scientists demonstrating how electrical signals are identified. Feel free to check out our relevant blog article: Why Can’t I Train Sense?
###How often do new devices get pushed?
Device detection updates are pushed automatically, and will vary from home to home based on what it has been learning. Sense needs to see many repetitions of a device working in your home before we can model it, and we’d only want to show you what we’re sure of.
###Relevant blog articles