I’ve just pulled the data again for all of Jan 2017 (the balance is the data pulled from Jan 22) and wanted to share what device learning performance looks like in my home. Note: Since Sense calculates it’s percentages based on the mix of devices used each day, this metric reflects the total percentage of daily electrical load that is learned, always on, and unknown. It does not represent the number of devices that have been learned, are always on, or unknown.
In January, load from learned devices dropped below 10% for the first time since late Oct 2016.
This, I’m told, is due to high load devices disappearing due to changed quality thresholds in ML models, and high load devices no longer having their expected load detected. In terms of the trends over time, load from learned devices is trending down since Nov 2016.
At the same time I’ve seen rolling averages from Always on growing through this month from a low of 9.5% to a high of 14.8%.
Talking about learned device load is just part of the picture. Drilling into the devices that Sense considers “learned” for Jan 2017 and which devices are correctly learned and trusted, of the 13.3% of total device load that Sense has identified, 4.4% of the total device load is trusted and 8.9% is untrusted.
The biggest impact is the loss of the Hot Water Heater which was nuked by an ML model quality threshold change, and the Kitchen Floor whose load stopped being detected on Jan 8th although it’s been on for the whole month.
For my top outcome of identifying power hogs, it’s hard to see this data in much of a positive light. I am less able to take informed action reducing my electricity bill than I have been since the end of October.