The first 3 months

I have been a Sense user for 3 months now. Overall, I am extremely satisfied! Technical support is superb and the user interface / app is beautiful. In the interest of sharing my Sense story with others, the only thing that really needs discussion is detection efficiency. As we all know, this technology works best when it can identify individual devices.

Sense has natively detected devices 18 times. Of those, 9 are working well. What about the others? Two were never heard from again so must represent a confused algorithm. One started getting conflated with something else, so technical support suggested that I deleted it and wait for re-detection (which did occur, and the new detection is better than the original). One detected device was only picking up 30% of usage so I put that device on an HS110 to get a better view. I also retired several of of the physical devices that had been detected, which makes the statistics look worse but has nothing to do with Sense technology.

Those 9 native devices pick up about 40% of my total usage. Sense is intentional about detecting those devices that have the most impact, and they have achieved their goal in my case. Since I wanted a more complete picture, I also invested in several TP-Link smart plugs with energy monitoring capability. Those devices are also located to provide as much impact as possible. The graph below shows how much of each day’s total usage is accounted for by each detection method over these first three months. The blue color represents native devices whose history is applied retroactively in certain cases. Uncolored (white) areas represent native detection.

I categorize my devices by their function in my house. Air conditioning is the largest usage by far, as my stove and hot water both run off natural gas. The graph below shows weekly averages over this same period.

I feel fortunate to know where 90% of my electricity is being used. Especially compared to other users for whom Sense has not been so informative. My intention in sharing is not to boast, but rather to congratulate Sense on a job well done. This post may also help new users to wait patiently for results, which do not happen instantly. Finally, this post shows how important integrations are for my Sense experience. Although one could say it is a weakness of Sense that their technology needed that much help from integrations to reach 90% accounting, I consider it a strength that they have made a flexible product that can work with other technology to fill in for their weakness. Teams are stronger than sum of their individual players.


Hey there @jefflayman! We love hearing feedback like this. If you’re a fan of Sense, there are a few ways you can help us share your story and experience.

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I forgot to share another graphic from my first 3 months. The image below shows how frequently native detections occurred for me. It is plotted on logarithmic scale since most occurred near the beginning, with longer and longer times between new detections. Some detections came in clusters of two or three at a time. The vertical value in the plot is the number of days since the previous detection divided by the detection count in that cluster.
A trend line curve is plotted with the data. I found that what Excel calls a power trend line fits best. The equation for this trend line is displayed in the graphic. That equation implies far more precision than is warranted since the coefficient of determination (R-squared, which measures fit quality) is not very close to one. Even if it were a perfect fit for my data, each Sense experience is unique.

I know the following will be wrong for a lot of people, but I offer it anyway since some idea is better than none. Hopefully it is like the weather man, to whom we still pay attention even though his forecasts are often wrong. The trend line equation above can be integrated and rounded. The result is an equation that expresses the number of native detections, D, expected after n days: D = 10n⁰·² - 10

For example, this equation indicates that after 100 days I can expect 15 native detections because one hundred raised to the power of zero-point-two, times ten, minus ten, is equal to fifteen. Another example is that after 8 days I can expect 5 native detections because eight raised to the power of zero-point-two, times ten, minus ten, is equal to five.

Let me repeat that this is only a guideline. The above equation doesn’t even fit my own experience exactly. Please expect that your mileage will vary.