Discussion: Why can't I train my sense?

Being that sense is a fairly new company and with more people buying it I am sure that we are going to be seeing many improvements with the app and with more people using it I am sure that device detection will only be happening faster. I am looking forward to them adding the TP-link HS300 to the list of supported devices which will end up giving them more data for their server.

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It looks like you’ve been a Sense user for a little over 2 weeks?

As Ryan suggests, even at the 2 week period it is very early in the Sense initial detection phase. I saw one device in the first week and a half or so (my furnace fan which cycles several times every hour, so it was an easy find) and then it was (IIRC) around the 2 week period where I started to see some additional devices.

Has your unit cleared the initial setup stages and is now indicating it’s monitoring?

The device is finding new leads but is often wrong on the type of load.
It has found my refrigerator and its light!

My freezer was also detected.

I am learning how to use the app better.

Some progress has been made but at a plodding pace.

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The very nature of the way that Sense works means…the impatient are apt to be somewhat frustrated in the beginning.

I am like you, very…very impatient, especially with tech. When I first got my Sense unit and it took 8 or 10 hours to calibrate before it even started looking for devices, and then spent another 3-5 days with no devices detected, it was incredibly tedious for me as well.

That said, I came here to the forum and started reading up on exactly why this was the way things were happening and soon started to understand and appreciate how things were working. It wasn’t easy, but I relaxed and accepted that patience was going to be a virtue with it came to Sense, and many months later I’m generally quite happy.

So relax, and enjoy the ride - you’re still at the very beginning. :wink:

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It’s really common for sense to misidentify a device. Motors identified as heaters or lights as motors. Sense has done what it is designed to do by detecting the device but needs your help with identification. Sometimes it takes some work to properly identify a device but having it be detected is something to be happy about.
Your frustrations will change to “I’m not getting detections” at some point. Sense is a bit of an up and down ride. You might have a period of many accurate detections followed by times where the detections are off or completely absent.
As @MachoDrone stated above and in many other posts, Patience is key.


Hi There,
First post in the community - so hi folks! :slight_smile:

Honestly not really blown away by the sense yet, its detected the fridge (and only when its pump is on, not on standby, so I can’t set an alert if the fridge is actually off when an alert would actually be useful).

I have read numerous posts asking for the ability to help sense detect devices, and the response from the Sense folks don’t seem to really close the issue for me.

Right now the device is looking at delta change, power signals and using an AI model to process these signals. There is no reason why there wouldnt be the ability to teach sense your devices. An Analogy of people in a photograph was used here but honestly that doesn’t hold. identifying a face is actually VERY easy, so not overly comparative to this.
My question is if you had exactly the same noise (background) and you switched a device on and off, only that device, while Sense was in ‘listening mode’. It should be able to get a better idea of that device. Then switch a different set of devices on and repeat the on & off of the target device - the AI at this point should be identifying the common signature across (this could be repeated on a different day, and different time - as each time the single device is switched on & off the AI model should be removing anything else that isn’t the same).

In the photo of people scenario it would be like looking for Mike in a crowd, but the crowd keeps changing, and eventually when there are enough different crowds Mike would be the only common denominator (couple that with the EXTENSIVE data Sense is providing their data scientists) i’m struggling to see why this is not possible.

The complicated part should really be the always on - as by definition these devices contribute to the noise and there isn’t the ability to disambiguate so readily (without a listening mode exercise) OR devices that are only switched on rarely as requires a lot more data samples during usage to single out.

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Sorry to hear your not yet impressed with sense and the detections @jamieeburgess.
For your fridge, sense is working exactly as designed but there is a very simple way for you to setup the alert you are seeking. Go to your device page in the app. Select your fridge and navigate to the top right hand corner so you can open the management page. Create a “custom notification” and have it let you know something like fridge is “off” for “4 hours”. You may have to tweak the time on it according to how often your fridge normally cycles.
To the rest of your post. I’m in agreement with a lot of it and I’ve also been very critical of what I believe I was led to expect and what the difference is in real world use.
We are not the only ones as you will see by reading the huge number of posts repeating the same complaints. I’ve just come to except it for what it is. Having patience is difficult but really is key.
I’ve only had sense since January 15th of this year so about 2 months. I’m at 21 active detections now and all of them are pretty accurate. I’ve had probably at least 20 other detections that sense has removed or combined with other devices or I have deleted due to not being satisfied for some reason.
Your really early into the sense experience, it gets better with time
Hang in there and try to be patient.
You’ll soon get more detections.

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I know what you’re saying and i also don’t like the comparison of face recognition either because they just aren’t the same. A much better comparison would be comparing it to radar detection since they are both analyzing energy wave forms and this technology has been around for decades as you can see from just two examples below. anyways like @samwooly1 said it gets better the longer you have Sense installed and they seem to be making great improvements at Sense and I am extremely happy with my little orange box.



@jamieeburgess, @mike_gessner,
You’re right - I may need to revise my factial recognition analogy a bit, because @jamieeburgess is right - Facial recognition really doesn’t need the full-on flexibility of machine learning for identification, nor does radar detection. But they both use the same two part process as Sense does - Identification followed by classification.

Facial identification is typically done using biometric algorithms that discover and measure facial features, or principle component analysis that translates facial reference points into simpler identifying metrics. @mike_gessner, I’m fairly certain that radar identification is done via DSP and convolutional algorithms, since most military systems were developed/designed well before machine learning really came into being. Both facial recognition and radar identification use fixed algorithms and a smaller set of well defined features to do identification than typicallly used for machine learning.

The real analogy should be the current state of the art in machine vision and image recognition, that uses complex neural networks like ResNet, to identify thousands of different everyday objects, animals, and other nouns.

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Would love to be able to tell Sense some details of my life like “MY HOT TUB RUNS FOR 15 MIN EVERY 6 HOURS” or maybe “I RUN MY DISHWASHER EVERY NIGHT AFTER DINNER” or maybe “I TURN ON MY BATHROOM LIGHT ON WEEKDAY MORNINGS AT 6AM”

… and so much more. Sense seems pretty clueless so far. I’m only 3 days in, but given the info I’ve provided, I’m disappointed at the device detection so far.

The only device it has detected is a light. A 10 watt light. I don’t have any 10 watt lights.

Try and be patient. It’s EXTREMELY difficult to do. At 3 days, ha I got any detections is a good sign.
There are many long discussions here about how we would all like to help or train Sense. Unfortunately, it’s not an option and probably won’t ever be.
Having it detect something like a 10watt “light”, doesn’t mean that it is a light. It may think that’s what it is but could be something else entirely.
This will be the only way to help Sense. When you identify what the detection is and properly name it, that will be the extent of the training.

Hang in there. Patience is really tough, especially after the detections start. I just reset mine yesterday and I’m starting over so we are pretty much both at the same place right now.
Last time around I had about 40-45 detections with around 25 being reliable enough to keep. Most were in the first 3 months.

I am only two days in and when I woke up this morning I was glad to see my garage door was picked up, one of my two sump pumps and two heaters, heat one and two. So I added details to the pump and thought the heat 1 was my oven and heatW my cooktop. However when I went to check to be sure when I tried the oven the cooktop showed up, no big deal so I swapped but when I tried both again they no longer show up. Likewise the sump pump shows on the meter but no longer shows in the pump stats.

Again, I am only two days in, hoping the three lost ones come back (garage is working fine) and other divides start to show up. Will keep you posted

Good answers from Sense here:

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Three days is barely a start and you should plan on weeks/months/years as Sense learns your home and as Sense technology continues to improve. You have just begun a LONG journey, and there isn’t any way to “tell” Sense much of anything…from what I’ve read over the past year and a half that’s not in the plans.

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Using commonsense “rules” to guide Sense seems quite logical until you peer back into the the history of artificial intelligence. We’re on our third round of “artificial intelligence”, with machine learning here in the 2010’s, and two prior booms. The previous boom was in the mid-1980s through early 1990’s with the maturation of rules-based systems, sometimes called expert systems. They used a collection of rules (a rules-base), much like your suggested “details” to make decisions and predict things. The reason that expert systems didn’t take off, except in some remote corners of various industries (like credit scoring), is the rules themselves:

  • They don’t represent reality, only an “expert’s” view on reality (rules can be very wrong or have a human bias)
  • They encourage representational error - the world isn’t always as precise as rules have to be (the light is only on 95% of the time when the conditions are met, plus it is turned on occasionally at other times).
  • They are difficult to manage and often unpredictable with lots of side effects, especially as they build up. I competed with a company that used a rules-base to design chips - their biggest complaint was that the rules-base was unstable, even though they had their best experts building the rules, and often gave unpredictable results.
  • There are always too many rules (complicated to mange), but also too few (lot’s of missed corner cases). Anybody who tries to program their thermostat around their active family’s activities has experienced this phenomenon.

But what about using these rules in some other way in conjunction with machine learning ? The same issues apply. Plus one additional issue adding rules like into machine learning training or feature engineering is that you are injecting a bias into the learning - by tuning Sense to look and learn from specific times, you are also teaching it not to look at other times during the day…

I’ll leave you with this article for thought:

My suggestion - just wait for a while…

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This is what sense is supposed to be able to do…for many of us the reality is a little different…

What is an acceptable length of time for “a while”?

Example…My pool filter has never been detected. I waited a year and then had reason to move the clamps and peform a data reset. This has meant that I now need to wait “a while” longer…:slight_smile:

Their marketing is terrible.
That shot you show makes it sound like Sense is going to tell you something when the reality is, you’ll have to use notifications, look at your timeline and use your own reasoning to pit together a picture of what’s happening.
As far as how long to wait for the pool pump, if it’s variable speed then possibly NEVER.

I feel your pain !

  • 1 device in 3 days - I urge patience
  • 1 device in 1 year - Talk to support, preferably 6 months ago.
  • 1 problematic device that hasn’t shown up for a year - as @samwooly1 suggests, it might be outside the current range of detectability for Sense.

I have shared my Time2Detection chart before, but here’s an update. Many detections in the first week or so, but they continue trickling out. Some of the multiple vacuum cleaners are either other power tools, or our cleaning person’s different vacuums plugged into different legs at our house.

In theory, over time, the Sense-sentience time has decreased. i.e. The delay between install & a good number of detections, when Sense “gets a feel” for your house, has gone down. There is a limit. In the ideal case your devices would all have to go on and off in there different modes at least one. In practice, the number of on-off cycles required for detection can be very large, depending upon the device. That said, there is nothing to stop Sense trending toward the ideal … which, actually, it seems to be doing. The dataset has grown and the “whiles” get shorter, especially after you do a reset … there’s a kind of leapfrogging that happens akin to countries that didn’t have any communications services suddenly having fiber optic or 5G and bypassing all that expensive and laborious copper stuff.

I’m two days post resets and got 3 detections this morning. Two I had before, a heat pump and a refrigerator. The third was new, a refrigerator I added but Sense didn’t detect in the couple of months before the reset.
These fast detections makes me feel like not all DATA is lost from a reset. If machine learning takes hundreds or more cycles then how would I ha e such fast detections?
I could see where they ha e DATA for the same identical product across many users but I ran into the water heater replacement where the same exact model wasn’t detected the same. I’m thinking this new fridge was probably on the edge of Being detected before I decided to reset.

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