I use this with a lenovo WatchX and it works well. It is pretty basic so you can join the party and hack if you feel it. WatchX is very cheap. ~USD $30 on aliexpress.
I would not ever go near the lenovo watch android app which I consider to be on par with radioactive toxic waste.
Using gadgetbridge & Watch X is superior to the Apple Watch & ecosystem at about 1/10th the cost. Recommended.
I use this with a Mi Band 4! The initial steps to get the Xiaomi DRM Pairing key to actually connect it are a bit of a pain (which isn't the developers' fault), but once you've done that once it's a seamless experience. Huge props to the developers!
I want to share a small project, closely related to the paper. You can try it out if you have free 5-10 minutes and an Android device:
https://edge-ml.dmz.teco.edu/
You login; create a so-called workspace; add some labels like walking, jumping, tapping on the device etc.. (simple actions for testing purposes); collect data for your labels with your mobile device and create a machine learning model with a single click. Then scan the QR-code of the model and your actions are predicted by the model in real-time. It's really interesting how accurate the predictions are even with a small sample size.
Possibly-pathological usage report: training with default parameters against three samples each of tapping the left and right edges of my device ~rapidly (2.5Hz?) doesn't produce a model that can accurately infer which side of my device I'm tapping.
I wouldn't be surprised to learn that adjusting the model parameters or adding more samples would likely remedy this. (By all means go dig out the samples and model created under "i336_" if you're interested.)
The UI is also notable as well. I initially visited on desktop because that's what I was already using, then realized the site is actually designed to be used in a desktop/device split scenario. Nice.
Some pedantic UI nits, in case you want them :) -
- The backend very occasionally 503s, which creates a toast/popup full of HTML in the UI. Only noticed on desktop, but can probably also occur on device too.
- The current approach of tap-label-then-begin-typing-name-to-rename is cool but doesn't catch the backspace key, and I also had to guess that I could type. Create-textbox-on-mousedown would be more intuitive ("ah yes clicking this does let me rename it") and also eliminates the gotta-catch-all-the-keycodes problem.
- I can't either preset the countdown and duration, or have it be persistently saved on mobile. (I wanted to set countdown to ~1-2 seconds.)
- If you submit an empty countdown in the mobile UI the site gets very confused :) a full page reload was needed
- Once I'd hit Train I was like, "...okay, now what? Oh, the header parts ('Workspaces / blah / blah') are clickable, I click in there to go back. Right then"). Back and/or obvious navigation buttons everywhere would probably be helpful for orientation.
- After leaving the tab for some time then coming back to it I was met with a bouncing "Unauthorized" at the top of the page. The requests for .../samples, .../models and .../workspaces are all 401ing.
That's actually everything. The UI is overall refreshingly straightforward/to-the-point (ie, not full of unnecessary layers of indirection!), and fast.
For example, I didn't realize I needed to create a layer to begin with, then when I created it on desktop it immediately showed up on my phone. Nice. (Next step, long-polling :P)
It's strange, I look at my Google maps histories, and it showed when I traveled by car vs by motorcycle. In a state like California, where lane splitting is legal, I figured they might use [going faster than surrounding stopped traffic] to determine, but since I've moved, it continues to indicate correctly. Only way I assume they're doing this is via accelerometer.
Yes. Activity detection is performed by occasionally sampling the the accelerometer in android phones. IIRC, it is turned on for a few seconds every 60 seconds or so, and the samples are sent through a rather simple ML model that produces: {activity as one of: {biking, walking, running, driving, motorcycling, unknown, <a few i do not remember>}, confidence: float [0..1)} . Source: worked on this long ago at Google.
Wow I never noticed that. I wonder how they do that. iOS activity recognition only offers "automotive", and Android has "IN_VEHICLE" and "TILTING". You could classify motorcycling pretty easily offline with sensor data but I'm not really familiar with how motion data is collected, and how often.
If hacker news had tags, the "anxiety" tag would be increasingly active these days (prions anyone?), but I feel like this right here should worry people more than it does given how many devices most people carry around at all times with an over-confidence in life because they use a password manager and SMS for 2FA.
Doesn’t mention the most prominent one: coordinated activity measured on two wrist accelerometer devices in proximity is a decent-confidence indicator of sexual activity.
What do you mean? At least the current URL [0] returns a response of content-type application/pdf. So the builtin pdf viewer of your browser should display it, no? I know sometimes admins change URLs tho.
Yeah, it only works if you have cookies enabled(works with js disabled). You could use containers or CookieAutoDelete if you use firefox to auto delete cookies later. Or just configure the browser to be on incognito mode always with only third-party cookies disabled.
[+] [-] 0x402DF854|4 years ago|reply
[1]: https://codeberg.org/Freeyourgadget/Gadgetbridge/
[+] [-] harry8|4 years ago|reply
I use this with a lenovo WatchX and it works well. It is pretty basic so you can join the party and hack if you feel it. WatchX is very cheap. ~USD $30 on aliexpress.
I would not ever go near the lenovo watch android app which I consider to be on par with radioactive toxic waste.
Using gadgetbridge & Watch X is superior to the Apple Watch & ecosystem at about 1/10th the cost. Recommended.
[+] [-] schmorptron|4 years ago|reply
[+] [-] unknown|4 years ago|reply
[deleted]
[+] [-] zibzab|4 years ago|reply
I wonder if I can buy a second hand miband and get around that.
[+] [-] 1996|4 years ago|reply
[+] [-] thifhi|4 years ago|reply
You login; create a so-called workspace; add some labels like walking, jumping, tapping on the device etc.. (simple actions for testing purposes); collect data for your labels with your mobile device and create a machine learning model with a single click. Then scan the QR-code of the model and your actions are predicted by the model in real-time. It's really interesting how accurate the predictions are even with a small sample size.
[+] [-] exikyut|4 years ago|reply
Possibly-pathological usage report: training with default parameters against three samples each of tapping the left and right edges of my device ~rapidly (2.5Hz?) doesn't produce a model that can accurately infer which side of my device I'm tapping.
I wouldn't be surprised to learn that adjusting the model parameters or adding more samples would likely remedy this. (By all means go dig out the samples and model created under "i336_" if you're interested.)
The UI is also notable as well. I initially visited on desktop because that's what I was already using, then realized the site is actually designed to be used in a desktop/device split scenario. Nice.
Some pedantic UI nits, in case you want them :) -
- The backend very occasionally 503s, which creates a toast/popup full of HTML in the UI. Only noticed on desktop, but can probably also occur on device too.
- The current approach of tap-label-then-begin-typing-name-to-rename is cool but doesn't catch the backspace key, and I also had to guess that I could type. Create-textbox-on-mousedown would be more intuitive ("ah yes clicking this does let me rename it") and also eliminates the gotta-catch-all-the-keycodes problem.
- I can't either preset the countdown and duration, or have it be persistently saved on mobile. (I wanted to set countdown to ~1-2 seconds.)
- If you submit an empty countdown in the mobile UI the site gets very confused :) a full page reload was needed
- Once I'd hit Train I was like, "...okay, now what? Oh, the header parts ('Workspaces / blah / blah') are clickable, I click in there to go back. Right then"). Back and/or obvious navigation buttons everywhere would probably be helpful for orientation.
- After leaving the tab for some time then coming back to it I was met with a bouncing "Unauthorized" at the top of the page. The requests for .../samples, .../models and .../workspaces are all 401ing.
That's actually everything. The UI is overall refreshingly straightforward/to-the-point (ie, not full of unnecessary layers of indirection!), and fast.
For example, I didn't realize I needed to create a layer to begin with, then when I created it on desktop it immediately showed up on my phone. Nice. (Next step, long-polling :P)
[+] [-] ralusek|4 years ago|reply
[+] [-] dmitrygr|4 years ago|reply
[+] [-] jeffbee|4 years ago|reply
[+] [-] BurningFrog|4 years ago|reply
[+] [-] ccn0p|4 years ago|reply
[+] [-] benrapscallion|4 years ago|reply
[+] [-] harry8|4 years ago|reply
[+] [-] travisporter|4 years ago|reply
[+] [-] inetknght|4 years ago|reply
[+] [-] est31|4 years ago|reply
[0]: https://dl.acm.org/doi/pdf/10.1145/3309074.3309076
[+] [-] lavios|4 years ago|reply
[+] [-] unknown|4 years ago|reply
[deleted]
[+] [-] sarak12070|4 years ago|reply
[deleted]