No GPS required: our app can now locate underground trains

Edit: found it. https://medium.com/snips-ai/underground-location-tracking-3e...

I am actually currently working on a project to record the sound of the London Underground passing under me.

We can very clearly hear the Northern Line under us. It's < 30 meters below us.

I have become obsessed with getting high-quality, low frequency recordings of it passing under us.

Why? I don't know. I just can't take my mind off it.

For example, there are two tunnels (north and south bound). By correlating it with actual TfL data, can I figure out the sound signature of each?

More intriguingly, I know that there are maintenance vehicles that operate under us in off hours. Can I "catch" them?

I'm not sure what else I might do with this project, but the idea of capturing the sound of this semi-ephemeral creature that operates below me has captivated me.

Whoever wrote this did a fantastic job.

I figured someone was working on this but it’s so refreshing to read about the thought and level of detail that went into your design. What an effort too! Congratulations transit team, you all should be so proud for solving what I’d imagine is one of transit’s largest small gripes.

Or is the hardware in smartphones too inaccurate even with the extra information?

Sort of related, what I find kind of silly, is that my car probably knows really well where I am, but can't help my phone figure out where my car is pointing to despite being connected to it.

My point is, I see only one real business case for this.

I see they support the the largest cities in Sweden and Norway, wonder if there are any plans for Copenhagen, Denmark?

1. Seems a bit weird to be looking at the accelerometer data yet miss the obvious approach of summing up the acceleration to get the velocity and then summing that up to get position. Yes I know about drift but even then I'd assume the fairly constant several-second g force of pulling in or out of a station or taking a curve would be a strong signal easy to distinguish from short lived jostling.

2. The "train moving" frequency you discovered via fourier analysis was most likely the hunting oscillation. This has to do with how the wheels of the train are designed to force it to turn opposite to any deviation from the direction of the track. Thus there is a back and forth "hunting" for the center that is completely determined by the geometry of the track and the wheels, and therefore the length of track per complete back-and-forth cycle (aka the wavelength) is constant. The frequency of the oscillation (aka back-and-forth cycles per second) is just this constant length divided by the velocity of the train. This fact could be leveraged to estimate the actual train speed rather than just moving/not moving.

3. Combining 1 and 2, a combination of integrating acceleration and confirming / correcting estimated velocity with the expected hunting oscillation would likely be the most powerful / reliable model.

4. Using a classifier seems overkill here. But I'm sure at some point it was easier to just raw-data it than work out a theory driven model which accounted for all the practical confounding factors.

Yesterday night and this morning it kept telling me to get off the train either two early or too late, and this evening it didn’t even think I got on the L in the first place. The app even lightly scolded me for “missing” my train!

The motion detection might be a convolutional network or an svm. The mixer model perhaps a classic neural network.

I don't believe any of those are encrypted and transmit ~1000-10000 time per second on 1500-1600mhz spectrum which is fairly simple to reproduce using even a cheap SDR kit.

It could also work with 0 input from the train's telemetry - in much the same way as the app - the device would get a reference gps signal (or wifi/BLE when it knows it's in the station), then with a built-in accelerometer (which it has the luxury of direction + stability if it's mounted in the train car) it can determine with greater accuracy where the train is and how far it's moved.

Knowing the next station is usually a solved problem that doesn't need a smartphone, because that's displayed in the train itself and called out on speakers. But once you are on the platform and you need to ask the route planner what the fastest route is to a specific station (It could be walking to the surface and taking a bus, so it's not as simple as looking at the subway map) - then you are out of luck if platforms don't have 4/5G coverage!

Would be useful if I could teach this to your app.

I’m curious about the failure cases. Are they caused by exceptional circumstances, such as the train moving more slowly than normal or skipping a station? Or when you unexpectedly catch an express train or go the opposite direction? Does the algorithm know that it doesn’t know where you are, or does it confidently tell you the wrong station until the GPS is acquired?

I have noticed that a year ago or so, Google Maps app would lose the GNSS signal and stop updating the position while there was no signal. But now I have noticed that the position is updated, although is not accurate. I wonder if something similar has been implemented...

Wildly inaccurate even with GPS it seems.

Instant uninstall. Sorry.

That being said, if this app could convince cities to also be used for payment that would be a game changer. Uber for public transit would really remove so much friction from using transit.

Just show the predicted location of the train they should be on separately from their last known GPS position. Of course it would be difficult to market that alone as a novel innovative AI feature.

At least in NYC it should listen for door beeps.

I'm guessing this app won't work that well there. In fact it would probably generate false positives when labeling stations... ?

ML level - for some reason, made me think of ITER / fusion research trying to predict plasma behavior with ML also. Any specific connections people in the know care to point out?

One correction though - there is no subway line that goes across the Queensboro.

I found this to be a really well-done video on using quantum physics to track location integrating upon acceleration

I was excited to try it out but bummed to see my city isn't listed. It's even more disappointing considering Ulm Germany (with around 100k people) is there, but Cologne Germany (with a population of about 1.1mil) isn't.

There are lots of potential users here, especially since the official apps are aweful.

I think the answer is still unclear since they are using pre-determined routes (easier to track east -> west or east -> southwest than it is east -> north -> south -> north -> east again). But this is very cool that they have so much of the work done already. Maybe even all of it? I don't have the code to look at so ¯\_(ツ)_/¯

Either way, still freaked out they read my mind lol

Even without gps data, just having access to your phone accelerometer is enough to give a lot of data about your life. Cumulated with Google insanely big amount of data about wifi access point location, it means that they know where you are even without gps activated and how you got there.

https://en.wikipedia.org/wiki/Dead_reckoning

The first car navigator, the Etak, came out in 1985 and used dead reckoning and quantization to tell where the car was on the map; see this excellent article from 2017:

https://www.fastcompany.com/3047828/who-needs-gps-the-forgot...

Today dead reckoning is used in aerial navigation, and commercial planes (and others) are equipped with Inertial Navigation systems to supplement GPS information; they are getting more and more precise but can still go wrong and need frequent re-calibration.

The next step is "Quantum Positioning System" that promises to detect infinitely small movements and produce perfect dead reckoning at all times, with a precision of the order of one centimeter. It has already been tested successfully. For now the machines are heavy and extremely expensive, but it's imaginable that in some not-so-distant future the technology will be much more available.

https://newatlas.com/aircraft/quantum-navigation-infleqtion-...