[VLM]

You could play substantial DSP style filtering games such that your average human walks at a very constant speed and is mostly either standing perfectly still or walking at a constant speed. So your non-moving data points are rounded to zero and generate an error signal, and your moving datapoints can be average together to a constant generating an error signal, and the error signals can be shared between the two data sets and analyzed and averaged. Also all data has a resultant spectrum when you ram it thru a FFT, and I'm guessing the data spectrum looks a lot different than a noise spectrum enabling all kinds of fun filtering. Further I'm guessing a FFT analysis will show peaks at stride rate, and variations in stride rate will predictably vary velocity.

My first guess was pure optical, an inside out 3-d scanner basically. OK, image analysis shows there's corners and walls, and the building code requires all doorknobs to be at exactly X inches off the floor, countertops Y off the floor, stairs of certain rise/run combos, and the room dimensions WILL round to closest integer inch so you do some curve fitting and the highest correlation dimensions win. Especially when in the article he described it as placing the phone against all the walls. A simple inertial nav system wouldn't care if you held the phone at an angle or upside down, but optical needs flatness. You'd be making one of those 360 degree panorama pix, kind of, then analyzing it.

Maybe I should be creating a 2 zillion pound startup instead of posting to HN?

[mojuba]

Half a zillion idea: use sound echolocation principles.

Edit: http://www.gsmnation.com/blog/2013/06/19/echolocation-app-le...