Has anyone experience of GPS on iPhone?

Mark Waddingham mark at livecode.com
Wed May 6 10:52:18 EDT 2020


On 2020-05-06 14:09, Graham Samuel via use-livecode wrote:
> Bill, I think you are confirming that there is some mystery here.
> There are a lot of apps that seem to get location, and measures
> derived from location, almost completely right, whereas I am having
> trouble doing so with what must be the same essential data.
> 
> How then to avoid either under- or over-estimating the trip distance?
> Plenty of apps have done it but I just can’t see how, although I keep
> tinkering with the parameters. Of course I can never forget that my
> scripting might just be plain wrong, but so far my incremental method
> hasn’t worked sufficiently well, in the sense that if run the app and
> choose to walk in an exact straight line, I can compare a single
> measure of distance from the starting point with my integral approach.
> So far the result is not even close. As you say, intensive Internet
> searches are called for.

I'm pretty sure that the data you are getting is precisely what all 
other apps will get - we are just returning the location data as 
provided by CoreLocation. The difference will be the analysis which 
these apps are doing on the data to derive an accurate assessment of the 
route taken I'd imagine. Indeed, it could be they also take into account 
other senses (compass and accelerometer) to help - but I don't know that 
for sure.

There are two functions which might help you with your endeavour:

   mobileSetLocationHistoryLimit
   mobileGetLocationHistory()

The details are in the docs, but basically the engine can collect and 
keep a list of locations which you can collect periodically.

I suspect the way to think about this is not to think about it as an 
incremental thing at all as any outliers will completely destroy the 
accuracy. Instead imagine it as a 'curve-fitting' exercise (piece-wise 
linear approximation is probably sufficient!) - i.e. taking sets of 
(slightly) overlapping samples and derive a 'best-guess' path which fits 
the data.

It is likely that some cleaning of the data would be needed first to 
eliminate outliers also. e.g. You can compute speed needed to get 
between individual points, if any given point is outside of a reasonable 
range of 'current' speed with approximated acceleration/deceleration 
taken into account then it should be discarded.

Doing a google search for "deriving a approximate path from gps data" 
turns up quite a lot of literature on the subject, so this is definitely 
something which has/is studied in depth...

Warmest Regards,

Mark.

-- 
Mark Waddingham ~ mark at livecode.com ~ http://www.livecode.com/
LiveCode: Everyone can create apps



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