An iOS application uses the geofencing for notifying the user about predefined nearby locations. The application is allowed to miss some location (the user is not getting a notification about a nearby location), but it is desirable to keep the missing rate low.
One way to implement this would be to start monitoring for significant change locations with startMonitoringSignificantLocationChanges and each time the "location change" event is fired, look for locations within, let say, 500m radius of the reported location.
What worries me is the requirement to perform the query for the nearby regions each time the significant location change occurs and it impact on the battery.
The other way to do it would be to register the locations with startMonitoringForRegion but Apple has put a (reasonable) limitation on the number of simultaneously tracked regions which is 20 and we have significantly more than 20 locations. So some sort of dynamic updating of the tracked regions is required but I am still unsure what is the best way to do it.
Any ideas on how can it be done so that it keeps the battery consumption low but also has the low missing rate for locations?
Since there was not much activity on the question I will describe how we are currently solving this problem.
We tied the reloading of the new regions to significant location change (SLC) events. When an SLC takes place, we check for 20 neighbouring regions that should be "geofenced". To find the 20 closest regions we are simply approximating 1'' of the latitude and longitude according to the following formulae:
Latitude: 1 deg = 110.54 km
Longitude: 1 deg = 111.320 * cos(latitude) km
and just check the bounding square of the current position of the device for the centers of the monitored regions (see: Simple calculations for working with lat/lon + km distance?)
So, for example, if (10N,10E) is the current location of the device we start with the bounding square with vertices at (10-1',10-1'), (X-10',10+1'), (10+1',10+1'), (10+1',10-1') (at latitude (10N,10E) one latitude/longitude minute approximates 1,85 km).
If there are 20 (or almost 20) - we register them for the geofencing and wait for the next SCL. If less/more, just increase/decrease the size of the bounding rectangle and repeat the search.
You can tweak this search algorithm for a better performance, but the one described here will already do the job.
You could reserve a location for a "meta-geofence" encompassing all the currently monitored locations. When the user leaves this geofence, the app will be notified. Then the app can update itself and stop tracking the farthest areas and start tracking new areas in the vicinity.
I thought I would add another option for using more than 20 Geofences in your app. This way has been working well in our app for a long time now and uses CLLocation methods that are built-in.
- (void)locationManager:(CLLocationManager *)manager didUpdateLocations:(NSArray *)locations {
if (locations.count > 0) {
CLLocation *location = locations[0];
NSMutableArray *sortedFences = [[NSMutableArray alloc] init];
// add distance to each fence to be sorted
for (GeofenceObject *geofence in enabledFences) {
// create a CLLocation object from my custom object
CLLocationCoordinate2D coordinate = CLLocationCoordinate2DMake(geofence.latitude, geofence.longitude);
CLLocation *fenceLocation = [[CLLocation alloc] initWithLatitude:coordinate.latitude longitude:coordinate.longitude];
// calculate distance from current location
CLLocationDistance distance = [location distanceFromLocation:fenceLocation];
// save distance so we can filter array later
geofence.distance = distance;
[sortedFences addObject:geofence];
}
// sort our array of geofences by distance and add we can add the first 20
NSSortDescriptor *sortByName = [NSSortDescriptor sortDescriptorWithKey:#"distance" ascending:YES];
NSArray *sortDescriptors = [NSArray arrayWithObject:sortByName];
NSArray *sortedArray = [sortedFences sortedArrayUsingDescriptors:sortDescriptors];
// should only use array of 20, but I was using hardcoded count to exit
for (GeofenceObject *geofence in sortedArray) {
CLLocationCoordinate2D coordinate = CLLocationCoordinate2DMake(geofence.latitude, geofence.longitude);
CLLocationDistance radius = geofence.radius;
NSString *ident = geofence.geofenceId;
CLCircularRegion *fenceRegion = [[CLCircularRegion alloc] initWithCenter:coordinate radius:radius identifier:ident];
fenceRegion.notifyOnEntry = geofence.entry;
fenceRegion.notifyOnExit = geofence.exit;
[locationController.locationManager startMonitoringForRegion:fenceRegion];
}
}
}
Hopefully this will help someone or steer them on the right path.
If you are concerned about performing the proximity check on each significant location change, you could use a spatial indexing/search method like R-trees or R*-tree to reduce the number of comparisons needed for each location change, as those search algorithms will filter out (possibly large) spatially irrelevant regions. That should reduce the time/battery power needed to perform the proximity checks.
I know this post is old, but for those looking to do something similar, Skyhook offers the ability to geofence an infinite number of venues.
From their marketing:
Skyhook’s Context Accelerator enables app developers and advertisers to instantly deploy Infinite Geofences to any brand chain (such as CVS) or venue category (such as convenience stores) through a simple web interface. Using the same patented technology from Skyhook’s first-party location network, the Context Accelerator SDK manages those active geofences on-device, regardless of OS limitations allowing for infinite geofencing.
Related
I would need very accurate speed for my app, even when the user is only walking. I tried using the GPS, it works well but not for speeds that low. So my question is, could I use the accelerometer to get some more accurate values? If yes, how would I do that?
I do not think you will get something from accelerometer. Accelerometer only returns you motion (x,y,z). I do not know how you could able to get speed out of that, unless you will do some linear modelling algorithm that requires heavy research, that could be a Ph.D topic I guess.
I propose the following implementation.
- (id) init
{
self = [super init];
if (self != nil) {
self.manager = [[CLLocationManager alloc] init];
self.manager.delegate = self;
[self.manager startUpdatingLocation];
}
return self;
}
- (void)locationManager:(CLLocationManager *)manager didUpdateToLocation:(CLLocation *)newLocation fromLocation:(CLLocation *)oldLocation
{
NSLog(#"Speed = %f", newLocation.speed);
}
or you could use directly CMPedometer class which I believe that class developed exactly for physical activity applications. I have recently used that class and I am quite satisfied.
import CoreMotion
let lengthFormatter = NSLengthFormatter()
let pedometer = CMPedometer()
pedometer.startPedometerUpdatesFromDate(NSDate(), withHandler: { data, error in
if !error {
println("Steps Taken: \(data.numberOfSteps)")
var distance = data.distance.doubleValue
println("Distance: \(lengthFormatter.stringFromMeters(distance))")
var time = data.endDate.timeIntervalSinceDate(data.startDate)
var speed = distance / time
println("Speed: \(lengthFormatter.stringFromMeters(speed)) / s")
}
})
could I use the accelerometer to get some more accurate values
No, the accelerometer cannot tell you anything about speed. Acceleration and speed are very different things. Indeed, during motion with a constant speed, there is no acceleration (except gravity and similar side effects). You could travel at the speed of light and experience no acceleration (if you could travel at the speed of light).
It really isn't possible to get a decent speed estimate from the Accelerometer. That even if you start with the device at rest and end with it at rest and alsoo using the gyroscope.
Averaging the GPS location is probably the best, possibly a moving average of some sort.
I already have answerded similar question many times.
The apporach with the accelerometer will not work well for more than some seconds. The cause is the dramatic accuracy loss due double integration.
This is well explained in a Goole Talk "Sensor Fusioning" video.
What you can do, for low GPS speed:
A bit simplified:
1. Take locations evry 5 seconds,
2. calculate distance between fix(i-5) and fix(i),
3. calcuate time difference,
and cacluate then the speed in m/s by distanceMeters / timeDeltaSeconds
An advanced solution would use a time window of let's say 5 seconds,
and this evaluation window will move 1 step further every second,
using the same 3 calculation steps as above
I am working on a tracking app, which needs to display the tracking path on map. When I start updating location and does not move the device after the installation, the locationManagar reports wrong location updates,
I am drawing a route based on location points reported,
Also when user is driving in a vehicle at high speed on straight road, it shows glitches like this as well,
How can I ignore these erroneous location updates.
You can download the app here and test yourself
Have a look at Horizontal Accuracy check this to make sure you have an accurate location. For example below 10meters or below zero:
// test that the horizontal accuracy does not indicate an invalid measurement
if (lastLocation.horizontalAccuracy < 0)
return;
And make sure you have a new location because it will return the last one default:
// test the age of the location measurement to determine if the measurement is cached
// in most cases you will not want to rely on cached measurements
NSTimeInterval locationAge = -[lastLocation.timestamp timeIntervalSinceNow];
if (locationAge > 5.0)
return;
Also make sure you set the right desiredAccuracy on the CLLocationManager. For example:
_manager.desiredAccuracy = kCLLocationAccuracyBestForNavigation;
I'm wondering if there is a way to check if a user is actually at a specific location or not (or maybe within 50-100 feet of it). I have a CLLocationCoordinate2D defined and I know I can check my mapView.userLocation.coordinate.latitude and mapView.userLocation.coordinate.longitude, but I'm not sure what the best way to check this would be.
Basically you just have to compare the lat lon and calculate the distance. Luckily, iOS has a built-in method for that inside the CLLocation class.
Here is a simple way to do it.
CLLocation* location = [[CLLocation alloc] initWithLatitude:marker.coordinate.latitude longitude:marker.coordinate.longitude];
CLLocationDistance distance = [location distanceFromLocation:userLocation];
the returned value is in meters which you can then easily convert to feet or any other unit of measurement that you are interested in.
Here is the documentation for reference
I am making an alarm that shuts off only after the phone has been moved a certain distance(to force the user out of bed). I need to be able to find the distance travelled after the alarm has gone off, then take this distance and use it in a method to shut the alarm sound off if the minimum distance has been travelled. Any ideas?
I'm using the following to update the location. Any thoughts on how to incorporate this into disabling the alarm?
-(void)locationManager:(CLLocationManager *)manager didUpdateToLocation:(CLLocation *)newLocation fromLocation:(CLLocation *)oldLocation
{
if(!newLocation) {
NSLog(#"No movement");
}
if ((oldLocation.coordinate.latitude != newLocation.coordinate.latitude) &&
(oldLocation.coordinate.longitude != newLocation.coordinate.longitude))
{
CLLocation *loc1 = [[CLLocation alloc] initWithLatitude:oldLocation.coordinate.latitude longitude:oldLocation.coordinate.longitude];
CLLocation *loc2 = [[CLLocation alloc] initWithLatitude:newLocation.coordinate.latitude longitude:newLocation.coordinate.longitude];
CLLocationDistance distance = [loc2 distanceFromLocation:loc1];
if (distance>=4) {
NSLog(#"Very good!");
}
}
NSLog(#"Location:%#", newLocation);
}
-(void)locationManager:(CLLocationManager *)manager didFailWithError:(NSError *)error
{
NSLog(#"Could not find location: %#", error);
}
A couple of thoughts:
You're not considering horizontalAccuracy. First if this is negative for either coordinate, then you just can't do any comparison. And even if they're both non-negative, you probably want to back out the horizontal accuracies if you really want to determine if the user moved a certain distances.
Look at not only the latitude and longitude, but the horizontalAccuracy, too.
You're not considering that when you turn on location services, there are frequently a whole series of coordinates that come in, and the coordinates may bounce around as the horizontal accuracy gets better and better. You want to make sure you don't consider this slow triangulation as the movement necessary to qualify as having gotten out of bed.
Make sure you do your experimentation on a real device, in real world scenarios. Using the simulator is definitely not a good test. Nor is using a device plugged into your computer (because you you want to see your GPS in real world scenario, where someone has moved around before going to bed).
I'd suggest starting with a simple app that logs location events in a database (or other format) and perhaps show the log in a tableview, so you don't always have to go back to your computer to review the results. Fire up that app, walk around, and then look at the location events you get. That will help you get your arms around the patterns you see as people use their actual devices.
Note that if this app is destined for the app store, you'll want to engage lots of different people in different environments and different devices and different scenarios (poor GPS locations, with wifi, no wifi, etc.). Even when you do your own real-world GPS experience with a physical device, you must appreciate that everyone else's may experience different GPS results.
I must confess to some reservations whether the iPhone GPS is accurate enough for this sort of app as a generalized solution, and you'll probably want to warn the user to make sure to plug in their iPhone before they go to sleep so the GPS doesn't drain the battery. You might also want to play tricks like turning on location services after the user has demonstrated that they're up and about. You might also not even want to turn on location services until a few minutes before the alarm, thereby assuring that the GPS is as accurate as it can be when the alarm goes off, but not draining their battery as they sleep if they don't happen to have it plugged in and charging.
Update:
Probably easier than calculating distances yourself, use the location services distance filter (i.e. only generate events when the location changes by x meters). For example:
- (void)startLocationManager
{
self.locationManager = [[CLLocationManager alloc] init];
self.locationManager.desiredAccuracy = kCLLocationAccuracyBest;
self.locationManager.distanceFilter = 5.0; // detect when I move 5 meters
self.locationManager.delegate = self;
[self.locationManager startUpdatingLocation];
}
When I do that, standing completely still, as soon as I turn on location services, I get a whole bunch of events before I even start moving. You can see the GPS warming up, and getting more and more accurate:
latitude longitude horizontalAccuracy
---------------- ------------------ ------------------
39.9482837548282 (82.4963494095571) 65
39.9482817585030 (82.4964543834170) 10
39.9482392622539 (82.4964914314290) 5
39.9481753502422 (82.4964918505242) 5
39.9481269028419 (82.4964797805836) 5
I wait for that to quite down (it took 15-20 seconds in my case), and then I started walking in a straight line, looking at the distance from the last location I got above.
latitude longitude horizontalAccuracy distance
---------------- ------------------ ------------------ --------
39.9481722908476 (82.4964962091138) 5 5.3
39.9482206544289 (82.4965029146363) 5 10.4
39.9482627315828 (82.4965282279839) 5 15.4
39.9483157471204 (82.4965248752227) 5 21.2
I must confess that while I didn't measure it, these distances didn't feel quite right, but possibly within the 5 meter tolerance I set up with my distanceFilter.
Anyway, as all of this evidences, the right process is probably going to be
turn on location services, setting the distanceFilter appropriate for your app;
wait for the location to settle down;
make sure the horizontalAccuracy is even plausible for this process to work at all; and
wait for the new location notification based upon the GPS determining that the distanceFilter has been exceeded.
This never will be perfect (e.g. I had to walk a good 6-10 meters before my "5 meter" distanceFilter kicked in, probably a combination of the GPS lagging a few seconds and the horizontalAccuracy), but it might be "good enough for government work."
(By the way, I've changed my coordinates in the above log, so don't look for me in this Ohio cornfield, but it gives you and idea of the sort of pattern you may see.)
This is my first time posting a question here, but I have found a lot of help from other people's questions.
My question refers to the -distanceFromLocation: function in CLLocation. I had assumed that finding the distance between point A and point B would be the same as that between point B and point A, but I have found that it is not. I have tested this in a very simple case:
CLLocation *test1 = [[CLLocation alloc] initWithLatitude:37.529530 longitude:-122.259232];
CLLocation *test2 = [[CLLocation alloc] initWithLatitude:47.900002 longitude:-103.495102];
NSLog(#"%f vs %f",[test2 distanceFromLocation:test1],[test1 distanceFromLocation:test2]);
[test1 release];
[test2 release];
The output to this was 1907269.942754 vs 1908105.959114, a difference of almost 900 meters.
Though 900 meters may be a small percentage, I am trying to determine if the user is closer to something than an annotation and 900 meters can change that.
My question is, which one of these values, if any, is correct? Also if which location I test against is important, do I need to always test against the same location (e.g. user to destination and annotation to destination rather than destination to user and annotation to destination)?
Sorry that the sample is a bit out of context, as my project is rather large and this illustrates my problem. Any help would be appreciated as this has caused me quite a bit of confusion and frustration.
The error you're observing is 1 part in 2000. Presumably the algorithm used in this method is optimized for speed, so sorting a list of locations on distance is fast, rather than accurate to the millimeter.
If you need accurate results, don't use these methods but find another way. If you need reproducible results, order the arguments in a defined way, e.g. always start with the lower latitude.