I'm in the process of creating my first iPhone app. It is an exercise log that will allow users to use the GPS to track a run, then be able to save a map of the route as well as the time/distance and upload it to a website. A local list of runs would also be saved on the device. My question is, what is the best way to implement the saving and retrieval of the map? I recall reading somewhere that the way to do it is to have entities that have latitude and longitude attributes, and then fetch these in reverse by time when plotting the map. This would mean that each entity is a point during the run. Is there a way to store all of the coordinates in an array in one entity so that one entity would represent a whole run?
I haven't really looked at relationships since I'm new to app development, but it seems like I could use relationships to store runs? As in, have the parent entity be the run, and have one of the destinations be all the coordinate entities of that run. Does this sound correct?
Thanks!
Having run as an entity makes sense. For the waypoints along the route, suggest a relationship with a 1-to-many cardinality (that is, one run has many waypoints). The attributes of the run might include start time/date, end time/date. The waypoints attributes might be latitude, longitude, altitude, date/time. You'll probably want to experiment with how you decide to log a waypoint during the run. Maybe collect every minute, or based on moving a certain distance from the last waypoint.
The waypoint with the earliest date/time is the starting point, and the waypoint with the latest date/time is the ending point.
With the above, you can plot the route one a map, calculate speed between waypoints, average speed, total distance, and maybe some sort of difficulty factor based on altitude changes.
Related
I need a framework which takes a set of latitude longitude points and plots on a world map, grouped by country having the count of points as a marker on each country. Grouping here is the count of latitude longitude points in a country.
And as I drill down into a country, the clustering should change to state based one. And the next level, to districts.
Leaflet marker cluster is something very similar to what I have asked for, but the grouping is based on proximity and it doesn't consider country or state boundaries. That is, they are not region aware.
Regionbound.com has tweaked in some code in the leaflet code for making it region aware,
Sample marker definition:
var marker1 = new L.marker([-37.8, 145], {regions: ["Asia-Pac", "Australia", "VIC", "Melbourne"]} );
But the sample code says, every latitude longitude must be defined along with some extra parameter containing place information.
I could get the place information using reverse geocoding, but reverse geocoding every latitude longitude is time consuming right.
Highmaps provided by Highcharts is one another solution, but there, every country has code which should be assigned a value[count of point coordinates belonging to that country].
But all I have is latitude longitude points, no country or state information.
Thus, I need something which takes only a set of latitude longitude and does clustering based on country, state, district depending on the zoom level.
You have 2 separate needs in your questions:
Map your lat/lng coordinates to appropriate administrative areas. E.g. through the reverse geocoding that you mention.
Display "clusters" on those administrative areas depending on zoom level.
As for point 1, you know that lat/lng points do not say by themselves which administrative area(s) they belong to. So "reverse geocoding every latitude longitude" is a mandatory step. Whether time consuming or not depends on the solution you choose to perform this operation.
If I understand correctly, you would like a "framework" that could do that automatically for you. But frameworks are usually data agnostic, and if they do not have data about boundaries of those administrative areas, they cannot help you.
You may rather look for "services" (like the Mapbox Geocoding API that you mention) or software that would already have such data. It is not time consuming if you can program the lookup (or perform "bulk" operations) and if you are not limited by the requests rate and your amount of points to map (which may be the case with Mapbox).
You could very well set up your own application to perform this mapping:
As for the dataset for administrative areas boundaries, you would probably be interested in links in this post: Are there any free administrative boundaries available as shapefiles? If your points are limited to a few countries, it will be easier for you to find the appropriate data source(s).
Once you have that data, many GIS software should be capable of mapping your lat/lng points to the areas they belong to. This would be mainly for a "one-shot" operation, if your set of points do not change much.
A "web-compatible" alternative would be for example to use Leaflet with point in polygon for Leaflet plugin. You would need your boundaries data converted to GeoJSON format first. Again, GIS software should be capable of doing so, or many online services as well (search for "convert geojson" for example).
A server-side solution would avoid having to manage the entire boundaries data through network and in client browser (if you need to perform the mapping dynamically). I am sure many GIS servers are capable of performing this operation, once they are fed with the boundaries data.
For point 2, once you have completed the above step, I think you would have many options available, including those you mention (RegionBound, Highmaps).
Even with standard mapping libraries (Leaflet, OpenLayers 3), you would just need to build your "clusters" (markers on administrative areas with a number saying how many points are in there), like you have to do with Highmaps anyway for example.
Computing the number of "clustered" point is as easy as filtering your points per area name / code. Then switch the clusters to the desired administrative level when the map zoom changes.
So the key is really to determine first to which areas your points belong to (point 1).
Then a small question would rise about where to place the "cluster" marker:
On centroid of the administrative area? You need the coordinates of that centroid from your data source, or a good algorithm to compute it from the boundaries (good luck on that…).
On "center" of the bounding box of the area? Leaflet can easily compute that: from your area vector shape, you would do myShape.getBounds().getCenter().
On barycentre / centroid of the clustered points? This is what Leaflet.markercluster and RegionBound do (do not know for Highmaps).
Good luck!
I am going to design an Android application and I will be needing the distances of the pathways inside our university(pathways between buildings)
I read about OSM(OpenStreetMap) and tried it. It is a map which is editable which means anyone can contribute to that map(like a wikipedia map version).
It has many routing services that give routes and directions between two point(start and end).
There is a routing service named GraphHopper and it is very easy to use. I can just drag and drop the start and end pt and it gives the distance(km) between the two pts.
What I want to know is how did they come up with the distance?
Is the distance reliable and accurate?
Any help is greatly appreciated because I want to use the distances for my Android app and I need to know if these distances have basis.
The distance is 'accurate' in the sense that it correctly processes the existing information from OpenStreetMap and correctly adds road segments for the final route. You can just try for your local area and compare to your own knowledge.
There could be mapping errors, where a road is incorrectly mapped. And there could be also roads missing and so the router uses a detour making the path unnecessarily longer. Also there are different modes like for cars or bikes or fastest and shortest where you get a different distance between two coordinates.
I have a database with the current coordinates of every online user. With a push of a button the user can update his/her coordinates to update his current location (which are then sent off to server). The app will allow you to set the radius of a circle (where the user is in the center) in which you can see the other users on a map. The users outside the circle are discarded.
What is the optimal way to find the users around you?
1) The easiest solution is to find the distance between you and every user and then see if it's less than the radius. This would place the sever under unnecessarily great load as comparison has to be made with every user in the world. In addition, how would one deal with changes in the locations?
2) An improved way would be to only calculate and compare the distance with other users who have similar latitude and longitude. Again in order to be efficient, if the radius is decreased the app should only target users with even closer coordinates. This is not as easy as it sounds. If one were to walk around the North Pole with, say, 10m radius then every step around the circumference would equal to a change of 9 degrees longitude. Every step along the equator would be marginal. Still, even being very rough and assuming there aren't many users visiting the Poles I could narrow it down to some extent.
Any ideas regarding finding users close-by and how to keep them up to date would be much appreciated! :)
Andres
Very good practice is to use GeoHash concept (http://geohash.org/) or GeoModel http://code.google.com/p/geomodel/ (better for BigTable like databases). Those are efficient ways of geospatial searches. I encourage you to read some of those at links I have provided, but in few words:
GeoHash translates lon and lat to unique hash string, than you can query database through those hashes. If points are closer to each other similar prefix will bi longer
GeoModel is similar to GegoHash with that difference that hashed are squares with set accuracy. If square is smaller the hash is longer.
Hope I have helped you. But decision, which you will pick, is yours :).
Lukasz
1) you would probably need a two step process here.
a) Assuming that all locations go into a database, you can do a compare at the sql level (very rough one) based on the lat & long, i.e. if you're looking for 100m distances you can safely disregard locations that differ by more than 0.01 degree in both directions. I don't think your North Pole users will mind ;)
Also, don't consider this unnecessary - better do it on the server than the iPhone.
b) you can then use, for the remaining entries, a comparison formula as outlined below.
2) you can find a way to calculate distances between two coordinates here http://snipplr.com/view/2531/calculate-the-distance-between-two-coordinates-latitude-longitude/
The best solution currently, in my opinion, is to wrap the whole earth in a matrix. Every cell will cover a small area and have a unique identifier. This information would be stored for every coordinate in the database and it allows me to quickly filter out irrelevant users (who are very far away). Then use Pythagoras to calculate the distance between all the other users and the client.
I'd like to know (from a high level view) what would be required to take a pdf floor plan of a building and determine where exactly you are on that floor plan using GPS coordinates? In addition to location, the user would be presented with a "turn by turn" directions to another point on the map, navigating down hallways, between cubicles, etc.
Use case: an iPhone app that determined a user's location and guided them to a conference room or person's office in the building.
I realize that this is by no means trivial, but any help is appreciated. Thanks!
It's an interesting problem. When you're using Core Location, you're not necessarily using GPS. Using WiFi and cell tower triangulation, you can get pretty good location results. So from Core Location you get a latitude and longitude fix. (You might also get altitude info, since GPS data is 3-dimensional. You also will get an accuracy value.)
So you have lat and lon. You need to map these coordinates to the PDF plan's coordinates. Assuming that the plan is aligned with the latitude and longitude lines, and that you have a lat-long fix for one of the points on the plan, you need to calculate the x-axis scale and y-axis scale. Then it's some calculations to map the lat-long to x-y coordinates on the PDF plan.
GPS may not be accurate enough for this purpose, especially indoors. Assuming errors on
the order of 10 meters, you'll have difficulty determining which floor the user is on.
Here's a neat (?) idea that might work: can you post some "You are here" placards
at various locations around the building? You could label each one with a unique,
machine-readable location code (maybe a QR code or something similar), then take an
image using the camera, have your app read that image and interpret the location code,
and use that instead of GPS to determine the start location.
GPS inside? That's your first -- and biggest -- hurdle.
Next hurdle is knowing the GPS coordinates of at least three points on that PDF to define the plane of of your map in the real world. (The PDF will need to be to scale, of course.)
So that gives you where you are on the PDF. Now you'll need to figure out some way to determine where you can walk (or where you can't) to get directions.
I'd like to use reliable locations, even on an old iphone. However, many readings (particularly from cell towers) are too inaccurate. I think.
When I plot my position + accuracy radius (or look at google maps app), I notice the center of the estimated circle is generally close to my physical location. I'm guessing that if I cut the "accuracy" number in half, I'll still be in the circle 99% of the time.
I believe this is a probabilistic game - the location manager is trying to provide an estimate that's correct 99.99999% of the time, so they give a deliberately wide margin. Any thoughts/info?
The CoreLocation framework gives you the radius of the circle for every CLLocation you get using the horizontalAccuracy/verticalAccuracy properties. You can specify to the CLLocationManager a desiredAccuracy property that use these types:
kCLLocationAccuracyNearestTenMeters, kCLLocationAccuracyHundredMeters, kCLLocationAccuracyKilometer, kCLLocationAccuracyThreeKilometers;
So you get notifications when you get inside your desired range. That said, when you use the CLLocationManager the first event is given to you ASAP, and then the proceeding events are the ones that satisfy your conditions.
When you're using CoreLocation, you're getting back "answers" that get better and better. I've noticed that the "best" answer is almost always accurate to within 100m, so theoretically you could probably cut down on the "buffer" that you're normally given. The only way to really know, though, and this is what I would do, is to test test test. Find iphones and ipods from all generations and see what types of accuracies you're getting and what types of results you're getting. In a lot of ways, it depends on the type of app you're making, but if you want to deliver sensitive or important information based on where the user is, you should really wait for the framework to give you a nearly exact location.