Posts Tagged ‘GPS’

The Geolocation API is built into all modern mobile browsers and it lets you take either a quick, onetime snapshot, or you can get continuous location updates. Using the browser to get your approximate location is very, very cool, but it’s also fraught with many challenges. The vast majority of blog posts on this API talk about what it can do, this blog post focuses on how to best use it and understanding the data provided by the API.

To start things out, let’s take a quick look at a short list of some of the challenges when using the Geolocation API.

Challenge 1. You will not know where the location information is coming from. There’s no way to tell if it’s from the GPS, the cellular provider or the browser vendors location service. If you care about these things then the native Android SDK, for example, gives you a huge amount of control over what they call ‘location providers.’

Challenge 2. You cannot force the app to stay open. This means that the typical user has to keep tapping the app to keep it alive otherwise the screen will go to sleep and minimize your app.

Challenge 3. Speaking about minimizing apps, when the browser is minimized the geolocation capabilities stop working. If you have a requirement for the app to keep working in the background then you’ll need to go native.

Challenge 4. You’ll have very limited control over battery usage. Second only to the screen on your phone or tablet, the current generation of GPS chips are major energy hogs and can suck down your battery very quickly. Since the Geolocation API gives you very little control over how it works you cannot build much efficiency into your apps.

Challenge 5. Most smartphones and tablets use a consumer-grade GPS chip and antenna, and that limits the potential accuracy and precision. On average, the best possible accuracy is typically between 3 and 10 meters, or 10 – 33 feet. This is based on my own extensive experience building GPS-based mobile apps and working with many customers who are also using mobile apps. Under the most ideal scenario, the device will be kept stationary in one location until the desired accuracy number is achieved.

What’s it good for? Okay, you may be wondering what is browser-based geolocation good for? It’s perfect for very simple use cases that don’t require much accuracy. If you need to map manhole covers, or parking spaces, or any other physical things that are close together you’ll need a GPS device with professional-level capabilities.

Here are a few generic examples that I think are ideal for HTML5 Geolocation:

  • Simply getting your approximate location in latitude/longitude and converting it to a physical address.
  • Finding an approximate starting location for searching nearby places or things in a database or for getting one-time driving directions.
  • Determining which zip code, city or State you are in to enable specific features in the app.
  • Getting the approximate location of a decently sized geological feature such as a park, a building, a pond, a parking lot, a driveway, a group of trees, an intersection, etc.

What’s the best way to get a single location? The best way to get a single location is to not use getCurrentPosition() but to use watchPosition() and analyze the data for a minimum set of acceptable values.

Why? Because getCurrentPosition() simply forces the browser to barf up the best available raw, location snapshot right now. It literally forces a location out of the phone. Accuracy values can be wildly inaccurate, especially if the GPS hasn’t warmed up, or if you aren’t near a WiFi with your WiFi turned on, or if your cellular provider can’t get a good triangulation fix on your phone, or it returns a cached value from a different location altogether. There are many, many “what ifs?”

So, I recommend using watchPosition() and firing it off and letting it run until the return values meet some minimum criteria that you set. You need to know that while this is happening the location values returned may cover a fairly wide geographic area…remember our best accuracy values are 10 – 30 meters. Here’s a real-world example of Geolocation API location values that I captured over a 5 minute period while standing stationary in front of a building.

5 minute snapshot

What steps do you recommend? Here are five basic steps to help guide you towards one approach for getting the best location. This is a very simplistic approach and may not be appropriate for all use cases, but I think it’s adequate to demonstrate the basic concepts for working towards determining the best possible location.

Step 1. Immediately reject any values that have accuracy above a certain threshold that you determine. For example, let’s say we’ll reject any values with an accuracy reading greater than 50 meters.

Step 2. Create three arrays, one for accuracy, latitude and longitude. If the accuracy is below your threshold, or in this case < 50 meters, then push the values to the appropriate arrays. You will also need to set a maximize size for the array and create a simple algorithm for adding new values and removing old ones.

The array length could be 10, 20 or even 100 or more entries. Just keep in mind that the longer the array, the longer it will take to fill up and the longer the user will have to wait for the end result.

Step 3. Start calculating the average values for accuracy, latitude and longitude.

Step 4. Start calculating the standard deviation for accuracy, latitude and longitude.

Step 5. If your arrays fill up to the desired length and the average accuracy meets your best-possible criteria, and the standard deviation is acceptable then you can take the average latitude, longitude values as your approximate location.

For an example of this simple algorithm at work visit the following URL on your phone and step outside to get a clear view of the sky: http://esri.github.io/html5-geolocation-tool-js/data-test.html.

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Posted in Browsers, GPS | Comments Off

Is a consumer smartphone GPS good enough?

When I presented at OSCON  (O’Reilly’s Open Source Conference) in Portland, Oregon this last week on native Android GPS and Geolocation, I was repeatedly asked the question “is the GPS in smartphones good enough?” In general the answer is “yes”. But, I should back this statement up by looking at several everyday types of scenarios to help illustrate my answer.

What does accuracy mean? First lets briefly look at what accuracy means. Accuracy, in a technical sense, means you get a latitude, longitude and accuracy number from the GPS. Then you can draw a circle using the accuracy number as radius around the latitude/longitude point. It’s highly likely that your actual location is somewhere within that circle. It’s unfortunate that consumer GPS devices don’t also come with a probability factor that would indicate how much to trust the accuracy number. As it is, we will have to take it on a certain amount of faith that our real location is, in fact, somewhere within the accuracy circle.

Under absolutely perfect conditions your typical smartphone GPS chip will deliver around 3 meters (~10 ft) in accuracy for several minutes at a time.  Standing on the highest mountaintop in the Rocky Mountains with no clouds in the sky might come close to being a perfect condition. Under what I’ll call “average” conditions, which reflect everyday in-city usage patterns, you can expect accuracy from 3 – 150 meters (10 ft – 500 ft) or greater and the accuracy number typically fluctuates quite a bit over a period of minutes or hours. GPS signals are affected by anything that interferes with your smartphone receiving the weak transmissions from GPS satellites circling above us. Nearby trees, cars, buildings, big weather storms can all reduce accuracy, and so can being inside a building or underneath trees.

Getting the weather. Now back to the everyday scenarios I mentioned. I bet that most people who own smartphones use them to check the weather at least once per day. Furthermore, weather is typically affecting a large geographic area so the vast majority of forecasts cover cities, counties, States, regions or even entire countries.

I’m going to argue that for this scenario a GPS accuracy of 1000 to 2000 meters, or 0.6 to 1.24 miles is good enough to get started with a finding places app. Values in this accuracy range can be easily and quickly retrieved by a typical smartphone.

Finding places around me. Almost everyone that owns a smartphone has used an app to search for food, gas, groceries etc that are nearby.  There’s no hard written rule, but I think most people would agree that users who are looking for places around them tend to be less concerned about high levels of accuracy. Some applications let you choose target levels of accuracy such as 1 mile, 10 miles or even up to 100 miles for the search radius.

I’m going to argue that for this scenario, as well, that a GPS accuracy of 1000 to 2000 meters will also work perfectly fine.

Real-time driving directions. There are only a handful of applications that do this on smartphones, and even fewer apps do it really well. There’s a lot of hidden math involved in making everything look smooth to the user. These apps wipe away all of the complexity: simply give it a starting point and an endpoint and then away you go.  We’ve all used these types of applications so we know they work well the majority of the time even with the occasional navigational glitch, hardware lockup or low battery.

Social Media location. Hundreds of millions of people use location-aware social media apps every day. Some of these apps provide you with discounts, give-aways and coupons for retail locations that are around you.  For a typical big box store, it’s easy for an app to place you in the parking lot of a Target, Walmart, or a large supermarket and promotions can be based on your location, time of day or day of the week. It’s more challenging for stores with smaller storefronts to use targeted advertising unless someone is simply “in the vicinity”.  For example, tiny stores, kiosks and shops trying to compete in high traffic tourist areas have to compete with many other vendors. In a crowded marketplace area, even with 3 meter accuracy you could be standing next to four or more different storefronts.

A final few words

Hopefully these short examples have successfully illustrated the point that for typical consumer-focused applications smartphone GPS is simply good enough. Certainly there are many, many more scenarios that could be examined so I tried to pick the most common ones. Because of the lower accuracy requirements you can get less accurate results faster from a GPS. Speedy results can mean everything for today’s consumers who have high levels of intolerance for application delays.

The opposite is also true, the greater the accuracy requirements the longer it can take to get a more precise GPS measurement. As I’ve mentioned in my others posts on this subject, it’s takes time for a GPS device to get a fix and then it will try its best to hold onto it as you move around. I suspect that most consumers are significantly less demanding about accuracy as compared to commercial and government users. If consumers were more demanding then there would be a greater uproar about GPS accuracy.

To better understand how to make the most of location data check out the other posts I’ve written in the reference section below.

References:

Six most common use cases for Android GPS

How accurate is Android GPS? Part 1 – Understanding location data.

How accurate is Android GPS? Part 2 – Consuming real-time locations

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Posted in Android, Open Source | Comments Off

If you are headed to OSCON, swing by my session on Mastering Android Geolocation. It’s a deep dive into the Android SDKs android.location package. If you’ve ever wanted to learn about the fundamental’s of the SDKs Geolocation capabilities then this is a must attend session. It will also give you a strong foundation to understand the underlying capabilities of the new Google Play Services SDK that includes Fused Location, Activity Recognition, and Geofencing APIs.

The presentation includes digging into the capabilities of my open source GPS Testing tool that lets you easily test different aspects of the Geolocation capabilities.

Here’s the details and I hope to see you there:

 Location, Location, Location: Mastering Android Geolocation
07/25/2013  5:00pm –  5:40pm PDT (40 minutes)
Room: Portland 251 (capacity: 200)
http://www.oscon.com/oscon2013/public/schedule/detail/28713

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Posted in Android, Conferences, GPS | Comments Off

Where Part 1 focused on non-GPS enabled devices, Part 2 is totally focused on mobile web geolocation. The great news is that the usage of HTML5 location services along-side the fact that there is a GPS chipset in most, if not all, modern smartphones and tablets dramatically improves the chances of getting an accurate location. And, besides that fact — mobile geolocation is simply a lot of fun to work with.

I also want to point out that there are an increasing number of really good blog posts covering the topic of “how to use” the API that look at the nitty-gritty of how the code works. This post is different in that I’ve tried to focus on “how to build successful applications” with the API, and how to get the most out of the API so that you can successfully implement your unique requirements.

What’s different about desktop vs. mobile HTML5 Geolocation? With mobile you can access the GPS if it’s available. It’s important to note that in order to access a device GPS you have to set the optional enableHighAccuracy property in your code. Contrary to what is shown in some samples on the internet, you can use this property with both the getCurrentPosition() and watchPosition() functions.

//One time snapshot
navigator.geolocation.getCurrentPosition(
     processGeolocation,
     // Optional settings below
     geolocationError,
     {
         timeout: 0,
         enableHighAccuracy: true,
         maximumAge: Infinity
     }
);

//Tracking users position
watchId = navigator.geolocation.watchPosition(
     processGeolocation,
     // Optional settings below
     geolocationError,
     {
         timeout: 0,
         enableHighAccuracy: true,
         maximumAge: Infinity
     }
);

How accurate is it??? This is the million dollar question, right? When using enableHighAccuracy() on a phone where all the appropriate permissions have been selected and granted, I’ve typically seen accuracy readings as low as 3 meters (~10 feet) that were obtained within 10 – 30 seconds of kicking off the geolocation functionality. I’d consider that excellent for most consumer and retail applications. You should be aware that like any location-based functionality you will get spurious (abnormal) results that fall way outside the norm, and sometimes these results are wildly wrong.

I’ve seen claims that using the enableHighAccuracy() property slows down the phones ability to deliver a location. I’m going to argue that those claims are misleading. It is true that the GPS, itself, can take a significant amount of time to warm up and start delivering high accuracy results. For an in-depth look at that topic see my post on the Six Most Common Use Cases for Android GPS. However, there are conditions where simply enabling the enableHighAccuracy() property doesn’t affect the speed in which you can get the initial result. More on these topics below.

What is the best way to try out various configuration scenarios? I’ve built an HTML5 Geolocation Testing tool that can be used in browser, or it can be repurposed to work in PhoneGap or Titanium. It is a jQuery-based mobile application that includes a map and settings view were you can adjust all the different properties and try out different configuration scenarios. It’s a work-in-progress so I welcome suggestions and pull requests.

 Why HTML5 Geolocation rather than native? Applications using HTML5 Geolocation typically have slightly different requirements than native GPS-based applications. Each platform has its advantages and disadvantages and it all comes down to your requirements, budget, timeframes and skill sets:

  • Ability to re-use existing JavaScript and HTML5 skills to build a high-accuracy mobile application.
  • Don’t have access to native platform developers or skillsets on Android, iPhone and/or Windows Phone.
  • Need a cross-platform stand-alone web app, or a web app that has been repurposed to work with PhoneGap or Titanium.
  • Quickly locate the user/consumer within a reasonable expectation of accuracy.
  • Typically it is a non-commercial, consumer grade application that does not have extremely high accuracy requirements (e.g. < 1 meter).

How fast can I get an initial location result? The answer is very fast, potentially within a few seconds, given the following scenarios:

  • If there was a cached GPS or Network location stored on the phone. The GPS location is, of course, from the GPS chipset. The Network location comes from your wireless carrier and is dependent on your phone and their capabilities.
  • How the timeout and maximumAge properties are set. If you set timeout = 0 and maximumAge = Infinity it will force the application to grab any cached location, if one is available. Other settings may result in delays.
  • If the phone or tablet has decent internet connectivity and Wifi enabled.
  • If the device is in an urban area with many wifi nodes broadcasting their SSIDs nearby.
  • The device has a clear and uninterrupted view of the sky. GPS’s listen for a very weak signal from multiple satellites. These signals can be partially or completely blocked by buildings, thick foliage, vehicle roofs, etc.

 How accurate is the initial location result? Hah, you might have guessed I’d say that it depends.  When you first kick off a geolocation request, accuracy does depend on a number of different factors that are mentioned above. And it’s safe to say that, in the vast majority of cases, the first location is not the most accurate and typically not the most dependable. If you want the fastest, most accurate location possible then you will most likely need to either do multiple snapshots, or use watchLocation until your desired level of accuracy is met. It’s important to note because I’ve been asked about this many times, you cannot expect the GPS, itself, to have enough time to lock onto a satellite and deliver a fast, accurate initial location. It may take dozens of seconds or even minutes. Yep, it’s true. Factors that affect initial location accuracy include:

  • Cached locations – how recently the user accessed location functionality. For example, applications like Facebook typically grab a location when you open the app. So frequent users of social media are more likely to have a fresh, cached location that non-social media users. If you are targeting business travelers, the cached location might the last city before they got on a plane. Or, it could be your home neighborhood and not where you work or go to games.
  • Wifi turned “on”. If the Wifi is turned on then the device can access the location service and there is a much greater chance that the initial result is fairly accurate. If you didn’t have a chance to read Part 1, when the Wifi is on your browser gathers local Wifi node information from your Wifi card, and it can use that information in a location service provider request over the internet to try and triangulate your position. Typically this means your initial location can be within a block or two of the actual position. Also, it is possible if Wifi is turned on that you can get a significantly more accurate initial location than if you were using GPS by itself with no Wifi or internet.
  • Internet connectivity strength. If you have a poor internet connection and no Wifi, then the browser’s requests to the location service can be delayed, blocked or even interrupted.
  • No VPN. Take note commercial application developers: as mentioned in Part 1, if VPN software is in use it can wildly affect accuracy and even place you in another State (or Country).

Can I use HTML5 Geolocation for mobile tracking? Yes, with caveats. Typically HTML5 tracking applications are built inside a native wrapper framework such as PhoneGap or Titanium. There are several immediate problems with stand-alone, browser-only HTML5 tracking applications. First, there is no built-in functionality to keep the screen from going to sleep. Second, when the screen goes to sleep the HTML5 Geolocation functionality also goes to sleep. Native-based tracking applications can work around these limitations and listen passively in the background when they are minimized. Third, you have little control over the GPS settings to help management battery consumption.

Can I use HTML5 Geolocation offline? Yes! If there is no cellular connection or Wifi available, then HTML5 Geolocation can still access cached locations and real-time GPS information. This is vastly different from what was discussed in Part 1 as related to applications targeted at laptops, desktops and tablets that may or may not have GPS. If a device does not have a built-in or externally available GPS then your offline application will not work.

Handling abnormal location results. Your application will occasionally encounter widely inaccurate results and you need to handle these gracefully for the best user experience possible. My recommendation is to check the timestamps and distance traveled between the current geolocation object and the previous one. If the distance or speed seems excessive then you’ll need to reject the result. In the reference section below is a link to more information on calculating the distance between two points containing latitude and longitude. As an example, see the attached screenshot with the spurious results indicated by red circles. Also note in the screenshot the accuracy level was 3 meters, so it’s important to understand that even at high accuracy levels you still need to very that each location meets your minimum requirements. This way your results will always look polished and professional to the end user.

Spurious results

What are some of the downsides of using HTML5 Geolocation versus native? The bottom line is that for simple location gathering and basic tracking HTML5 Geolocation is just fine. This should meet the requirements for most consumer applications. For anything more complex than that you should consider looking at going native.

  • It may not work on older phones and older browsers (depending on your definition of old). See below in the references section for a link to a fallback library to handle these situations.
  • HMTL5 Geolocation offers significantly less control over GPS settings. This can have an unacceptable impact on more complex applications.  Because of this, I also suggest that HTML5 Geolocation is not suitable for long-running tracking applications.
  • Battery life management. This is a direct result of bullet #2. It’s more challenging to manage battery life with HTML5 Geolocatoin if your requirements call for continuous use of the GPS.  Your control is very limited with respect to these two properties: timeout and maximumAge.
  • Cannot use it when the application is minimized. If your requirements calls for the ability to passively receive locations while in a minimized state then, as mentioned earlier, you will have to go native.
  • Very little control over how often you want location updates. You’ll need to do a bunch of custom coding to emulate what is already built into native application APIs. For example, the native Android API offers very detailed control over what type of geolocation data you can get access to, how you can access it and how often. Read more on that topic in my post on How Accurate is Android GPS Part 1 – Understanding Location Data and also take a look at Android’s LocationManager Class.

References

W3C Geolocation API Specification 

HTML5 Geolocation Test Tool

Mozilla – Using Geolocation

Calculating distance between two points.

Geolocation fallback library for older browsers

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Posted in Browsers, HTML5, Mobile | 19 Comments »

Six Most Common Use Cases for Android GPS

This post summarizes the six most common use cases associated with using GPS and location services on an Android device. It also continues the series on using the open source GPSTester tool to build better location aware Android apps. So not only can you read about what works and what doesn’t you can also try various scenarios out yourself using the tool rather than having to build code from scratch.

I’m striving to make this information freely available because adding location to your apps can be fun, and it can also be an important part of the applications that you build. By taking into account these six use cases you will be able to build applications that better meet your requirements and make for a more enjoyable end user experience.

Use Case 1 – Cold Start. Application launches from a completely stopped state. Cached GPS  and Network location values may be unreliable. As a developer you don’t really have any control over this but you need to plan for it. The screenshot from the GPSTester tool below shows a typical cold start where the cached network location has better accuracy than the most recent GPS location. You can see from the timestamps that even though the GPS location is more recent than the network location, it’s the network location that has better accuracy.

Use Case 2 – Warm Start. Application launches from a minimized state. Cached GPS values may be reliable depending on how much time has passed since application was last running, and the total distance traveled away from when the app was last used. Like the cold start, the user that decides how and when to start the app and you just have to plan for this use case. The screenshot below represents a typical warm start scenario where the cached GPS result has better accuracy than the cached network provider.

Use Case 3 – Minimized. Requirements may call for location listeners to continue to run in the background, or to be shut off when the application is minimized. There is also the option of using what’s called passive listeners which rely on other applications to call location services. Note, if you listen for location changes in  a minimized state you typically won’t benefit from this information until the application is opened again. In my previous posts I’ve stated that if your target demographic uses retail and social media apps this use case may be of benefit if the person uses the device constantly during the day. Many retail and social media apps access location. However, in many commercial use cases using passive location listeners may provide less than desirable results since there is much less of a chance of another application using a location service.

Pros: Running location services while app is minimized can speed up acquisition time when app starts, but only if your requirements call for always-on accuracy at a moment’s notice. If you shut off location then you will save battery life.

Cons: If active location services are left on in a minimized state this can sap the battery without the user really knowing it.

Use Case 4 – Snapshot. Application only needs to hit a minimum level of accuracy before shutting off location services. The screenshot below shows that it took approximately 2 minutes for the device to reach an accuracy of 12 meters. Yep, you heard that right…2 minutes! Also note how much the latitude and longitude of the different providers wandered around the map. The blue dot indicates network locations and the red dot indicates GPS locations. This is just a reminder that consumer-grade Android devices may or may not be accurate enough for your unique requirements.

Pros: Maximizes battery life.

Cons: May cause user interface delays if user needs to refresh the location during a single application session.

Use Case 5 – Continuous duty. Location services need to be constantly on while application is running. The screenshot below shows a use case of the user being in a downtown area with lots of tall buildings, the apps was run for about 10 minutes, then minimized briefly, then opened again for a warm start. The accuracy didn’t change much even after 10 more minutes of testing. As you can see, the GPS provider accuracy has suffered significantly at 153 meters, while the network provider is offering 45 meters of accuracy.

Pros: Best for constant, up-to-date, always on accuracy. Accuracy available instantly (after the device has ‘warmed up’).

Cons: Huge drain on the battery, but you can adjust the minimum distance property needed to trigger a location update.

Use Case 6 – Intermittent duty. GPS is only needed to run at intervals. To test these types of scenarios you can adjust various settings from within the GPSTester Tool’s preferences. Specifically you can modify the GPS and Network properties for minimum update time and distance. This is very powerful as you can easily toggle these settings to test various settings on-the-fly versus have to write custom code.

Pros: Depending on your use cases such as delivery driver tracking application, this can provide a good compromise on battery usage and accuracy.

Cons: You will have to write algorithms to constantly adjust the location service settings to meet the users movement patterns. This may also involve cycling the location services on and off to maximize battery life.

A few comments on testing your use cases. In the GPSTester tool there are a number of settings you can use to adjust how the device will receive location information.

You have full control over which providers are being used whether it’s GPS, Network or Critera.

Location provider indicators on the main screen will show which providers are being used. You can also see which provider is providing the best accuracy as determined by comparing available providers.

There is a list of available providers available on the GPSTester tool as well as table row showing what the device considers to be providing the best accuracy.

References

Android GPS Testing Tool

GPSTest Tool Github Repo

How accurate is Android GPS Part 1 – Understanding location data

How accurate is Android GPS Part 2 – Consuming real-time locations

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Posted in Android, Mobile | 1 Comment »

In part 1, we looked at the six types of location data available through the Android native SDK and talked about how to work with cached location data. As others have also discovered, there is a ton of information to say on this topic and way more than you could pile into a single blog post. So, this post focuses on working with real-time locations. Once you activate the location listeners they will start sending you information and knowing how to handle that data is what this post is about.

The most important take away I hope to leave you with is take time to understand your accuracy requirements and your user’s basic geographic behavior patterns. I’ve tried to liberally sprinkle example use cases to help illustrate some of the concepts.

Time and distance properties. The first thing you’ll notice when you start building location aware Android apps is you can set time and distance properties that affect how often the device will request a location update. This is accomplished using the overloaded LocationManager.requestLocationUpdates() method. These properties adjust how aggressively the device will request location updates by minimum time elapsed and minimum distance traveled. How you adjust these settings significantly affects the battery life. The equation for battery life is straightforward and simple: the shorter the minimum time interval the faster the battery will be drained.

In the code snippet below, the time and distance properties are both set to zero, which is the most aggressive setting.  You’ll get a location update if any change in location is detected at any time. This setting can result in your app accessing the GPS provider as often as 50 – 60 times or more per minute.

locationManager.requestLocationUpdates(LocationManager.GPS_PROVIDER,0,0,listener);

I’ve experimented with this setting by leaving it running, and it drained a fully charge Samsung Galaxy SIII in less than 3 hours. The phone also got very hot to the touch. It takes considerable power to run the current generation of GPS chips. Even using network location requires that the phone use its radio to make an internet request to the location processing server. So, carefully evaluate your use cases and be conservative about the time and distance properties that are needed.

Except for high performance situations, it will be rare when you need location access every second at a zero distance delta. You can also adjust these properties if your app detects a change in the usage pattern. For example, if the user slows down for a period of time then you might restart the listener using a longer time interval. The listener does not have to stay static and be set only once. Hopefully this is your “ah-hah!” moment. In fact I encourage you to make dynamic adjustments to the intervals as your usage scenarios change. The GPSTester tool allows you to easily experiment with different configurations.

Here are some use case examples:

  • Real-time tracking app for use when walking, running, biking or driving.  As expected, this app will require the most aggressive settings for time and distance.
  • Delivery vehicle tracking app. The delivery vehicle will be starting and stopping all day long. Minimal ability to plug phone into charger. This app should dynamically adjust its time and distance settings.
  • App only needs a one-time snapshot location to find nearby coffee shops. This requires that the app run until a minimum accuracy value is received and then it can turn off the location listeners. Other examples are placing a geotagging a photo, tweet or Facebook posting. You could also try your luck using the overloaded Location.requestSingleUpdate() method.

And, here’s a very basic set of technical requirements for dynamically changing requestLocationUpdates() settings:

  • Start application using minTime = 0 and minDistance = 0. Use an aggressive setting to get accurate location as quickly as possible.
  • Once accuracy is less than 50 meters and speed less than 45 mph set minTime = 5000 and minDistance = 25.
  • Speed equals 0 for greater than 1 hour. Shut off location listeners and notify user.
  • Battery gets low. Shut off location listeners and notify user.

Time to 1st real-time location. It can take up to several minutes to get the first GPS or Network location result. Use effective notifications to let your users know there will be a delay in getting this information. For example, many Android mapping apps use an accuracy circle around the current location indicator to give a sense of accuracy level. 

As you can see in the GPS Provider screenshot taken from the GPS Tester app, using a warm GPS it took ~9 secs to get the first GPS result from the device and then 1450ms to get the next update for an accuracy of 3.0 meters.  By warm I’m referring to a device where the GPS and Network location have been accessed recently.

How long it takes to start getting accurate results depends on many different factors of which you, as the developer, will have very little control over but you’ll need to plan for accordingly. As discussed in Part 1, many developers lean heavily on the cached locations to try and work around these types of delays. Yet, depending on your use cases and the end user personas these results can either be very useful or fantastically inaccurate.

According to Google user interface responsiveness guidelines 100 to 200 milliseconds is where users will start to perceive slowness and we are talking about 9 whole seconds here that the user had to wait. Of course 9 seconds is “fast” for a GPS acquisition. And, you can typically expect much longer time frames, especially on a cold device, and until the accuracy drops down to within a few hundred meters or less.

I’ve seen differences in acquisition times between two phones of the same exact model and same settings even though they were placed right next to each other. Other factors that affect acquisition times can be as simple as where you placed the phone in the car such as down by the gear shift between the seats or up on the dashboard. Or the user could be standing just inside a restaurant under a metal awning because it’s raining outside.  The list goes on and on. Cement, bricks, metal, car bodies, heavy foliage and buildings are some other examples of things that can interfere with GPS signal accuracy and the time to first acquisition. Like the Boy Scouts say, “Be Prepared” and be kind to your users by using user interface notifications to let them know of location acquisition delays.

Streaming real-time locations. Once the device starts providing real-time locations, my suggestion is to check the accuracy of each result and consider rejecting those greater than a certain amount that are based on your requirements. The longer the location provider runs, and if the device has an unobstructed views of the sky and good cellular connection, then typically the accuracy will improve up to a certain point and then level off, and then it will fluctuate.  Here’s a pseudo-code snippet showing how to check the accuracy of each GPS location result:

public void onLocationChanged(Location location) {
     if(location.getAccuracy() < 100.0 && location.getSpeed() < 6.95){
          //Do something
     }
     else{
          //Continue listening for a more accurate location
     }
}

Here are some rough examples of accuracy thresholds I used for a project last year. Your requirements may vary as to how these different thresholds will affect the behavior of your application; these were examples that required geocoding that converted the current location to an approximate address. Depending on the result the application gave different feedback to the user:

  • Rooftop  <= 10 meters (desired result)
  • Street >10 meters and <= 100 meters (let user know it’s close but not perfect. Good enough?)
  • Neighborhood > 100 meters and  <= 500 meters (give visual feedback that accuracy is low)
  • City > 500 meters and <= 2000 meters (ask user to verify city name from a list)
  • County > 2000 meters (prompt for manual location input)

Take into account your own unique use cases. You might completely reject any accuracy value greater than 100 meters (328 ft) if your app simply helps people find open parking lots at NFL games. You could have an app that returns a list of Dentist offices within a 5 mile (8000m) radius. Or a weather app could only need to know approximately what city you are in. These are just ideas to help get you thinking.

Not all real-time location data is alike.  Continuing on the theme of consuming real-time location, let’s dig into a few more examples of why it should be looked at closely. Here’s one thing that I keep forgetting even though I’ve blogged about it: you can get null location values and if not properly handled they will crash the app. That’s an easy one to forget until your users start to report random application crashes.

You can also look for what I’ll call spurious results. These are results that are way outside what you might consider a running average. Check the distance between the last location result and the current location result using the Location.distanceBetween() method. If the distance and speed required to cover that distance is significantly greater than the running average, then you can reject that result.

I also want to mention that simply holding the device in one location while standing outdoors can result in the latitude/longitude wandering over a reasonable distance. Even if you set the phone on a rock the results can wander. Just keep this in mind if you have accuracy requirements. Just because the user is standing still outdoors doesn’t mean that the indicated location will stay exactly the same. It could wander over a 10 to 50 meter radius or more.

I have occasionally seen wild location fluctuations that were enough to make a mapping application nauseatingly jump back and forth between different center points. Unfortunately, when it happened I didn’t have the device on a debugger, but I suspect it had to do with the phone detecting various WiFi end points when I stopped at stoplights along my route. It’s possible the phone tried to resolve those WiFi locations using the Google Network Location service and that there was some lag time in processing those results.

Are Android, off-the-shelf, retail smartphones as accurate as something like a Trimble Pro Series Receiver? No way, not all, definitely not! If you have high accuracy, field-usage requirements calling for sub-meter results you should not be using a typical retail Android device. For example, if you are standing in an intersection with four manhole covers that are two feet apart and form a circle, you could not accurately map which manhole cover is the right one that you need to be working in if you are using an off-the-shelf Android. Using my own phone as an example, on a good day my Samsung Galaxy SIII occasionally has down to 3 meters GPS accuracy for short periods of time and then it can start wandering.

Comparing Network and GPS locations and using Criteria. Yes, you should definitely compare the results between these two. The more data you have the better. There’s not a whole lot to say about this other than look at timestamps, accuracy and distance traveled factors. In my experience, just something to keep in mind is the network locations happen much slower than the GPS. I expected this because of the lag time involved with the phone sending information to the remote location service and then waiting for a result to come back. You can read more about how location services work in this article.

The use of android.location.Criteria can also be used to control which listener(s) are used. You can experiment with Criteria using the GPSTester tool. The only minor caveat is it doesn’t include all possible criteria in the current version (v1.2.1.1). My general recommendation is to skip Criteria and hard code in the validation rules. I don’t currently subscribe to the idea that the Criteria will know what’s best for my end users. Please comment below if you feel otherwise, but in my own experience I haven’t come across a use case where Criteria gave what I thought was the right answer. In one use case, the Criteria was set to not incur costs, yet the value returned was to use the network provider even though GPS was available. Using the network location service would have incurred bandwidth costs.

What to do when app is minimized? A common workflow is for a user to minimize the app and then either forget about it or come back to it later. I’ve included this because it’s common for the user to get a phone call or a text message that results in the app being minimized. In most of the use cases I work with, the requirements call for both the GPS and Network Location services to be shut off when the app is minimized. It’s just way too easy for the user to forget about the app and then it could kill the battery in a very short time.

There is the option of using a passive listener. I rarely use these because it assumes some other unknown application will spin up the GPS or Network Location providers.  Your use cases will help you decide whether or not implementing a passive listener is a good idea. If your target audience is a 20-something student who is constantly using location based social media such as Facebook every hour and eighteen hours a day then there’s a good chance the passive listener will return recent and mostly accurate results. However, if you are building a commercial-grade application on a work-related phone then a passive listener is significantly less likely, or even highly unlikely, to speed up the applications ability to get a fast fix on startup.

Use Intents when implementing a passive listener, this involves adding directives in the AndroidManifest.xml as well as writing some code. A great example of how to do this can be found here, so I’m not going to reinvent the wheel. Just don’t forget to add the receiver tag to your manifest:

 <receiver android:name=".receivers.PassiveLocationChangeReceiver"/>

When the app restarts you can use information from the passive listener and consider whether or not it meets your accuracy criteria. You can also use the passive listener to run background processes within your app while it is minimized. You’ll use the Location timestamp once the app is opened again. If the timestamp is very recent, such as less than one hour old, then you could consider using the passive location immediately. Otherwise, you’ll be back to waiting for a real-time location result. For this approach consider comparing Location.getRealtimeNanos() to SystemClock.elapsedRealtimeNanos(). If your target audience are business travelers, then for example you might want to reject cached results that are greater than 8 hours old because chances are the user has hopped on a plane.

Privacy, data storage and data consumption. Yeh, it’s a bummer I even had to bring this up. I’m not a lawyer, but every lawyer I’ve worked with on these types of production applications strongly reminds me to have a Privacy Policy and to be transparent about how the data is stored and how the data is used. Don’t try to do this on your own, hire a lawyer or the equivalent of a lawyer in your country, as the case law is constantly changing and can vary from State-to-State and Country-to-Country.

And, that’s the wrap-up for Part 2. Stay tuned for additional posts on this series that cover using the GPSTester tool and how to interpret the results.

References

Google Developer docs – Location Strategies

Android blog – Deep dive into location

GPS Testing Tool (open source)

HTML5 Geolocation API – How accurate is it, really?

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