I'm creating an application that needs to be very accurate such that when an individual is walking past a certain building, it will provide them with information regarding that building. I was wondering could this be accurate enough using the Android Location API? What technical challenges should I consider?
Edit: I am using a HTC Sensation XE although i'm not sure what chip it uses for GPS
There are multiple variable factors here:
1. GPS hardware itself.
2. Even if the GPS hardware is good,you cannot assume to have very good accuracy since GPS works on "Line of sight"...so if there is lots of trees/high buildings/or anything that could possibly cover the satellite from the GPS receiver would decrease the accuracy of the location determined
3.Time and location---Not all GPS satellites are available in all places at all times...and the accuracy depends on the number of available satellites currently above the user in the sky(to say in lay man terms).
4.The speed of the user.This is more to do with the polling time rather than the GPS accuracy,If say the user is moving in a high speed train,it practically becomes impossible to exactly poll the GPS for the location at that required time thus missing the building.
You might want to understand on how GPS works and this is more of a GPS technology limtation rather than Androids.
Cheers.
Basically the answer depends on your GPS hardware. However, do not expect accuracy of a few meters.
See here for a similar question and some aspects for accuracy: https://stackoverflow.com/a/8852790/1127492
According to this question, accuracy of Android phones' GPS can vary from around 5 to 50 meters, but it mostly depends on the performance of the GPS chips, which has nothing to do with the OS per se.
According to the location API doc, you can also try to use the cell towers and wi-fi hotspot for location, but this will typically be even less precise.
Related
I'm building an app using Geofences, right now the minimum radius I can set so my geofence can get accurately detected is 30m. I want to be able to set a minimum radius of 5m.
In the Android Developers documentation about geofences says:
When indoor location is available, the accuracy range can be as small as 5 meters.
What does it mean with the indoor location? Is it something I should enable in the phone? I don't get it. Also I looked over internet and I know that the accuracy of a geofence is perform by the system and cannot get the Wifi RTT or anything else work with it.
What can anyone do to get a better accuracy for geofences?
Indoor location means using bluetooth beacons to determine a more exact location via triangulation. It only works in a predefined area as you need special hardware in the physical location. Getting it down to 5m outside would require GPS hardware more powerful than in the typical phone. The typical phone is accurate to only about 10m in the best case. What you wan't just isn't possible.
Hi i know the working principle of GPS. After some R&D on the same, i have some doubts regarding the Global Positioning System
We all know that GPS can work without internet. But will the accuracy be correct in non-remote areas like Desert, mid-sea, dense forest?
I am in an idea to build an app that utilises, GPS in non-remote areas.
Will the GPS works in restricted areas? For example, in Countries border, ocean border and all?
There is a very good article about cell phone GPS accuracy from Community Health Maps. How Accurate is the GPS on my Smartphone? (Part 1 and Part 2)
In this article they explain cell phone A-GPS. The A stands for assisted, in which the phone downloads the GPS ephemeris (data about the GPS satellite constellation). Without data access the GPS may take several minutes to become accurate because the ephemeris would be downloaded from the GPS satellites.
The GPS system does not have border restrictions. It is space based a radio communication. If you have a good view of the sky and have good satellite geometry you can get good positional accuracy. Many new phones now use GNSS instead of GPS. This is US GPS plus Russian GLONASS and other systems. This helps by increasing the number of satellites available, and the GLONASS satellite system is better in high northern latitudes.
I am trying to get the user's speed from their Android device, but which is the most reliable way to do it?
There is the location.getSpeed() function that uses GPS; is this a reliable way to obtain the speed? Should I instead calculate speed manually using GPS coordinates obtained? Or is there another way that I'm missing to accomplish this?
IMO, best current approach on Android is to use Location.getSpeed() along with the Google Services Location API and the fused location provider. Then, reality-check this value against Google Play Services Activity Recognition.
The fused location provider integrates some other on-board sensors to tweak location data, which is better than GPS alone. Then, check the ActivityRecognition.getMostProbableActivity() method. If the DetectedActivity is type STILL, your true speed is probably equal to 0. If its ON_FOOT, it's probably a low speed (e.g., 1 m/s). If its ON_BICYCLE or IN_VEHICLE, you're probably fine relying on the speed output obtained directly from Location.getSpeed(). You'll also want to check the DetectedActivity.getConfidence() value too, and set your own threshold for a confidence level you feed "confident" with :) when relying on these values.
I'd also definitely suggest that you do NOT simply average sequential positions to get an average speed between two position (if you do this, it needs to be an average over a large number of positions). In my benchmarking on mobile devices (see my dissertation here, pages 105-106, and 137-138 especially), I've found instantaneous speed calculated by the GPS subsystem (which is typically based off of the Doppler shift of GPS carrier signals) to be far more accurate than the positions derived from GPS. 95th percentile of speed observed while stationary indoors (using assisted GPS only, no sensor fusion) was 1 m/s on a Sanyo Pro 200 I tested. I was able to filter out a significant number of position outliers using speed data (see page 137-138) in some intelligent energy management techniques I was evaluating. With sensor fusion, and activity recognition to help filter outliers, accuracy should be better than this on a similar device.
Finally, and I can't emphasis this enough, do you own testing on real devices, as many as you can get a hold off, and preferably the most popular models out there. Android has a variety of OEMs putting out devices, which will all have their eccentricities. Your best bet it to create a solution that targets the most popular models, acknowledging that it's unrealistic to get a solution working perfectly on all models.
It seems that the getSpeed() method is not always reliable, especially at low speed and when gps coverage is not optimal.
You can have a look at this question and this one which are both about alternatives for getSpeed().
The android developper page however says that you'll get better performance by using the Google Location API.
So it appears that the choice is depending on the usage of your app: if you target slow displacement in area with poor gps coverage (walking in the wood), use your own implementation. Fast in area with good GPS coverage, use the Google Location API.
The best way for devices that are moving faster than walking speed, is to use directly the location.getSpeed().
For pedestrian, or other slow speed situations, this is not quite easy, maybe it is simply impossible to have a valid slow speed that is valid at the moment.
Some try to evaluate the history and do an averaging, or threshold based approach, this will improve for a specific application / usage.
But the simplest is to design your App to ignore low speeds.
Some links related to speed:
GPS position correction
Smooth GPS data
I have been developing location tracking apps and testing them mostly on my HTC G1 running Android 1.6. I find that there are certain time intervals -- of approximately 1-2 hours -- when the recorded GPS locations become very erratic: I end up with what looks like a random distribution of points around my actual location, but instead of being clustered tightly within a 10-50 meter circle as they normally are (I use a minimum accuracy for recording these locations), they are spread out with a radius of something like 1-5 km -- even though each of these locations comes in with a reported accuracy of under 50 meters.
It's as if the actual location accuracy balloons during these periods but the reported accuracy remains the same. This is relatively infrequent and when it occurs it lasts only for a few hours, after which everything appears normal again. Because it is so infrequent, and because I am usually also in the process of tinkering with the app, I am having a hard time ruling out the possibility that this is caused by a bug in my code.
Has anyone else experienced this? Are there known hardware or firmware issues that could be causing it? If so, does anyone have a good way of detecting the problem when it is occurring and correcting the reported accuracy values? I assume one option would be to rely on the NMEA sentences, but I would like to be able to run the app on Android API level 4 and I see that GpsStatus.NmeaListener requires 5 or above.
I would really appreciate any suggestions.
1-5km deviance should never happen in GPS receivers.
If that happens then it looks like an alternate location service is active, like cell tower location, and wifi location.
If you want a precise position you should filter out all non GPS ones.
GPS positions can be detected that they have a speed and heading (bearing) assigned when the device moves. (I am not sure if the check for an altitude helps)
The line patterns comes from the situation when a new GPS sattelite comes into the view, and other(s) are going ou of view. The new situation can be worse from the geometric sattelite constellation. This new constellation can also called so called Multi-Path Effects (Reflections of the GPS Signal at the opposite building)
And I hope that you don't do you measurements indoors, (where GPS does not work reliably)
I'm trying to find a solution for pinpointing indoors, specifically inside big crowded places, like malls for example.
I tried building a simple app that tried to pinpoint the phone using only the Network service or Wifi networks.
Usually when Wifi was on the accuracy got to 40-60 meters, and when the wifi was off and only the network service was used, the accuracy got to 600-1000 meters.
Unfortunately that really is too inaccurate for my needs.
I read that Google have successfully added an accurate solution for indoors navigation ( http://www.engadget.com/2012/01/08/google-maps-indoor-navigation-las-vegas-ces-2012/ ) , so I guess there might be a possible way to achieve a higher accuracy. 5-10 meters accuracy should suffice.
I'd be happy to get any kind of advice!
Thanks!
In highly trafficked public spaces, indoor location solutions tend to be based on WiFi mapping combined with known map information. That approach allows an increase in the accuracy of the location information you will get from your cellular device (over results from testing performed in locations not yet mapped). The actual error rate will depend on how dense and well mapped the WiFi hot spots are, whether they are in stable locations or tend to be moved around, the accuracy of the floor plans, and the effectiveness of the algorithms that integrate the floor plan information (e.g., defining which paths may be navigated by people, for example).
Other organizations are deploying infrastructure in public spaces (e.g., Nokia - Bluetooth-based). This solution assumes you control the infrastructure (and assumes the latest Bluetooth technology).
I work for TRX Systems and we are complementing these existing technologies with sensor and map fusion technology. In this approach, we fuse information from a multitude of sensors - including signals of opportunity (GPS, WiFi, cell triangulation, Bluetooth), embedded sensors (inertial, altimeter, ranging, compass), and known and inferred map information, to deliver an accurate location indoors.
Carol
The only way to accurately estimate your indoor position is by mapping the signal of known radio hotspots (i.e. wi-fi). That's why the indoor navigation feature has been implemented just for a few locations.