After doing some asking around and reading, it sounds like you're lucky to get even within 10 meters of accuracy with a GPS on a mobile device (specifically Android).
I've seen a video that shows a home-made device reading out to several decimals. Is this only because of the data format from the chip? (aka, not really precise either?)
Is there any real working way that I can use an Android device to track real static positions within rooms in a building?
Ideally, I'd be able to mark a point in a room and come back to it later with virtually no drift.
The LocationProvider is different from each Android Device you are using. The SDK does not handle the calculation of your exact location but the phone does. But each device can have one or mare LocationProvider, thats why you need to set some Criterias when your picking a LocationProvider.
To get your exact position on the earth the GPS needs 3 points from 3 different satellites. Thats why the GPS works best in the open space. Regarding making a precise calculation on a static persion inside a building, this conflict with the whole scenario of the GPS-System. I'm not saying it's impossible to get a location inside a building but as with any other signals, obstacles that blocks the signal makes is weaker.
If you are inside a barn with thin walls this might work, but inside a 10 storage building your scenario seems quite impossible.
You can though force your phone to get the best LocationProvider and hopefully that will give you the most precise location. And yes, you can get inside 1-2m in precision outside.
I hope this helps a little. Enjoy your project.
Related
I am working on the GPS part of a project and I would like to get something past the community. I have searched around for all the typical GPS "jumping and drifting" and I have worked on improving what I get but last week I got some really weird data that I cannot put my finger on.
The application basically has a foreground service that tracks the location and then uploads that data on a timer. Of course we have all the proper permissions needed and there is also a filter that weeds out data with really bad accuracy and "detects" stops. All was working well until what you can see here happened.
These are some of the data points I got. A "beautiful" pattern drawing. The same happens to another location too but not to this extend. I checked the data to find out why my filter didn't even try to make things better and I found out that it would be unable to. All the points have proper speed, heading, and accuracy and for all intents and purposes I could say that the person actually did the whole thing. The problem is that it didn't happen. The phone, (Samsung J5) might not be the best there is out there, was in a room the whole time. From my understanding of the Fused Location Provider there is no speed reported if there is no GPS involved in the process. And lets assume that where the phone was sitting it could actually get a GPS signal. I can see it jumping around but going for a walk around the neighborhood?
I know and understand that the location in Android (and any other platform) can be a very complicated matter comprised of many different variables that mainly start from the hardware providing these variables, but how can we explain this sudden influx of crazy, even though seemingly proper, data? Can we consider that keeping the location service up and running for a long time actually bogged or "tired" the system? How can the same device that has given OK data to this point suddenly provide this dataset?
To add to the issue. In the data there were also one or two long delays of around 2 minutes (intervals set to 15 and 10 (for fastest) seconds). I am 100% sure that the service did not restart or anything of the kind because I am logging for that.
Any kind of insight would be greatly appreciated and if there is any way/method/algorithm you could recommend looking into to "fix" this kind of behavior would be great. Thank you in advance and sorry for the long question. I needed to provide a proper background.
EDIT: This is not really the answer to my question, why such a behavior suddenly appears, so I am adding it here as a way to try and mitigate the problem, at least a bit. I decided to use the Google's ActivityRecognitionAPI (comes bundled in the location API so no need to have more dependencies) and merged its output with my existing filter to hopefully "fix" the "false" location data.
If someone could still, though, give me a good answer (help me understand) on whether there are factors like long running times, or other hardware (or software) factors (excluding the typical knowledge that GPS chips on phones are bad) that can cause weird and unexpected behaviors like the mentioned one would be rather appreciated.
(We can of course always say - "It is the phones fault" - and be done ;) )
The GPS has errors, so even if you stand still at the same point you will get different readings. There's a couple of things you can do:
Use the accuracy value of the GPS - if the distance between the new reading and the previous one is lower than the accuracy - ignore it.
Use the device's accelerometer in order to determine if it's moving or not.
I'm trying to find a good way to track location of people in a building. I would ultimately like to be able to create a graphic on demand showing where employees are in a building - which floor (elevation), and where on the floor they are located (lat/lon). I have read that elevation is relative to the WGS84 ellipsoid, not sea level necessarily, which is fine. I can define a baseline of where the first floor is, for example, and then calculate the difference of a person's current location from there. If I understand correctly, the general precision lat/lon for a GPS is as fine as 1m, which should be sufficient for me.
Part of my problem is finding a device to use for employees to carry around. The other is finding a device with a supported API (read: "free API") or other programming options. I would like this to be manufacturer-independent.
I would love to do cross-platform development - iOS, Android, PC, web, etc.
Does anyone have experience with something like this, and what recommendations can you offer on where to start? I know this is a little open ended but I'm not sure where to start.
Thanks.
This all does not work (tracking within a building).
GPS Signal is very poor or non existent within a building.
(Next time search here on Stackoverflow. It has been asked some times.)
The only robust and working solution, are BlueTooth beacons.
Such small hardware pieces are mounted within the building.
Such beacons (search for iBeacon) just send out an id.
The phone receives the id, and the approximate distance to it.
You have to administrate and know which id is at which level of the building.
Even when having good reception the GPS signal is not precise enough to determine the floor a person is location.
Some phones have a barometer, like the ipHone, this can track relative heigh changes, and may be used to determine level within a building. (Once calibrated before entering the buulding)
how can I correctly identify if the user is driving or not ? I am trying to make an app where I can find my parked car's location.
The simplest way was to ask user to press a button after parking the car so that my app can remember its location.
But I want my app to be automatic. It should correctly recognize if the user is in vehicle or not without interacting with the user.
I tried out Activity Recognition as well but it does not give me exact/correct result. Even when I am walking it says driving and vice versa. I cannot trust it.
There are several apps in the play store which achieve this. I want to learn this as well.
Would some one take some time and help me out on this. It will be of greate help. Thanks a lot in advance :)
I've never done this before, but here are some things I'd try:
location - mainly, how fast their location is changing. probably not great for slow traffic, but if they are moving 60mph, there's no way they are walking. You could also combine this with map data about known roads, or maybe even use locations of well-known airports to know that someone is more likely flying than driving
use the device's accelerometers to compute it's speed (in conjunction with location info to correct for accumulated error).
have the user connect their device to the car with bluetooth - and then when the connection drops, you know they aren't in their car. Or better yet, figure out if you can just detect they are in the car from strength of the bluetooth signal. Though I'm not sure that's possible.
(maybe) ask your users to use a simple RFID chip in their car, and then use that as an indicator of whether or not the phone is in the car. Of course this has implications on the user experience.
in a different vein, maybe some sensor on the device could pick up vibrations? Just thinking that car rides aren't perfectly smooth, so any vibration sensing + some signal processing (DFT the data, then look for certain low frequencies that correspond to driving - probably low frequency and below audible).
The best? Probably a combination of all of the above. The more signals you can gather, the better. Perhaps you could even collect a bunch of data, and try to use it to train a classifier? Then again, if any one of these signals turns out to be strong enough, you might not need the others. Be sure to test a variety of scenarios, e.g. phone in the cup holder v. in your pocket, city driving & slow traffic v. highway driving / empty streets, etc.
I'd be curious to know if any of these ideas pan out.
Also fwiw, Determining if user is driving using gps appears relevant - though it's a simple speed-based check - if you cruise around a parking lot at 8mph looking for a spot, you'll completely fail at catching where the car is parked if your threshold is 10mph.
If the speed drops from above 40km/h to under 7km/h, and stays low for more than 5 minutes.
I'm creating an application that gets the users speed whilst driving using the Android Location class. The problem that I am facing is that every post on a forum or article explains problems with the getSpeed() method. Having just gone into my car to test several times, it returns 0. I am not sure why, just wondering if anyone has been able to find out why and how to get the actual speed?
Thanks in advance
getSpeed works just fine, provided you have a capable GPS hardware in your device and you have enough satellites in sight. I am using it for a flight logging application.
One issue with getSpeed is, that the emulator will always return 0; even if it is fed with NMEA data which has speed info. So testing requires the real devices.
If the GPS receiver is inside the car, one issue might be, that it cannot acquire enough satellites in time for your test. Try leaving the device near the windshield (if it is not covered with a reflective surface based on something metallic!) and give it time to get a fix. Consider using a GpsStatusListener to get a count of visible satellites.
The trick mentioned above to compute speed from distances of samples requires filtering of the data. The more samples you use the more noise you get (which needs filtering, search for it here, there are several articles on stackoverflow on this topic). The less samples you use the greater is the error when not moving on a straight line.
I'm new in Android and I would like to ask you is there any possible way to know if the Android phone moved about 5 meters from its current location ?
One idea is to use the accelerometer to detect when the phone is moving. Naturally, you can't estimate the distance moved very accurately, but it might work for your application. If the accelerometer says the phone is moving for more than 5 seconds or so (maybe you can detect a pattern of movement?) you might infer that the phone moved significantly from its original position.
Of course, the user can trick your app by shaking the phone...
A good resource concerning GPS can be found at the official site: http://www.gps.gov/systems/gps/performance/accuracy/
The short answer, however, is that the GPS accuracy of a specific phone at a given moment is dependent upon several variables. Those that are most pertinent to your question would be the actual hardware of the device, and the environmental conditions at present. Typically, a phone under good conditions can expect at best 10m of lateral accuracy. Taking into account poor conditions, local interference, limited satellite connectivity, etc, can push the error of a reading much higher. Unfortunately, consistently and precisely measuring a movement of 5m is unlikely.