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I am facing a problem I don't how to do that. Suppose I have 20 users in the city so I want to find the nearest user to me with in a range of 5 kilometres. Actually, I am building an app using firebase where I can find the nearest blood donor. How can I find it? Need suggestion. if I add 5 kilometres to latitude and longitude from all side. Is it possible and Am I on the right track? if yes so how would I add 5 kilometres to latitude and longitude?
You can use the geodesy library to calculate distances between locations.
https://pub.dev/packages/geodesy
num distance = geodesy.distanceBetweenTwoGeoPoints(l1, l2);
Note -- since the earth's surface is not flat (although some still believe that) you cannot use simple euclidian geometry to calculate the distance.
I am using the FusedLocationProviderClient to get locationUpdates after setting up LocationRequest properties.
To calculate 'distance traveled' I thought I would do the following:
Location lastLocation; // initialized to start location with getLocation() - code not shown.
LocationCallback locationCallback;
Double DistanceTraveled = 0.0;
locationCallback = new LocationCallback() {
#Override
public void onLocationResult(LocationResult locationResult) {
if (locationResult != null) {
// Get last location in result if more than one are returned.
Location thisLocation = locationResult.getLastLocation();
// Sum up DistanceTraveled
DistanceTraveled = DistanceTraveled + lastLocation.distanceTo(thisLocation);
// Save thisLocation for next time onLocationResult() is called
lastLocation.set(thisLocation);
}
}
}
Well, this doesn't work very well. On every callback, the exact location changes by 0 meters to 10 meters randomly just due to the accuracy of the result. So, if I am standing perfectly still for 10 minutes with a 5 second update using this algorithm, it will sum up several meters that I have traveled, when I haven't moved at all!
What should I be doing to get an accurate accounting of my distance traveled? What options exist?
Ok - it has been 12 days since I posted my question here. Lots of reading, testing, coding, more testing, more reading. I now have a responsibility to contribute to the site that gives so much to me. So here goes.
First, the following post has many tidbits of info and links to assist. calculate actual distance travelled by mobile
Now, I am specifically concerned about tracking the distance traveled by someone walking; to be exact while bird watching. My app is for bird watchers. So, I am interested in logging the birds seen, along with where, and tracking the overall distance walked. It turns out these are two different issues. Getting the current coords for a sighting of a bird is easy stuff; just get the location. The accuracy is that which is reported.
Now, to the problem of this post. Calculating distance walked. That is a different problem altogether. And this is what I was looking for when posting the question. How do people get an accurate accounting of distance traveled, when walking? Because just registering for location updates and then summing up the Location1.distanceTo(Location2) usually gives one a wildly inflated total distance. Why? I didn't understand the problem. Now I do. And if I had this understanding, then the path to the solution would have been clearer.
Let me give an example. Let's say I walk for 10 seconds. At second 0 (t0) is where I start. And let's say I move 1 meter by t1. I stand at this position until t5, and then walk for another 5 seconds until t10. A combination of walking/standing help to illustrate the problem.
Each GPS location update contains a coordinate (lat/lng), or a point, along with an accuracy rating in meters. Along with other data, but the only other one I care about is time in milliseconds. In this example, always 1000 ms more than the last update.
Think of this GPS update as a point at the epicenter of a circle with radius accuracy-in-meters as returned. Your actual location could be anywhere within that circle or on the circle's edge, in theory. Not sure how accurate that accuracy-in-meters is (seems like it should have it's own accuracy rating), but let's assume it is accurate, and your true location is no more than accuracy-in-meters away from the point reported. In fact, let's assume it is always that distance from your true location for purposes of illustration. Let's also assume that this accuracy-in-meters is 20m in this example for each point returned.
So, at t0, my true location could be 20m ahead of where it reported. I walk 1 meter forward and location update at t1 reports I am 20m ahead of where I truly am. So, computing t0.distanceTo(t1) reports that I have moved 40m when I have truly only moved 1m. Starting to see the picture? Read on...
Now, I stand here until t5. And I get 4 more location updates, which for example purposes, are 20m ahead, 20 meters behind, 20 meters to my left and 20 meters to my right. (This is an extreme example, but uses easy numbers for illustration). So, in addition to my supposed 40m of travel after 1 second, it now thinks I have moved approximately 20x4 or 80m more, for a total of 120m. And I have only moved 1m in reality! Continue to walk 5 more meters to t10 and your distance could again be 5x20 or 100m more for a total of 220m, when you have only walked 6m in 10 seconds. That is why simply summing up distance traveled will never be accurate as long as there is any error in the accuracy.
That's the problem. And until one understands that, you are befuddled by how this crappy Galaxy S9 is doing this to you.
What about averaging points? "midpoint(t0,t1).distanceTo(midpoint(t2,t3)" and so on? This will always produce less-than true distance traveled. Depending on movement, sometimes by a lot.
There are lots of methods (see link above) to try in order to reduce the error in Distance Traveled calculations. I have found that my method below produces more accurate results when walking, than Google's MyTracks app. I have repeatedly tested at 200m, 500m and 1000m distances. And this consistently produces good results usually with < 10% error. Half the time, Google's MyTracks says I have walked 500m+ on the 200m test.
onLocationResult(LocationResult locationResult) {
lastLocationReceived.set(locationResult.getLastLocation());
// Throw away updates that don't meet a certain accuracy. e.g. 30m
if (lastLocationReceived.hasAccuracy() && locatLocationReceived.getAccuracy() <= MIN_ACC_METERS_FOR_DISTANCE_TRAVELED) {
// Don't use it if the current accuracy X 1.5 > distance traveled since last valid location
if ((lastLocationReceived.getAccuracy() * 1.5) < loastLocationReceived.distanceTo(lastLocationUsedForDistanceTraveled) {
// Calculate speed of travel to last valid location; avg walking speed is 1.4m/s; I used 2.0m/s as a high end value.
// Throw away values that are too high because it would have required that you run to get there.
// Sometimes the location is somewhere you could not have gotten to given the time.
long timeDelta = lastLocationReceived.getTime() - lastLocationUsedForDistanceTraveled.getTime();
if ((lastLocationReceived.distanceTo(lastLocationUsedForDistanceTraveled) / timeDelta) > MAX_WALKING_SPEED) {
// NOW we have a value we can use to minimize error
distanceTraveled += lastLocationReceived.distanceTo(lastLocationUsedForDistanceTraveled);
// Update last valid location
lastLocationUsedForDistanceTraveled.set(lastLocationReceived);
}
}
}
};
Notes:
onPause() for activity stop locationUpdates.
onResume() restart locationUpdates.
Setting/using locationRequest.setSmallestDisplacement() produced strange results for me. I ended up never setting this value in my locationRequest. How does it know you have moved 5m when the hAccuracy is 20m?
I don't find a need to keep getting location updates with the app paused (in one's pocket). As soon as you pull you phone out of your pocket to use it to record a sighting, it reacquires fairly quickly. More testing may prove that this is error prone. But for now, it seems to be ok.
I have tested more methodologies than I can remember with wildly differing results. This simple method works best, for WALKING, in my tests. I am sure there is more that I could do that might further refine the error by a few percentage points. If anyone has concrete examples for how to achieve tighter accuracy, please post comments.
In my testing, I created an activity that allowed me to adjust locationRequest() settings in real time (stop and restart locationUpdates required on changes); as well as modifying min accuracy levels and accuracy multiplier (used above in code as 1.5). So I was able to test and play with different parameter settings to see what produced the best results.
I hope this helps others get started down this path for the first time. Would love to hear comments, corrections, improvements if anyone has some.
I working on an app that I need to calculate distance travelled from point A to point B (by car).
I asked Elm Electronics (chipset manufacturer) and they said there is no standard OBD-II PID to return mileage from odometer, although car manufacturers might provide a PID. Since this way is not standard then I found another way.
PID 0131 (Distance traveled since codes cleared), is returning something that I think might be helpful. IF i'm able to clear it at point A and read its value at point B then I'm done :)
I thought a lot to guess what does "codes cleared" mean but I couldn't realize what does it mean? and my another important question, how to clear code or reset this PID?
Any suggestion would be appreciated. Thanks.
Update
I just tested on two Cars.
On Benz car no OBD-II command works. I couldn't get any data :(
I got correct reply on Persona car (Local Malaysia) but 0x0131 PID was always returned 7F01 which is 16608KM even after passing few Kms. I tried to reset it by sending 04 command (as Eric suggested on his answer), However, nothing got clear :) and I still got 7F01 as response.
My Library can be used for anyone who is looking for OBD-II lib from here.
So, What I plan to do is, since I'm able to get speed (v) then I'm able to calculate distance based on d = v * t formula.
Elm Electronics are right. The resetting trouble codes solution is a possible, but maybe unwanted workaround though.
Mode 04 is for resetting the codes. Sending 04 will reset the MIL (Malfunction Indicator Light) and reset the codes you want to reset.
In the comments, Chris suggested to use the value, and than keep track of this value yourself. That way you don't need to misuse the Mode 04.
Th 0131 value overflows at 65535 km. But when you bring you car in for maintenance, they could reset this value, depending on who is maintaining your car ofcourse.
Source: Mode 04 - Wikipedia
There are two PIds: 0x0121 Distance travelled with malfunction indicator lamp (MIL) on which keeps the distance with MIL on and 0x0131 Distance travelled since codes cleared which keeps the distance after clearing the MIL by using mode 0x04. By saying code, it meant the Diagnostics Trouble Code (DTC). When one of them keeps counting the distance the other one is fixed and activation is done for them only based on MIL on or off.
For having the milage, afaik, you need to have current mileage from the odometer as the reference, in addition to those two PIDs. For example, if the current mileage on the odometer* is X and the first time readings for those two PIDs are Y and Z respectively, and x and y are real-time readings from those two PIDs, these two formulas can give you the mileage and trip distance:
Real-Time mileage** = X + (y - Y) + (z - Z)
Trip distance (MIL Off) = x(end) - x(start)
Trip distance (MIL On) = y(end) - y(start)
*The odometer is supposed to be available by PID 0x01A6 Odometer, but in almost all the vehicles, it's not supported.
**The overflow in readings from those two PIDs should be considered as well.
I think You can use the PID 0x011F (Run time since engine start) and PID 0x010D (Vehicle speed). If you save these values in an sd card then you can multiply these two values.
I need to get an accurate measurement of altitude using GPS only.
I tried Location.getAltitude(), but that is terribly inaccurate.
Any advice?
There are two issues with using altitude of a smartphone / tablet GPS:
The altitude is the altitude above the WGS84 reference ellipsoid. It is not the altitude above ground level or sea level. Here is more detail on that: http://www.gpspassion.com/forumsen/topic.asp?TOPIC_ID=10915. This error can be corrected; here is a description how to do that by hand: http://www.unavco.org/edu_outreach/tutorial/geoidcorr.html. The web article links to a calculator to get the Geoid height for correction; I do not know if there is also a web service available for this computation.
The GPS altitude is terribly inaccurate for relatively cheap GPS receivers. Here is an article on that: http://gpsinformation.net/main/altitude.htm. One method to cope with this kind of inaccuracy is to filter the altitude data. I used a circular array data structure to remember the last few (I used 4) altitude readings and compute the average. This sufficed to get a relatively accurate reading of vertical speed for my application.
Another way would be parsing NMEA strings. The $GPGGA sentence already contains the corrected altitude data above sea level.
So, simply create a listener to NMEA-strings for your LocationManager and parse the messages:
private GpsStatus.NmeaListener mNmeaListener = new GpsStatus.NmeaListener() {
#Override
public void onNmeaReceived(long timestamp, String nmea) {
parseNmeaString(nmea);
}
};
public void registerLocationManager(Context context) {
mLocationManager = (LocationManager) mContext.getSystemService(LOCATION_SERVICE);
mLocationManager.addNmeaListener(mNmeaListener);
}
private void parseNmeaString(String line) {
if (line.startsWith("$")) {
String[] tokens = line.split(",");
String type = tokens[0];
// Parse altitude above sea level, Detailed description of NMEA string here http://aprs.gids.nl/nmea/#gga
if (type.startsWith("$GPGGA")) {
if (!tokens[9].isEmpty()) {
mLastMslAltitude = Double.parseDouble(tokens[9]);
}
}
}
}
You can either replace the altitude of the last Location object received through a location listener, or parse the whole new location through NMEA.
Another approach is to measure the altitude from the barometer.
By using the pressure you can calculate the user's altitude. I'm uncertain of the precision level of this and whether it is more accurate than the other answer's approach.
By using the hypsometric formula you can calculate the altitude:
Variable definition:
P0: Sea-level pressure
P: Atmospheric pressure
T: Temperature
You can get the pressure in android from the environment sensors
SensorManager.getAltitude(SensorManager.PRESSURE_STANDARD_ATMOSPHERE,pressure)
If the device has a barometer, then use can that to improve the relative accuracy. I don't mean to use the barometer to compute the height in relation to the sea level, as can be found in several formulas, as this is highly dependent of the weather conditions.
What you want to do is to get the GPS-altitude when you know that the device has a good fix, with high accuracy values. At that point you fetch the barometric pressure and set that pressure as a reference.
When the pressure increases around 12 hPa, you will know that your altitude decreased by around 100 m ( https://en.wikipedia.org/wiki/Atmospheric_pressure "At low altitudes above sea level, the pressure decreases by about 1.2 kPa (12 hPa) for every 100 metres." ).
Don't take that value as an exact, but variations in the altitude determined by GPS vary a lot due to trees covering the line of sight and other factors, while the barometer will remain very precise under those conditions.
The following graph is a bike ride of around one hour and 20 minutes in duration. Starting point and end point are the same at around 477 m above sea level, determined via GPS. The measured pressure is 1015.223 hPA.
The lowest point is 377 m, with a measured pressure of 1025.119 hPa. So in that case, 100 m make a difference of 10 hPa.
The highest point is 550 m, with a measured pressure of 1007.765 hPa.
Ending point is the same height, and the exact same pressure as the starting conditions (the pressure could have varied due to the weather conditions, but it didn't). The temperature dropped around 1°C, so it was all pretty constant.
The black line containing the many variations is the altitude measured via GPS, the mirrored, but clean line, is the barometric pressure. It has very little variation in it simply because the pressure doesn't vary as wild as the GPS-quality. It is a very smooth, very precise curve. This is not due to lag. This is measured with a Bosch BME280 sensor, which is capable of detecting the closing of a door, change of floor detection, elevator direction, drones, with a noise of 0.2 Pa which equals 1.7 cm and an error of 1m at 400m of height change. These kind of sensors are integrated in some Smartphones. For example, the Pixel 3 contains a Bosch BMP380.
If you mirror the pressure graph, as is shown with the dotted black line, you will see that it very closely matches the GPS altitude. It is much more precise than GPS, but the only problem is that you can't take it as an absolute value.
The samples of GPS and pressure were both taken in 1 second intervals, so there is no curve smoothing from the d3 library causing some false impressions.
So maybe readjusting the pressure around every 10-30 minutes while you have a GPS good fix will give you a good base to perform your altitude measurements by pressure in between.
There are other ways to get the altitude than by GPS. You can use the barometer but as there isn't that many devices with a barometric sensors yet (only the new ones). I will recommend to use a web service to acquire the desired data.
Here is a question which should help you through: Get altitude by longitude and latitude in Android
For newcomers I made a library that wrap LocationManager into rxjava observables and add some observable helpers to get sea level altitutde from Nmea/GPGGA mre info here
There are libraries, such as the open-source CS-Map which provide an API that do these lookups in large tables. You specify the coordinates, and it will tell you the height offset that needs to be applied to the ellipsoidal height at that location to get the "real-world" orthometric height.
Note: Having used CS-Map before, it isn't exactly straight-forward 5-minute job to plug it in. Warning you in advance that it is more complicated than calling a single API with a set of lat-long coordinates and getting back a height. I no longer work at the company where we were doing this kind of work, so unfortunately cannot look up the code to say exactly which API to call.
Doing a google search for it right now (2019), it seems CS-Map has been merged into MetaCRS in OSGeo, the "Open Source Geospatial Foundation" project. That same search led me to this old CS-Map wiki as well as the PROJ GitHub page, where PROJ seems to be similar project to CS-Map.
I would recommend using NmeaListener, as sladstaetter
suggested in his answer. However, according to NMEA documentation, "$GPGGA" is not the only sentence you can get. You should look for any "GGA" sentence ($--GGA).
Regular expressions are great for that, e.g.:
#Override
public void onNmeaReceived(final long timestamp, final String nmea) {
final Pattern pattern = Pattern.compile("\\$..GGA,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,([+-]?\\d+(.\\d+)?),[^,]*,[^,]*,[^,]*,[^,]*,[^,]*$");
final Matcher matcher = pattern.matcher(nmea);
if (matcher.find()) {
final float altitude = Float.parseFloat(matcher.group(1));
// ...enjoy the altitude!
}
}
I need to get an accurate measurement of altitude using GPS only.
I tried Location.getAltitude(), but that is terribly inaccurate.
Any advice?
There are two issues with using altitude of a smartphone / tablet GPS:
The altitude is the altitude above the WGS84 reference ellipsoid. It is not the altitude above ground level or sea level. Here is more detail on that: http://www.gpspassion.com/forumsen/topic.asp?TOPIC_ID=10915. This error can be corrected; here is a description how to do that by hand: http://www.unavco.org/edu_outreach/tutorial/geoidcorr.html. The web article links to a calculator to get the Geoid height for correction; I do not know if there is also a web service available for this computation.
The GPS altitude is terribly inaccurate for relatively cheap GPS receivers. Here is an article on that: http://gpsinformation.net/main/altitude.htm. One method to cope with this kind of inaccuracy is to filter the altitude data. I used a circular array data structure to remember the last few (I used 4) altitude readings and compute the average. This sufficed to get a relatively accurate reading of vertical speed for my application.
Another way would be parsing NMEA strings. The $GPGGA sentence already contains the corrected altitude data above sea level.
So, simply create a listener to NMEA-strings for your LocationManager and parse the messages:
private GpsStatus.NmeaListener mNmeaListener = new GpsStatus.NmeaListener() {
#Override
public void onNmeaReceived(long timestamp, String nmea) {
parseNmeaString(nmea);
}
};
public void registerLocationManager(Context context) {
mLocationManager = (LocationManager) mContext.getSystemService(LOCATION_SERVICE);
mLocationManager.addNmeaListener(mNmeaListener);
}
private void parseNmeaString(String line) {
if (line.startsWith("$")) {
String[] tokens = line.split(",");
String type = tokens[0];
// Parse altitude above sea level, Detailed description of NMEA string here http://aprs.gids.nl/nmea/#gga
if (type.startsWith("$GPGGA")) {
if (!tokens[9].isEmpty()) {
mLastMslAltitude = Double.parseDouble(tokens[9]);
}
}
}
}
You can either replace the altitude of the last Location object received through a location listener, or parse the whole new location through NMEA.
Another approach is to measure the altitude from the barometer.
By using the pressure you can calculate the user's altitude. I'm uncertain of the precision level of this and whether it is more accurate than the other answer's approach.
By using the hypsometric formula you can calculate the altitude:
Variable definition:
P0: Sea-level pressure
P: Atmospheric pressure
T: Temperature
You can get the pressure in android from the environment sensors
SensorManager.getAltitude(SensorManager.PRESSURE_STANDARD_ATMOSPHERE,pressure)
If the device has a barometer, then use can that to improve the relative accuracy. I don't mean to use the barometer to compute the height in relation to the sea level, as can be found in several formulas, as this is highly dependent of the weather conditions.
What you want to do is to get the GPS-altitude when you know that the device has a good fix, with high accuracy values. At that point you fetch the barometric pressure and set that pressure as a reference.
When the pressure increases around 12 hPa, you will know that your altitude decreased by around 100 m ( https://en.wikipedia.org/wiki/Atmospheric_pressure "At low altitudes above sea level, the pressure decreases by about 1.2 kPa (12 hPa) for every 100 metres." ).
Don't take that value as an exact, but variations in the altitude determined by GPS vary a lot due to trees covering the line of sight and other factors, while the barometer will remain very precise under those conditions.
The following graph is a bike ride of around one hour and 20 minutes in duration. Starting point and end point are the same at around 477 m above sea level, determined via GPS. The measured pressure is 1015.223 hPA.
The lowest point is 377 m, with a measured pressure of 1025.119 hPa. So in that case, 100 m make a difference of 10 hPa.
The highest point is 550 m, with a measured pressure of 1007.765 hPa.
Ending point is the same height, and the exact same pressure as the starting conditions (the pressure could have varied due to the weather conditions, but it didn't). The temperature dropped around 1°C, so it was all pretty constant.
The black line containing the many variations is the altitude measured via GPS, the mirrored, but clean line, is the barometric pressure. It has very little variation in it simply because the pressure doesn't vary as wild as the GPS-quality. It is a very smooth, very precise curve. This is not due to lag. This is measured with a Bosch BME280 sensor, which is capable of detecting the closing of a door, change of floor detection, elevator direction, drones, with a noise of 0.2 Pa which equals 1.7 cm and an error of 1m at 400m of height change. These kind of sensors are integrated in some Smartphones. For example, the Pixel 3 contains a Bosch BMP380.
If you mirror the pressure graph, as is shown with the dotted black line, you will see that it very closely matches the GPS altitude. It is much more precise than GPS, but the only problem is that you can't take it as an absolute value.
The samples of GPS and pressure were both taken in 1 second intervals, so there is no curve smoothing from the d3 library causing some false impressions.
So maybe readjusting the pressure around every 10-30 minutes while you have a GPS good fix will give you a good base to perform your altitude measurements by pressure in between.
There are other ways to get the altitude than by GPS. You can use the barometer but as there isn't that many devices with a barometric sensors yet (only the new ones). I will recommend to use a web service to acquire the desired data.
Here is a question which should help you through: Get altitude by longitude and latitude in Android
For newcomers I made a library that wrap LocationManager into rxjava observables and add some observable helpers to get sea level altitutde from Nmea/GPGGA mre info here
There are libraries, such as the open-source CS-Map which provide an API that do these lookups in large tables. You specify the coordinates, and it will tell you the height offset that needs to be applied to the ellipsoidal height at that location to get the "real-world" orthometric height.
Note: Having used CS-Map before, it isn't exactly straight-forward 5-minute job to plug it in. Warning you in advance that it is more complicated than calling a single API with a set of lat-long coordinates and getting back a height. I no longer work at the company where we were doing this kind of work, so unfortunately cannot look up the code to say exactly which API to call.
Doing a google search for it right now (2019), it seems CS-Map has been merged into MetaCRS in OSGeo, the "Open Source Geospatial Foundation" project. That same search led me to this old CS-Map wiki as well as the PROJ GitHub page, where PROJ seems to be similar project to CS-Map.
I would recommend using NmeaListener, as sladstaetter
suggested in his answer. However, according to NMEA documentation, "$GPGGA" is not the only sentence you can get. You should look for any "GGA" sentence ($--GGA).
Regular expressions are great for that, e.g.:
#Override
public void onNmeaReceived(final long timestamp, final String nmea) {
final Pattern pattern = Pattern.compile("\\$..GGA,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,([+-]?\\d+(.\\d+)?),[^,]*,[^,]*,[^,]*,[^,]*,[^,]*$");
final Matcher matcher = pattern.matcher(nmea);
if (matcher.find()) {
final float altitude = Float.parseFloat(matcher.group(1));
// ...enjoy the altitude!
}
}