I'd like to know if iBeacons require a calibration phase (i.e, like Wi-Fi fingerprinting).
When trying to measure location based on Wi-Fi signal strength there's a need to do an arbitrary prior scan at the location you want to map.
I'd like to know if Iphone/Android already gets a fair coordinate based on ibeacons signal without a map phase.
If you want accurate distance estimates, then yes, it requires calibration.
However, it is not as temperamental as the wifi calibration. And often you can use the default calibration that comes with the particular iBeacon hardware.
For example my company, Radius Networks, makes a number of iBeacon hardware solutions and those are calibrated here in our lab. While environmental changes will effect that setting it often doesn't change things too drastically. For the most part the factory setting will be just fine for many use cases.
Obviously this is not the case if there is some drastic interference, such as installing the iBeacon behind a metal wall, or in a room that will be very crowded (people are notorious for absorbing RF). In those cases it would be best to recalibrate the beacon.
One difference to note about beacon calibration vs. something like wifi calibration, is that the beacon is configured to broadcast a calibration value. That value represents the expected RSSI that a phone will see at 1 meter away. That is then used to interpolate the distance estimate.
Related
I have followed the tutorial from RadiusNetwork to get the distance from a beacon using Android Beacon Library. I have read that it gives some fluctuations but I have three beacons in a room that is 7m x 7m one in each corner. With this, while sitting on a corner i have one in front of me (less that 0.2m) the other one at 10m (aprox, that's the diagonal of the room) and the other one at 7m. I tried to look for a solution here, but seems like everybody gets a better distance.
I did an app with that tutorial and when measuring the distance it tells me that the one that is 0,2 m away is 1.6m away, the one that is 10m says is at 70-90 m away and the other at 7m is at 40-60m.
I thought it was due to the power of the signal, which I tried to change but it wasn't the solution, since it was broadcasting the maximum power.
Anybody with the same problem that found a solution?
I made a measurements with the app with the Android Beacon Library. The phone was 1m away from the phone, and I got the following results:
I cannot specify the RSSI value at 1 meter, I can only pick one of the Transmission power (dBm and distance). The following is how the beacon's settings (in the owner app) looks like:
Beeks Toolkit App
I am using Beeks beacons from Bluvision.
According to the company:
"The txPower calibration for Eddystone broadcasts is done internally by our beacons and SDKs. When configuring Eddystone broadcasts, the picked calibration value will automatically match the advertisement's transmission power."
davidyoung is right. If you're using the Radbeacon dot, you can configure the advertised RSSI using the Radbeacon app (link is for the Android version).
With the app open, and the beacon on, hit scan. Once you see the beacon you want to calibrate, enable connections on the beacon (in the case of the Radbeacon dot, hold the button down for a couple seconds. The led will flash).
Tap on the beacon result in the app, and tap the menu icon in the top right. Select calibrate. Allow the calibrate function to run. If you are using Altbeacon or iBeacon frame types the phone should be 1 meter away. If you are using Eddystone the phone should be at 0 meters.
Note the RSSI value it returns, then tap back and enter that value in the Calibrated Power field. Save your changes, and you should be all set.
Make sure not to confuse the calibrate power value with the transmit power setting. Once you've set the calibrated power, if you change the transmit power you'll need to re-calibrate.
Also note that your distance values can vary quite a lot. Small rooms can complicate matters due to multi-pathing and other issues. You can experiment with various filtering methods, but the distances will rarely be spot-on.
I am trying to understand what exactly txPower is and how to use it, since I am planning to develop and Android app that uses Beacons.
I have seen 2 definitions online:
1.The transmitted power of the beacon.
2.The received power 1 meter away from the beacon.
How are these two definitions related?
Also, when transmitting a Beacon signal from a device using an app such as QuickBeacon, how do I determine what to set the power (txPower) to?
Most beacon formats contain a single byte in the transmission that indicates what the expected signal level should be when you are one meter away. This byte is sometimes called txPower (short for transmitted power) and sometimes measured power.
Do not confuse this with a second configuration setting on some beacon models that lets you vary how strongly the transmitter actually sends its broadcasts. This is typically called transmit power, which is why measured power is a less easily confused term.
The measured power field is used to make distance estimates. If the phone sees that its signal level is the same as the measured power field transmitted by the beacon, it knows it is exactly one meter away. If it has a stronger signal, it knows it is closer. If it has a weaker signal it knows it is further away. Using a formula, you can get a rough idea of the distance in meters.
Making this distance estimate accurate requires having the measured power field set properly to the expected signal level at one meter. It is often pre-configured into the beacon by the manufacturer, but it is typically adjustable. Why would you want to adjust it? If you place the beacon inside a cabinet, it might attenuate the signal. If you place the beacon against a metal wall, it might increase the signal due to reflections. For this reason, it is recommended that you calibrate a beacon by measuring and setting its measured power value after installation.
Calibration involves using a phone to measure the beacon signal level (using a measurement called the Received Signal Strength Indicator or RSSI, which is measured in dBm). To calibrate, you hold a phone with a typically performing bluetooth receiver (ideally an iPhone 6, but Nexus devices work well too) exactly one meter away from the beacon, and measure the average signal strength over 30 seconds. Many beacon configuration apps and tools like Locate for iOS and Android have calibration utilities.
Once you have the calibration value, you need to configure it inside your beacon per the manufacturer's instructions. This will give you more accurate distance estimates.
Check that issue maybe it helps:
Get Tx Power of BLE Beacon in Android also you could check out some devBytes from Google about BLE
https://www.youtube.com/watch?v=vUbFB1Qypg8
If you are using specific BLE beacons you need to referenced the datasheet and check how tx power is measured. As you already mentioned there is different definitions for it. During my dev I found that most suitable is that : txPower is measured in some distance from transmitter with way without obstacles. So if there is a wall for example txpower will be lower. Consider that.
txPower has defined the range of the Bluetooth signal to transmit the beacon.
I'm using my iPhone as an iBeacon device, and on the other side I have an Android 4.4.2 device scanning for the Bluetooth LE iBeacon signal from the iPhone. I searched for a good and easy way to calculate the distance between iBeacons and my Android phone, but I couldn't find anything that can help me with this.
Could you help me on this matter?
It's impossible to measure beacon distance accurately, I'm afraid, which is why Apple's own code just says "Immediate", "Near", "Far" and "Unknown". The best you can do is set up a reconstruction of the conditions you expect then do trial and error tests to map signal strength to probable distance. Trust me: I've spent a lot of time trying to do beacon distance measurement using a range of hardware.
Remember that the LE in Bluetooth LE means "Low Energy" – this stuff really is designed to use as little power as possible. That means the signal from iBeacons gets interrupted by people, walls and other objects. So, if I'm holding a beacon in my hand and put my phone next to it, I'll get a strong signal. If I move the beacon behind my back, the signal strength will collapse. If I just turn around, that has the same effect (for the same reason).
If you want to go down the "best you can do" approach, you effectively have to recreate at least partially the environment where your app will be used. So, if your app will be used in an office, find an office and place some beacons around there. Same for being in a shop.
Then get your app out and measure beacon strength at various distances to the beacon, potentially with obstacles in the way. With some averaging, you end up with something like "at 1 metre my signal strength was X, at 5 metres it was Y, at 10 metres it was Z", etc, and you then feed that into your distance calculation. It is, effectively, an educated guess.
If you find any library that claims to do beacon distancing for you, it just means they've taken their own educated guess based on their own signal strength testing.
One tip: if you're able to, stick your beacons to the ceiling. This minimises the chance of obstacles (read: people) getting between your beacon and your app.
We built a distance estimation formula into the Android Beacon Library of the form: d=A*(r/t)^B+C, where d is the distance in meters, r is the RSSI measured by the device and t is the reference RSSI at 1 meter. A, B, and C are constants. You can read more about it here. To use it with the library, you range for a beacon and then simply call:
beacon.getDistance();
This returns a distance estimate in meters. The library code is open source, so if you don't want to use the library you can copy the formula and use it directly.
As #TwoStraws notes, distance estimates are pretty rough guesses of how far a beacon is away, and the results you get vary with lots of factors:
The gain of the antenna on the receiving device. (Every Android device model is slightly different)
The noise on the A/D converter inside the phone that measures bluetooth signal strength.
The radio noise in the room.
Any obstructions between the transmitter and receiver.
Any surfaces (especially metal) that reflect radio signals.
Just be sure you set your expectations properly. Distance estimates are good for deciding if a beacon is close or far, or whether one beacon is closer than another. But they are less useful for measuring absolute distance.
Well for triangulation you need to have the direction from which your device is receiving the signal.We can calculate Angle of Arrival for that but calculating that angle requires an array of receivers. Is a cell phone capable of calculating Angle of Arrival? I am asking this because I have came across the terms like wifi/BLE triangulation, calculating position by triangulation etc but they're actually referring to Trilateration in most of the cases. I know how trilateration works for a mobile and all the details but I don't think Triangulation is possible. And if it is possible, how is it possible and which one (triangulation or trilateration) is expected to give better result if you use ibeacons to approximate positions?
Lot of people are misleading terms as you pointed out. Triangulation is not possible with standard ble beacons or WiFi (I mean without modify the standard ble 4.0 or 4.1 and WiFi) right now because the standard doesn't report useful information like the phase (if you have phase and an array of directional antennas that are powered on one per time at a predetermined frequency you can use algorithms like MUSIC and deal with angles) but we only have Rssi and TX power at one meter(if it's an iBeacon) with those information we can estimate the distance that is very imprecise and fluctuate rapidly over time because of multipath and diffraction.
In Nextome we have invented an algorithm to mitigate multipath fading that causes signal to bounce and achieve high accuracy Indoor Positioning of about 1 meter without fingerprinting.
No one has tested triangulation with standard iBeacons right now but trilateration. I would start looking at least square approximation to solve the trilateration problems, but don't expect big results without filtering out the noise.
Mobile mast triangulation usually uses the power level to estimate how far a phone is from a particular cell tower. At any given time a phone will generally be in touch with several towers, even though it is only using one at a time for calls etc.
If you have an estimate of the distance from two or more towers you can imagine drawing a circle around each tower with the radius equal to this distance.
Where the circles intersect is the 'likely' position(s) of the mobile device.
WiFi estimation works on roughly the same principles but is much more accurate as there are so many more WiFi networks.
The big data aggregators (Goggle, Apple etc and their partners) receive data from millions of phones which allows them accurately locate where a particular WiFi network is located. When you then ask your phone to check you position they are able to see what WiFi networks you are close to and vey accurately narrow down your position, especially in a built up area with many WiFi networks.
Most phone positioning systems will use a mix of technologies, GPS, cell strangulation, WiFi to help narrow down your location.
Of course if you are on top of a mountain or in desert the options are a bit more limited, and GPS becomes more important...
In my project, I want to detect if a user is moving or not by using either wifi rssi or accelerometer sensor.
What I should do to achieve that?
It actually all depends on what kind of movement you want to detect.
WiFi RSSIs : From a starting position and scan results (initial RSSIs for newly discovered access points), you can check through time their evolution in term of signal quality. A short displacement of the user will not be easy to find as RSSI values are tweaked by a large amount of parameters (orientation, obstacles, setup of the room, atmospheric conditions, people around). Thus you would need averaged values (scans must then be performed quickly to have enough data) and leaving an access point perimeter would make you lose the information.
Accelerometer : Depends on what quality of sensor you are using. If you're using embedded sensors within smartphones, it will be tough. Their accuracy is bad, and as you'll need to integrate its values (m/s² to get m/s) the error will grow subsequently. Plus it might be hard to discern real user movement from the device's tilt if you're using a mobile phone or tablet.
Without really knowing the details of your projet, I believe that RSSIs should be easier to use if you actually need to detect not so tiny motion. If you want something more precise, you'll need some way bigger research work.
See Android accelerometer accuracy (Inertial navigation) for RSSI-based indoor localization.