Presentation:  Factors  effecting  positional  accuracy  of  iBeacons  

Chris  Thomson    Codepilots.com  

 31st  March  2014  

Commentary  on  the  slides:  1. 2. 3. This presentation concerns indoor localisation and positioning – the target is

to locate a person using a mobile device within a building. 4. The technology under consideration to do this is the iBeacon. Battery powered

is a very important issue, as it means they can be placed anywhere without the expense of routing power or network connections. So Ideal for quick deployments, and use in locations inside and outside where we don’t want to make changes – e.g. heritage locations. Battery’s last up to 2 years, at which point the unit is replaced.

5. In this research I made use of Beacons by Estimote (estimote.com), who also produced these graphs. These graphs show the measured power at distances from a typical iBeacon, we can use power information to estimate the distance of an receiver. Notice how the measured power does not decrease uniformly as we move away from the receiver, this is the biggest limiting factor in using this technology for accurate positioning.

6. If we have at least 3 beacons we can, using geometry/trigonometry work out the unknown location of the receiver, based on the known location of the transmitters and their distance from the receiver. Unfortunately finding the distance is quite difficult!

7. You can express this problem mathematically in a number of ways, this is one of them. The d, is the distance we want to know, the d0 a measure of distance for a known power output, the n is the way the signal power degrades over distance, and squiggle the environmental effect, the environmental effect is actually quite large!

8. A fair bit of research in measuring distance in this way has been done, lots of it is to do with wireless sensor networks, three approaches seem common, these are as listed on the slide. But for iBeacons, we are limited to only the top approach as real time measurements are two power hungry, and we don’t have access to the raw radio in iOS to do anything clever.

9. The main issues and limitations are as listed on the slide, the questions we can actually investigate are underlined. These are: How the signal is received and transmitted; Now noisy is the environment, and its effect; and Humans and other objects.

10. 11. It is worth mentioning here, that at this stage, all of the above is basically

standard practice available on the market. 12. If you want to reproduce the results, this information will probably be

important. As radio reflection may also be an issue, the room has a concrete floor, breeze block walls, and a plasterboard ceiling. The presences of 2 doors and a window may also set up interesting interference patterns.

13. I need to do a statistical analysis of this variation, but have not yet done so. However the variance does not seem great.

14. 15. These are the main high level, and radio obstructions which could cause a

problem. 16. The way the iPad is held is very important, the receiver seems most sensitive

to being held at the front bottom of the iPad near the home button. So the orientation of the iPad is rather important. In this experiment the iPad was held horizontally in front of the person holding it, with hands underneath the device.

17. In this experiment the iPad was held, operator standing looking towards the top of each graph, and the iPad rotated in front of the operator.

18. In this case the ipad was placed onto a stool. Something interesting is going on with the bottom right beacon, why is it so far out?

19. Clearly I need to refine the experimental protocol here, as the changes in the top right beacon’s distance are rather interesting.

20. 21. 22.

Comments,  advice  and  suggestions  are  invited,  email  me:  chris  (at)  codepilots.com  or  twitter  @codepilots.