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A proof of concept for locating a device within a building using Wi-Fi signals.
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README.md

Field Map

A Wi-Fi based positioning tool

This program was created during the ABSA Aliens Internship program between the 29th of January and the 2nd of February 2018. It attempts to use fingerprints of Wi-Fi signals in a building to locate which room a user is in without needing access to a GPS system.

How it works

This proof of concept requires a premade map of the building. Each floor is split into rooms. A few dozen samples of the wifi signals in each room are taken and those signals are transformed into simple fingerprints, noting the mac address, maximum and minimum signal strength for each AP visible.

This data was uploaded to an online database.

When in operation, the navigation app uses simple linear interpolation and a few bias values to score each room fingerprint on how closely it matches the current readings. Whichever room scores highest according to the Classifier is considered to be the room the user is in. A simple map with collisions was used to allow the user to navigate the building.

Abilities and Limitations

The Wi-Fi positioning system excels at locating users in individual rooms and corridors, thanks to the unique signal profile numerous walls creates. In open spaces, larger areas are needed to see meaningful results and adjacent spaces sometimes become confused. More advanced classification functions or more granular fingerprints could improve these readings.

Contributors

@KaliumPuceon, @ForeverANoob and @nyashabryan were responsible for this project during the internship.

Tools

This was built in Android Studio, for Android KitKat and higher. The fingerprint data is stored in a free FireBase database. A small number of custom tools were used to get fingerprints and make them suitable for upload, which will be added to the repository soon.

License

This project is licensed under Apache 2.0, see the LICENSE file for the entire license.

Some notes on internal operation

This app is a slightly convoluted thing because the authors are all novices. In this regard, here's a primer on the internals.

On creation, the LoadUpActivity calls on a Firebase database and produces a Floor object, which is then passed on to the rest of the program. The Floor is loaded into a Classifier, which can be called on to find out which Room the user is in. The CustomView calls the Classifier every few seconds, and takes the Room object it produces. This Room object is used by the Map and Graph to find out where the user is in space. That information is used by the Map to draw the user in the layout of the office. The Graph plots a path from the user position to their target, and the Map draws this onto the layout of the office. There are several helper classes that assist this.

If you have questions about any single section, these people probably know them best:

  • Database: @NyashaBryan
  • Classifier: @KaliumPuceon
  • Drawing System: @ForeverANoob
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