RSSI-Based Position Estimation And Geo-Fencing Using Bluetooth

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The New Brunswick Community College – Centre for Applied Research in Mobile & Ubiquitous Computing

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The NBCC Mobile First Technology initiative (MFTi) collaborated with IGT (formerly GTECH) on an investigation of geo-fencing and position estimation algorithms that employ Bluetooth 4.0 beacons and received signal strength indication (RSSI).

Research topics

Bluetooth 4.0, geofencing, iBeacon, position estimation, RSSI


Geo-fencing is a form of identification used to determine whether a mobile device is inside (or outside) a specified area (aka, a geo-fence). Position estimation attempts to calculate the coordinates (location) of a mobile device of interest.

MFTi collaborated with IGT (formerly GTECH) on an investigation of geo-fencing and position estimation algorithms that employ Bluetooth 4.0 beacons and received signal strength indication (RSSI). This included a custom bounding-box algorithm designed and implemented by NBCC. MFTi produced two proprietary technical reports for IGT.

RSSI is an indirect measure of received power (RX) from a transmitter. In our case, the transmitters were Bluetooth 4.0 beacons, such as the Estimote. Several mathematical models exist for estimating distance to a transmitter based on RSSI. The experiments performed thus far use the following equation cited in a number of places, including [Dahlgren 2014]:

   RSSI = -(10 N log 10 d + A)

In this equation, A is the absolute energy in dBm at 1m from the beacon; N is a measure of the “influence of walls and other obstacles” [Dahlgren 2014, Kotanen 2003]; and d is distance. The distance equation used in the experiments reported below is, thus

   d = 10 ^ (A-RSSI / 10N)


Nbcc ca mobi diag-rssi-boundingbox-00.png

Figure 1. Estimating distances using RSSI for the bounding box algorithm.

Nbcc ca mobi diag-rssi-boundingbox-01.png

Figure 2. Radii about each beacon based on estimated distance.

Nbcc ca mobi diag-rssi-boundingbox-02.png

Figure 3. Finding the bounding box and estimated position.


References

  • Dahlgren, E. and Mahmood, H., “Evaluation of indoor positioning based on Bluetooth® Smart technology," 2014.
  • Kotanen, A., Hannikainen, M., Leppakoski, H., and Hamalainen, T. D. , “Experiments on local positioning with Bluetooth,” in Information Technology: Coding and Computing [Computers and Communications], 2003. Proceedings. ITCC 2003, 2003, pp. 297–303.

NBCC Team

  • Russell Allen, Coordinating Instructor of Information Technology, NBCC Moncton
  • David Morris, Instructor of Information Technology, NBCC Saint John
  • Matthew McArthur, Research Assistant (NBIF)
  • Wagner Faria Sodré Junior, Mitacs Globallink Scholar, Summer 2014
  • William McIver Jr., Ph.D., NSERC Industrial Research Chair in Mobile First Technology, Co-Principal Investigator

Client–Collaborators

  • Fayez Idris, Ph.D. IGT, Moncton, New Brunswick, Co-Principal Investigator

Funders

  • IGT
  • New Brunswick Innovation Fund - Research Assistantships Initiative
  • Mitacs Globallink
  • National Sciences and Engineering Research Council - Industrial Research Chair for Colleges


Contact

William McIver Jr., Ph.D.
NSERC Industrial Research Chair in Mobile & Ubiquitous Computing
Centre for Applied Research in Mobile & Ubiquitous Computing
New Brunswick Community College

Centre for Applied Research in Mobile & Ubiquitous Computing URL: http://wiki.nbcc.mobi
E-mail: bill.mciver@nbcc.ca
Twitter: @mciverNBCC
Blog: http://mciver.mobi/

New Brunswick Community College URL: http://nbcc.ca
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