Volume IV-2/W4
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 319-326, 2017
https://doi.org/10.5194/isprs-annals-IV-2-W4-319-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 319-326, 2017
https://doi.org/10.5194/isprs-annals-IV-2-W4-319-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  13 Sep 2017

13 Sep 2017

A STATISTICAL ANALYSIS ON THE SYSTEM PERFORMANCE OF A BLUETOOTH LOW ENERGY INDOOR POSITIONING SYSTEM IN A 3D ENVIRONMENT

G. G. Haagmans1, S. Verhagen1, R. L. Voûte2,3, and E. Verbree4 G. G. Haagmans et al.
  • 1Geoscience and Remote Sensing, Civil Engineering and Geosciences Faculty, TU Delft, the Netherlands
  • 2CGI Nederland BV, George Hintzenweg 89, 3068 AX Rotterdam, the Netherlands
  • 3Department Urbanism, Faculty of Architecture and the Built Environment, TU Delft, the Netherlands
  • 4OTB – Research for the Built Environment, Faculty of Architecture and the Built Environment, TU Delft, the Netherlands

Keywords: Indoor positioning system, Bluetooth low energy, system performance, theoretical design computations, precision, optimal configuration, 3D space

Abstract. Since GPS tends to fail for indoor positioning purposes, alternative methods like indoor positioning systems (IPS) based on Bluetooth low energy (BLE) are developing rapidly. Generally, IPS are deployed in environments covered with obstacles such as furniture, walls, people and electronics influencing the signal propagation. The major factor influencing the system performance and to acquire optimal positioning results is the geometry of the beacons. The geometry of the beacons is limited to the available infrastructure that can be deployed (number of beacons, basestations and tags), which leads to the following challenge: Given a limited number of beacons, where should they be placed in a specified indoor environment, such that the geometry contributes to optimal positioning results? This paper aims to propose a statistical model that is able to select the optimal configuration that satisfies the user requirements in terms of precision. The model requires the definition of a chosen 3D space (in our case 7 × 10 × 6 meter), number of beacons, possible user tag locations and a performance threshold (e.g. required precision). For any given set of beacon and receiver locations, the precision, internal- and external reliability can be determined on forehand. As validation, the modeled precision has been compared with observed precision results. The measurements have been performed with an IPS of BlooLoc at a chosen set of user tag locations for a given geometric configuration. Eventually, the model is able to select the optimal geometric configuration out of millions of possible configurations based on a performance threshold (e.g. required precision).