Wireless Museum Information Systems

This paper presents an algorithm for RSSI fingerprint positioning based on Euclidean distance for the use in a priori existing larger and dynamically changing WLAN infrastructure environments. Symptomatical for such environments are changing sets of base stations for different calibration points and for calibration phase and positioning phase. The presented algorithm has an accuracy of 2.06m median location estimation error. The algorithm uses four threshold parameters to adapt the calculation to the specific measuring environment. Furthermore the reduction of calibration effort is investigated. It is shown that an enlargement of the calibration grid size from 1m to 6m increases the median location estimation error from 2.06m to 3.5m. Regular calibration measurements include measurements in four rectangular bearings. Reducing the number of calibration bearings results in less calibration effort, but worsens estimation quality.

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Wireless Museum Information Systems

Abstract: This article describes several technical aspects of three different museum information systems developed at the author's university. It examines key features of the systems, shows multiple ways of mobile content access and outlines future research potentials.

Cited by 3 publications

References 2 publications

3D WLAN indoor positioning in multi-storey buildings

3D WLAN indoor positioning in multi-storey buildings

RSSI-based Euclidean Distance algorithm for indoor positioning adapted for the use in dynamically changing WLAN environments and multi-level buildings

Improved Rssi-Based Euclidean Distance Positioning Algorithm for Large and Dynamic Wlan Environments

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