Abstract

The paper presents a Wi-Fi-based indoor localisation system. It consists of two main parts, the localisation model and an Access Points (APs) detection module. The system uses a received signal strength (RSS) gathered by multiple mobile terminals to detect which AP should be included in the localisation model and whether the model needs to be updated (rebuilt). The rebuilding of the localisation model prevents the localisation system from a significant loss of accuracy. The proposed automatic detection of missing APs has a universal character and it can be applied to any Wi-Fi localisation model which was created using the fingerprinting method. The paper considers the localisation model based on the Random Forest algorithm. The system was tested on data collected inside a multi-floor academic building. The proposed implementation reduced the mean horizontal error by 5.5 m and the classification error for the floor’s prediction by 0.26 in case of a serious malfunction of a Wi-Fi infrastructure. Several simulations were performed, taking into account different occupancy scenarios as well as different numbers of missing APs. The simulations proved that the system correctly detects missing and present APs in the Wi-Fi infrastructure.

Highlights

  • Localisation services are part of our daily routine

  • This paper proposes a localisation solution that is based on received signal strength (RSS) from various access points (APs) of the Wi-Fi infrastructure inside the building

  • The results presented in this paper differ from most of the localisation solutions presented in various other articles, as they usually cover only one floor and are limited to a small area

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Summary

Introduction

Localisation services are part of our daily routine. While services based on Global PositioningSystem (GPS) provide sufficient accuracy when positioning in the outdoor environment, the issue of providing an accurate indoor position is much more complicated. Localisation services are part of our daily routine. System (GPS) provide sufficient accuracy when positioning in the outdoor environment, the issue of providing an accurate indoor position is much more complicated. A higher level of accuracy is required indoors than outdoors. This is because even a relatively small one-meter localisation error in the indoor environment may mean that the device being localised is in a different room or on a different floor. The most accurate localisation systems use different indoor localisation solutions or require the installation of particular devices inside the building that will enhance the localisation but at additional costs

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