Title: Dynamic route prediction with the magnetic field strength for indoor positioning

Authors: Khuong An Nguyen; Zhiyuan Luo

Addresses: Department of Computer Science, Royal Holloway, University of London, Egham, Surrey, TW20 0EX, UK ' Department of Computer Science, Royal Holloway, University of London, Egham, Surrey, TW20 0EX, UK

Abstract: WiFi fingerprinting has been a popular approach for indoor positioning in the past decade. However, most existing fingerprint-based systems were designed as an on-demand service to guide the user to his wanted destination. This paper introduces a novel feature that allows the positioning system to predict in advance which walking route the user may use, and the potential destination. To achieve this goal, a new so-called routine database will be used to maintain the magnetic field strength in the form of the training sequences to represent the walking trajectories. The benefit of the system is that it does not adhere to a certain predicted trajectory. Instead, the system dynamically adjusts the prediction as more data are exposed throughout the user's journey. The proposed system was tested in a real indoor environment to demonstrate that the system not only successfully estimated the route and the destination, but also improved the single positioning prediction.

Keywords: wifi fingerprinting; magnetic field strength; indoor positioning; dynamic route prediction; walking routes; walking trajectory.

DOI: 10.1504/IJWMC.2017.083055

International Journal of Wireless and Mobile Computing, 2017 Vol.12 No.1, pp.16 - 35

Received: 27 Apr 2016
Accepted: 14 Dec 2016

Published online: 18 Mar 2017 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article