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Sensors 2018, 18(2), 487; doi:10.3390/s18020487

Off-Line Evaluation of Mobile-Centric Indoor Positioning Systems: The Experiences from the 2017 IPIN Competition

1
Institute of New Imaging Technologies, Universitat Jaume I, 12071 Castelló, Spain
2
Centre for Automation and Robotics (CAR), CSIC-UPM, 28500 Arganda del Rey, Spain
3
Algoritmi Research Centre, University of Minho, 4800-058 Guimarães, Portugal
4
AraraDS, Monseñor Sótero Sanz 161, 8340457 Santiago, Chile
5
Department of Electrical Engineering, Yuan Ze University, Zhongli 32003, Taiwan
6
Faculty for Geomatics, Computer Science and Mathematics, HFT Stuttgart—University of Applied Sciences, 70174 Stuttgart, Germany
7
Estudis d’Informàtica, Multimèdia i Telecomunicació, Universitat Oberta de Catalunya, Rambla del Poblenou 156, 08018 Barcelona, Spain
8
Internet Interdisciplinary Institute IN3, Av. Carl Friedrich Gauss 5, 08860 Castelldefels, Barcelona, Spain
9
Centro de Computação Gráfica (CCG), 4800-058 Guimarães, Portugal
10
Department of Electrical Engineering, National Ilan University, Yilan 26047, Taiwan
11
Research Center for Information Technology Innovation, Academia Sinica, Taipei 11529, Taiwan
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Received: 15 December 2017 / Revised: 26 January 2018 / Accepted: 31 January 2018 / Published: 6 February 2018
(This article belongs to the Special Issue Smartphone-based Pedestrian Localization and Navigation)
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Abstract

The development of indoor positioning solutions using smartphones is a growing activity with an enormous potential for everyday life and professional applications. The research activities on this topic concentrate on the development of new positioning solutions that are tested in specific environments under their own evaluation metrics. To explore the real positioning quality of smartphone-based solutions and their capabilities for seamlessly adapting to different scenarios, it is needed to find fair evaluation frameworks. The design of competitions using extensive pre-recorded datasets is a valid way to generate open data for comparing the different solutions created by research teams. In this paper, we discuss the details of the 2017 IPIN indoor localization competition, the different datasets created, the teams participating in the event, and the results they obtained. We compare these results with other competition-based approaches (Microsoft and Perf-loc) and on-line evaluation web sites. The lessons learned by organising these competitions and the benefits for the community are addressed along the paper. Our analysis paves the way for future developments on the standardization of evaluations and for creating a widely-adopted benchmark strategy for researchers and companies in the field. View Full-Text
Keywords: indoor positioning and navigation; Wi-Fi fingerprinting; sensor fusion; competitions; benchmarking indoor positioning and navigation; Wi-Fi fingerprinting; sensor fusion; competitions; benchmarking
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MDPI and ACS Style

Torres-Sospedra, J.; Jiménez, A.R.; Moreira, A.; Lungenstrass, T.; Lu, W.-C.; Knauth, S.; Mendoza-Silva, G.M.; Seco, F.; Pérez-Navarro, A.; Nicolau, M.J.; Costa, A.; Meneses, F.; Farina, J.; Morales, J.P.; Lu, W.-C.; Cheng, H.-T.; Yang, S.-S.; Fang, S.-H.; Chien, Y.-R.; Tsao, Y. Off-Line Evaluation of Mobile-Centric Indoor Positioning Systems: The Experiences from the 2017 IPIN Competition. Sensors 2018, 18, 487.

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