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ZENODO
Dataset . 2017
License: CC BY
Data sources: Datacite
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Dataset . 2017
License: CC BY
Data sources: Datacite
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Datasets and Supporting Materials for the IPIN 2017 Competition Track 3 (Smartphone-based, off-site)

Authors: Ruiz, Antonio Ramon Jimenez; Mendoza-Silva, Germán Martín; Seco, Fernando; Torres-Sospedra, Joaquín;

Datasets and Supporting Materials for the IPIN 2017 Competition Track 3 (Smartphone-based, off-site)

Abstract

This package contains the datasets and supplementary materials used in the IPIN 2017 Competition (Sapporo, Japan). Contents: Track3_LogfileDescription_and_SupplementaryMaterial.pdf: Description of the logfiles and supplemental materials. Track3_TechnicalAnnex.pdf: Technical annex describing the competition 01-Logfiles: This folder contains a subfolder with the 25 training logfiles, a subfolder with the 9 validation logfiles, and a subfolder with the 7 blind evaluation logfiles as provided to competitors. 02-Supplementary_Materials: This folder contains the Matlab/Octave parser, the raster maps, the visualization of the training routes and the location of the BLE beacon (CAR) and some Wi-Fi APs (UJIUB). 03-Evaluation: This folder contains the scripts used to calculate the competition metric, the 75th percentile on the 505 evaluation points. The ground truth is also provided in MatLab format and as a CSV file. Since the results must be provided with a 2Hz freq. starting from apptimestamp 0, the GT includes the closest timestamp matching the timing provided by competitors. Please, cite the following works when using the datasets included in this package: Torres-Sospedra, J.; Jiménez, A. R.; Moreira, A.; Lungenstrass, T.; Lu, W.-C.; Knauth, S.; Mendoza-Silva, G.M.; Seco, F.; Perez-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. and Tsao, Y. Off-line evaluation of mobile-centric Indoor Positioning Systems: the experiences from the 2017 IPIN competition Sensors Vol. 18(2), 2018. http://dx.doi.org/10.3390/s18020487 Jimenez, A.R.; Mendoza-Silva, G.M.; Seco, F.; Torres-Sospedra, J. Datasets and Supporting Materials for the IPIN 2017 Competition Track 3 (Smartphone-based, off-site). http://dx.doi.org/10.5281/zenodo.2823924 Additional information can be found at: http://evaal.aaloa.org/2017/2017-competition-home http://indoorloc.uji.es/ipin2017track3/ For any further questions about the database and this competition track, please contact: Joaquín Torres (jtorres@uji.es) Institute of New Imaging Technologies, Universitat Jaume I, Spain. Antonio R. Jiménez (antonio.jimenez@csic.es) Center of Automation and Robotics (CAR)-CSIC/UPM, Spain.

We would like to thank Topcon Corporation for sponsoring the competition track with an award for the winning team. We are also grateful to Francesco Potortì, Sangjoon Park, Hideo Makino, Nobuo Kawaguchi, Takeshi Kurata and Jesús Ureña for their invaluable help in organizing and promoting the IPIN competition and conference. Many thanks to Raúl Montoliu, Emilio Sansano, Marina Granel and Luis Alisandra for collecting the databases in the UJITI building. Parts of this work were carried out with the financial support received from projects and grants: REPNIN network (TEC2015-71426-REDT), LORIS (TIN2012-38080-C04-04), TARSIUS (TIN2015-71564-C4-2-R (MINECO/FEDER)), SmartLoc (CSIC-PIE Ref.201450E011), "Metodologías avanzadas para el diseño, desarrollo, evaluación e integración de algoritmos de localización en interiores" (TIN2015-70202-P), GEO-C (Project ID: 642332, H2020-MSCA-ITN-2014—Marie Sklodowska-Curie Action:Innovative Training Networks).

Keywords

RF Fingerprinting, Sensor Fusion, Indoor Positioning, Particle filter, Kalman filter, Pedestrian Dead Reckoning, Competition datasets, Indoor Navigation, Map Matching

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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