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Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction

Indoor localization has become a mature research area, but further scientific developments are limited due to the lack of open datasets and corresponding frameworks suitable to compare and evaluate specialized localization solutions. Although several competitions provide datasets and environments fo...

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Autores principales: Baronti, Paolo, Barsocchi, Paolo, Chessa, Stefano, Mavilia, Fabio, Palumbo, Filippo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308497/
https://www.ncbi.nlm.nih.gov/pubmed/30562934
http://dx.doi.org/10.3390/s18124462
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author Baronti, Paolo
Barsocchi, Paolo
Chessa, Stefano
Mavilia, Fabio
Palumbo, Filippo
author_facet Baronti, Paolo
Barsocchi, Paolo
Chessa, Stefano
Mavilia, Fabio
Palumbo, Filippo
author_sort Baronti, Paolo
collection PubMed
description Indoor localization has become a mature research area, but further scientific developments are limited due to the lack of open datasets and corresponding frameworks suitable to compare and evaluate specialized localization solutions. Although several competitions provide datasets and environments for comparing different solutions, they hardly consider novel technologies such as Bluetooth Low Energy (BLE), which is gaining more and more importance in indoor localization due to its wide availability in personal and environmental devices and to its low costs and flexibility. This paper contributes to cover this gap by: (i) presenting a new indoor BLE dataset; (ii) reviewing several, meaningful use cases in different application scenarios; and (iii) discussing alternative uses of the dataset in the evaluation of different positioning and navigation applications, namely localization, tracking, occupancy and social interaction.
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spelling pubmed-63084972019-01-04 Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction Baronti, Paolo Barsocchi, Paolo Chessa, Stefano Mavilia, Fabio Palumbo, Filippo Sensors (Basel) Article Indoor localization has become a mature research area, but further scientific developments are limited due to the lack of open datasets and corresponding frameworks suitable to compare and evaluate specialized localization solutions. Although several competitions provide datasets and environments for comparing different solutions, they hardly consider novel technologies such as Bluetooth Low Energy (BLE), which is gaining more and more importance in indoor localization due to its wide availability in personal and environmental devices and to its low costs and flexibility. This paper contributes to cover this gap by: (i) presenting a new indoor BLE dataset; (ii) reviewing several, meaningful use cases in different application scenarios; and (iii) discussing alternative uses of the dataset in the evaluation of different positioning and navigation applications, namely localization, tracking, occupancy and social interaction. MDPI 2018-12-17 /pmc/articles/PMC6308497/ /pubmed/30562934 http://dx.doi.org/10.3390/s18124462 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Baronti, Paolo
Barsocchi, Paolo
Chessa, Stefano
Mavilia, Fabio
Palumbo, Filippo
Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction
title Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction
title_full Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction
title_fullStr Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction
title_full_unstemmed Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction
title_short Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction
title_sort indoor bluetooth low energy dataset for localization, tracking, occupancy, and social interaction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308497/
https://www.ncbi.nlm.nih.gov/pubmed/30562934
http://dx.doi.org/10.3390/s18124462
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