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Publication . Article . 2018

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

Paolo Baronti; Paolo Barsocchi; Stefano Chessa; Fabio Mavilia; Filippo Palumbo;
Open Access
English
Published: 01 Dec 2018 Journal: Sensors (Basel, Switzerland), volume 18, issue 12 (eissn: 1424-8220, Copyright policy )
Publisher: MDPI
Country: Italy
Abstract
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
and (iii) discussing alternative uses of the dataset in the evaluation of different positioning and navigation applications, namely localization, tracking, occupancy and social interaction.
(ii) reviewing several, meaningful use cases in different application scenarios
Subjects by Vocabulary

Library of Congress Subject Headings: lcsh:Chemical technology lcsh:TP1-1185

Microsoft Academic Graph classification: Tracking (particle physics) Computer science Real-time computing Occupancy Cover (telecommunications) Bluetooth Low Energy computer.internet_protocol computer Flexibility (engineering) Social relation

Subjects

Article, indoor localization, tracking, social interaction, Bluetooth Low Energy, dataset, Electrical and Electronic Engineering, Biochemistry, Instrumentation, Atomic and Molecular Physics, and Optics, Analytical Chemistry, Indoor localization, Tracking, Social interaction, Bluetooth Low Energy, Dataset

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Funded by
EC| NESTORE
Project
NESTORE
Novel Empowering Solutions and Technologies for Older people to Retain Everyday life activities
  • Funder: European Commission (EC)
  • Project Code: 769643
  • Funding stream: H2020 | RIA
Validated by funder
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Sensors
Article . 2018
Providers: PubMed Central
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