Bluetooth dataset for proximity detection in indoor environments collected with smartphones
This paper describes a data collection experiment and the resulting dataset based on Bluetooth beacon messages collected in an indoor museum. The goal of this dataset is to study algorithms and techniques for proximity detection between people and points of interest (POI). To this purpose, we releas...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340924001860 |
| _version_ | 1827313653517385728 |
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| author | Michele Girolami Davide La Rosa Paolo Barsocchi |
| author_facet | Michele Girolami Davide La Rosa Paolo Barsocchi |
| author_sort | Michele Girolami |
| collection | DOAJ |
| description | This paper describes a data collection experiment and the resulting dataset based on Bluetooth beacon messages collected in an indoor museum. The goal of this dataset is to study algorithms and techniques for proximity detection between people and points of interest (POI). To this purpose, we release the data we collected during 32 museum's visits, in which we vary the adopted smartphones and the visiting paths. The smartphone is used to collect Bluetooth beacons emitted by Bluetooth tags positioned nearby each POI. The visiting layout defines the order of visit of 10 artworks. The combination of different smartphones, the visiting paths and features of the indoor museum allow experiencing with realistic environmental conditions. The dataset comprises RSS (Received Signal Strength) values, timestamp and artwork identifiers, as long as a detailed ground truth, reporting the starting and ending time of each artwork's visit. The dataset is addressed to researchers and industrial players interested in further investigating how to automatically detect the location or the proximity between people and specific points of interest, by exploiting commercial technologies available with smartphone. The dataset is designed to speed up the prototyping process, by releasing an accurate ground truth annotation and details concerning the adopted hardware. |
| first_indexed | 2024-03-07T22:54:03Z |
| format | Article |
| id | doaj.art-333a4e961a284784be50cad0a6d10159 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-24T22:20:00Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-333a4e961a284784be50cad0a6d101592024-03-20T06:10:10ZengElsevierData in Brief2352-34092024-04-0153110215Bluetooth dataset for proximity detection in indoor environments collected with smartphonesMichele Girolami0Davide La Rosa1Paolo Barsocchi2Corresponding author.; Institute of Information Science and Technologies, National Research Council, (ISTI-CNR), Via G. Moruzzi, 1, 56124, Pisa, ItalyInstitute of Information Science and Technologies, National Research Council, (ISTI-CNR), Via G. Moruzzi, 1, 56124, Pisa, ItalyInstitute of Information Science and Technologies, National Research Council, (ISTI-CNR), Via G. Moruzzi, 1, 56124, Pisa, ItalyThis paper describes a data collection experiment and the resulting dataset based on Bluetooth beacon messages collected in an indoor museum. The goal of this dataset is to study algorithms and techniques for proximity detection between people and points of interest (POI). To this purpose, we release the data we collected during 32 museum's visits, in which we vary the adopted smartphones and the visiting paths. The smartphone is used to collect Bluetooth beacons emitted by Bluetooth tags positioned nearby each POI. The visiting layout defines the order of visit of 10 artworks. The combination of different smartphones, the visiting paths and features of the indoor museum allow experiencing with realistic environmental conditions. The dataset comprises RSS (Received Signal Strength) values, timestamp and artwork identifiers, as long as a detailed ground truth, reporting the starting and ending time of each artwork's visit. The dataset is addressed to researchers and industrial players interested in further investigating how to automatically detect the location or the proximity between people and specific points of interest, by exploiting commercial technologies available with smartphone. The dataset is designed to speed up the prototyping process, by releasing an accurate ground truth annotation and details concerning the adopted hardware.http://www.sciencedirect.com/science/article/pii/S2352340924001860CrowdSensingBluetoothIndoor localizationProximityCultural heritage |
| spellingShingle | Michele Girolami Davide La Rosa Paolo Barsocchi Bluetooth dataset for proximity detection in indoor environments collected with smartphones Data in Brief CrowdSensing Bluetooth Indoor localization Proximity Cultural heritage |
| title | Bluetooth dataset for proximity detection in indoor environments collected with smartphones |
| title_full | Bluetooth dataset for proximity detection in indoor environments collected with smartphones |
| title_fullStr | Bluetooth dataset for proximity detection in indoor environments collected with smartphones |
| title_full_unstemmed | Bluetooth dataset for proximity detection in indoor environments collected with smartphones |
| title_short | Bluetooth dataset for proximity detection in indoor environments collected with smartphones |
| title_sort | bluetooth dataset for proximity detection in indoor environments collected with smartphones |
| topic | CrowdSensing Bluetooth Indoor localization Proximity Cultural heritage |
| url | http://www.sciencedirect.com/science/article/pii/S2352340924001860 |
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