Bouchard Kévin, Eusufzai Mahir Rafi, Ramezani Ramin et Naeim Arash. (2016). Generalizable spatial feature for human positioning based on Bluetooth beacons. Dans 2016 IEEE 7th Annual ubiquitous computing, electronics & mobile communication conference (UEMCON). (p. 1-5). Piscataway, New Jersey : IEEE.
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URL officielle: http://dx.doi.org/doi:10.1109/UEMCON.2016.7777884
Résumé
Every year smaller, cheaper and more precise technologies for ambient intelligence are emerging. One of them has been particularly gaining a lot of traction in the past few year. Indeed, due to their low cost and long battery life, the so-called Bluetooth beacons are being used for a wide range of applications including indoor localization of human. Our team has been using them to gather statistics about room occupancy in health monitoring. In this paper, we consider the beacons signals as time series and we define a new spatial feature that generalize across any configuration (floor plan, beacons number, etc.). The feature is used to distinguish positioning information from the resident. The results of leave-one-out experiments with various floor plans shows promising results.
| Type de document: | Chapitre de livre |
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| Date: | 2016 |
| Lieu de publication: | Piscataway, New Jersey |
| Identifiant unique: | 10.1109/UEMCON.2016.7777884 |
| Sujets: | Sciences naturelles et génie > Sciences mathématiques > Informatique Sciences de la santé |
| Département, module, service et unité de recherche: | Départements et modules > Département d'informatique et de mathématique |
| Liens connexes: | |
| Mots-clés: | data mining, Bluetooth, positioning, activity recognition, health monitoring, ambient intelligence |
| Déposé le: | 15 févr. 2021 16:33 |
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| Dernière modification: | 15 févr. 2021 16:33 |
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