Bergeron Frédéric, Giroux Sylvain, Bouchard Kévin et Gaboury Sébastien. (2017). RFID based activities of daily living recognition. Dans 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). (p. 1-5). Piscataway, New Jersey : IEEE Press.
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URL officielle: http://dx.doi.org/doi:10.1109/UIC-ATC.2017.8397548
Résumé
In this paper, we address the issue of indoor activities of daily living recognition with a novel Activity Recognition System (ARS). This system only uses interactions between objects. Their locations is provided by a tracking system based on passive RFID tags to compute activity probabilities. Classification within the tracking system is done through a random forest that gives over 97% in accuracy. Activities are represented by the use of a custom behaviour tree, which makes it possible to compose interactions to form activities of any complexity. Interactions and activities are defined in a human readable form to allow everyone to expand them with minimal prior knowledge.
| Type de document: | Chapitre de livre |
|---|---|
| Date: | 2017 |
| Lieu de publication: | Piscataway, New Jersey |
| Identifiant unique: | 10.1109/UIC-ATC.2017.8397548 |
| 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: | smart home, radiofrequency identification, activity recognition, task analysis, forestry, tracking system classification, RFID based activities, custom behaviour tree |
| Déposé le: | 12 févr. 2021 19:08 |
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| Dernière modification: | 12 févr. 2021 19:08 |
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