Transparent RFID tag wall enabled by artificial intelligence for assisted living.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
16 09 2024
16 09 2024
Historique:
received:
25
01
2024
accepted:
08
06
2024
medline:
17
9
2024
pubmed:
17
9
2024
entrez:
16
9
2024
Statut:
epublish
Résumé
Current approaches to activity-assisted living (AAL) are complex, expensive, and intrusive, which reduces their practicality and end user acceptance. However, emerging technologies such as artificial intelligence and wireless communications offer new opportunities to enhance AAL systems. These improvements could potentially lower healthcare costs and reduce hospitalisations by enabling more effective identification, monitoring, and localisation of hazardous activities, ensuring rapid response to emergencies. In response to these challenges, this paper introduces the Transparent RFID Tag Wall (TRT-Wall), a novel system taht utilises a passive ultra-high frequency (UHF) radio-frequency identification (RFID) tag array combined with deep learning for contactless human activity monitoring. The TRT-Wall is tested on five distinct activities: sitting, standing, walking (in both directions), and no-activity. Experimental results demonstrate that the TRT-Wall distinguishes these activities with an impressive average accuracy of
Identifiants
pubmed: 39284809
doi: 10.1038/s41598-024-64411-y
pii: 10.1038/s41598-024-64411-y
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
18896Subventions
Organisme : Engineering and Physical Sciences Research Council
ID : EP/X040518/1
Organisme : Engineering and Physical Sciences Research Council
ID : EP/T021020/1
Informations de copyright
© 2024. The Author(s).
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