Empowering the Blind: Contactless Activity Recognition with Commodity Software-Defined Radio and Ultra-High-Frequency Radio Frequency Identification.

SDR-RFID blind contactless activity monitoring visual impairment

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
04 Jun 2024
Historique:
received: 17 04 2024
revised: 21 05 2024
accepted: 22 05 2024
medline: 19 6 2024
pubmed: 19 6 2024
entrez: 19 6 2024
Statut: epublish

Résumé

This study presents a novel computational radio frequency identification (RFID) system designed specifically for assisting blind individuals, utilising software-defined radio (SDR) with coherent detection. The system employs battery-less ultra-high-frequency (UHF) tag arrays in Gen2 RFID systems, enhancing the transmission of sensed information beyond standard identification bits. Our method uses an SDR reader to efficiently manage multiple tags with Gen2 preambles implemented on a single transceiver card. The results highlight the system's real-time capability to detect movements and direction of walking within a four-meter range, indicating significant advances in contactless activity monitoring. This system not only handles the complexities of multiple tag scenarios but also delineates the influence of system parameters on RFID operational efficiency. This study contributes to assistive technology, provides a platform for future advancements aimed at addressing contemporary limitations in pseudo-localisation, and offers a practical, affordable assistance system for blind individuals.

Identifiants

pubmed: 38894436
pii: s24113645
doi: 10.3390/s24113645
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Muhammad Zakir Khan (MZ)

James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK.

Turke Althobaiti (T)

Department of Computer Science, Faculty of Science, Northern Border University, Arar 73222, Saudi Arabia.

Muhannad Almutiry (M)

Electrical Engineering Department, Northern Border University, Arar 73222, Saudi Arabia.

Naeem Ramzan (N)

School of Computing, Engineering and Physical Sciences, University of the West of Scotland, Paisley PA1 2BE, UK.

Classifications MeSH