A COTS (UHF) RFID Floor for Device-Free Ambient Assisted Living Monitoring

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The complexity and the intrusiveness of current proposals for AAL monitoring negatively impact end-user acceptability, and ultimately still hinder widespread adoption by key stakeholders (e.g. public and private sector care providers) who seek to balance system usefulness with upfront installation and long-term configuration and maintenance costs. We present the results of our experiments with a device-free wireless sensing (DFWS) approach utilising commercial off-the-shelf (COTS) Ultra High Frequency (UHF) Radio Frequency Identification (RFID) equipment. Our system is based on antennas above the ceiling and a dense deployment of passive RFID tags under the floor. We provide baseline performance of state of the art machine learning techniques applied to a region-level localisation task. We describe the dataset, which we collected in a realistic testbed, and which we share with the community. Contrary to past work with similar systems, our dataset was collected in a realistic domestic environment over a number of days. The data highlights the potential but also the problems that need to be solved before RFID DFWS approaches can be used for long-term AAL monitoring.
Original languageEnglish
Title of host publicationAmbient Intelligence – Software and Applications. ISAmI 2020
EditorsPaulo Novais, Gianni Vercelli, Josep L. Larriba-Pey, Francisco Herrera, Pablo Chamoso
PublisherSpringer
Pages127-136
Number of pages10
ISBN (Electronic)9783030583569
ISBN (Print)9783030583552
DOIs
Publication statusPublished - 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1239

Keywords

  • Ambient Assisted Living (AAL)
  • Device free wireless sensing
  • Fingerprinting
  • Healthcare monitoring
  • Indoor localisation
  • Radio-frequency identification (RFID)
  • Region-level tracking

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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