Using RFID to Detect Interactions in Ambient Assisted Living Environments

Raúl Parada; Joan Melià-Seguí; Marc Morenza-Cinos; Anna Carreras; Rafael Pous

doi:10.1109/MIS.2015.43

Using RFID to Detect Interactions in Ambient Assisted Living Environments

Raúl Parada, Joan Melià-Seguí, Marc Morenza-Cinos, Anna Carreras, Rafael Pous

Producció científica: Article en revista indexada › Article › Avaluat per experts

39 Cites (Scopus)

Resum

Elderly people with physical or cognitive disabilities such as visual impairment lack independence in their everyday activities, such as shopping in retail stores. Ambient assisted living (AAL) technologies can help. The authors of this article propose the use of RFID technologies to enable an AAL system in a retail store. This article presents an RFID-enabled intelligent system that can detect user-object interactions via a supervised machine learning algorithm. The authors' proposal detects RFID signals from different objects and classifies them as interacted or static objects through an automatic training system, achieving a detection accuracy over 86 percent.

Idioma original	Anglès
Número d’article	7156012
Pàgines (de-a)	16-22
Nombre de pàgines	7
Revista	IEEE Intelligent Systems
Volum	30
Número	4
DOIs	https://doi.org/10.1109/MIS.2015.43
Estat de la publicació	Publicada - 1 de jul. 2015
Publicat externament	Sí

Accés al document

10.1109/MIS.2015.43

Altres arxius i enllaços

Link to publication in Scopus

Com citar-ho

@article{501ec9cfaaee43e193ac1a3a2d9c1ac3,

title = "Using RFID to Detect Interactions in Ambient Assisted Living Environments",

abstract = "Elderly people with physical or cognitive disabilities such as visual impairment lack independence in their everyday activities, such as shopping in retail stores. Ambient assisted living (AAL) technologies can help. The authors of this article propose the use of RFID technologies to enable an AAL system in a retail store. This article presents an RFID-enabled intelligent system that can detect user-object interactions via a supervised machine learning algorithm. The authors' proposal detects RFID signals from different objects and classifies them as interacted or static objects through an automatic training system, achieving a detection accuracy over 86 percent.",

keywords = "handicapped persons/special needs, intelligent systems, interactive systems, machine learning, sensor networks, wireless systems",

author = "Ra{\'u}l Parada and Joan Meli{\`a}-Segu{\'i} and Marc Morenza-Cinos and Anna Carreras and Rafael Pous",

note = "Publisher Copyright: {\textcopyright} 2001-2011 IEEE.",

year = "2015",

month = jul,

day = "1",

doi = "10.1109/MIS.2015.43",

language = "English",

volume = "30",

pages = "16--22",

journal = "IEEE Intelligent Systems",

issn = "1541-1672",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "4",

}

TY - JOUR

T1 - Using RFID to Detect Interactions in Ambient Assisted Living Environments

AU - Parada, Raúl

AU - Melià-Seguí, Joan

AU - Morenza-Cinos, Marc

AU - Carreras, Anna

AU - Pous, Rafael

PY - 2015/7/1

Y1 - 2015/7/1

N2 - Elderly people with physical or cognitive disabilities such as visual impairment lack independence in their everyday activities, such as shopping in retail stores. Ambient assisted living (AAL) technologies can help. The authors of this article propose the use of RFID technologies to enable an AAL system in a retail store. This article presents an RFID-enabled intelligent system that can detect user-object interactions via a supervised machine learning algorithm. The authors' proposal detects RFID signals from different objects and classifies them as interacted or static objects through an automatic training system, achieving a detection accuracy over 86 percent.

AB - Elderly people with physical or cognitive disabilities such as visual impairment lack independence in their everyday activities, such as shopping in retail stores. Ambient assisted living (AAL) technologies can help. The authors of this article propose the use of RFID technologies to enable an AAL system in a retail store. This article presents an RFID-enabled intelligent system that can detect user-object interactions via a supervised machine learning algorithm. The authors' proposal detects RFID signals from different objects and classifies them as interacted or static objects through an automatic training system, achieving a detection accuracy over 86 percent.

KW - handicapped persons/special needs

KW - intelligent systems

KW - interactive systems

KW - machine learning

KW - sensor networks

KW - wireless systems

UR - http://www.scopus.com/inward/record.url?scp=84937204127&partnerID=8YFLogxK

U2 - 10.1109/MIS.2015.43

DO - 10.1109/MIS.2015.43

M3 - Article

AN - SCOPUS:84937204127

SN - 1541-1672

VL - 30

SP - 16

EP - 22

JO - IEEE Intelligent Systems

JF - IEEE Intelligent Systems

IS - 4

M1 - 7156012

ER -

Using RFID to Detect Interactions in Ambient Assisted Living Environments

Resum

Accés al document

Altres arxius i enllaços

Fingerprint

Com citar-ho