Human activity recognition in smart homes based on passive RFID localization

Bouchard, Kévin; Bilodeau, Jean-Sébastien; Fortin-Simard, Dany; Gaboury, Sébastien; Bouchard, Bruno; Bouzouane, Abdenour

doi:10.1145/2674396.2674403

Cited by 16 publications

(5 citation statements)

References 26 publications

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“…In the literature, various methods have been proposed [ 27 , 28 , 29 , 30 , 31 , 32 ] to detect activities of daily life for elderly people at home using passive infrared (PIR) motion sensors, body-worn sensors, pressure sensors, video monitoring, or sound recognition. Bouchard et al [ 33 ] describe their work on human activities recognition in smart homes using passive RFID (Radio Frequency IDentification) tags. They aim to identify human activities with a minimal rate of false positives.…”

Section: Related Workmentioning

confidence: 99%

A Framework for Detecting and Analyzing Behavior Changes of Elderly People over Time Using Learning Techniques

Zekri

Delot

Thilliez

et al. 2020

Sensors

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A sensor-rich environment can be exploited for elder healthcare applications. In this work, our objective was to conduct a continuous and long-term analysis of elderly’s behavior for detecting changes. We indeed did not study snapshots of the behavior but, rather, analyzed the overall behavior evolution over long periods of time in order to detect anomalies. Therefore, we proposed a learning method and formalize a normal behavior pattern for elderly people related to her/his Activities of Daily Living (ADL). We also defined a temporal similarity score between activities that allows detecting behavior changes over time. During the periods of time when behavior changes occurred, we then focused on each activity to identify anomalies. Finally, when a behavior change occurred, it was also necessary to help caregivers and/or family members understand the possible pathology detected in order for them to react accordingly. Therefore, the framework presented in this article includes a fuzzy logic-based decision support system that provides information about the suspected disease and its severity.

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Section: Related Workmentioning

confidence: 99%

A Framework for Detecting and Analyzing Behavior Changes of Elderly People over Time Using Learning Techniques

Zekri

Delot

Thilliez

et al. 2020

Sensors

View full text Add to dashboard Cite

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“…Notably, passive RFID tags are powered by the radio waves that are emitted by the antennas, and so they do not have internal sources of power and it does not add radio noise with a good resistance performance in harsh environments. The tags are widely adapted in many applications such as when applied to objects (cups, a kettle or furniture) in Smart homes [5]. The drawbacks about passive RFID tags that they require higher power interrogators, small memory with a limited amount of data to be stored and low reading ranges.…”

Section: The Radio Frequency Identificationmentioning

confidence: 99%

RFID Systems in Healthcare Settings and Activity of Daily Living in Smart Homes: A Review

Alsinglawi¹,

Nguyễn²,

Gunawardana³

et al. 2017

ETSN

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Elderly inhabitants have a strong influence to healthcare facilities globally in the last few years as a result of the high demand on the healthcare services and the gap between the services provided by caregivers and the increasing number of older people. Radio Frequency Identification (RFID) technologies have been increasingly adopted in smart homes and used widely for indoor localisation. These technologies have been benefiting to healthcare domain where they improve the quality of services delivering by healthcare providers. This article presents a comprehensive review on RFID systems and healthcare research works in smart homes. We also compare RFID-based solutions in healthcare and distinguish challenges of smart home technologies in indoor environment. We also discuss research challenges related to Activity in Daily Living (ADL) in smart homes for wellbeing.

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“…Notably, passive RFID tags are powered by the radio waves that are emitted by the antennas so they do not have an internal source of power. The tags are usually applied on objects in smart homes, such as cups, kettle or furniture [10]. They support elderly citizens who live independently in their residential homes and need less expensive service than traditional nursing homes or hospitals.…”

Section: Smart Homes Systems and Rfidmentioning

confidence: 99%