Accurate Trilateration for Passive RFID Localization in Smart Homes View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-03

AUTHORS

Kevin Bouchard, Dany Fortin-Simard, Sebastien Gaboury, Bruno Bouchard, Abdenour Bouzouane

ABSTRACT

The smart home as emerged in recent years as a new trend of research aiming to propose an alternative to postpone the institutionalization of cognitively-impaired people. These habitats are intended to provide security, guidance and direct support services to its resident. To fulfill this important mission, an algorithm first has to identify the ongoing activities of its user by tracking, in real time, the position of the main daily living objects. Many researchers addressed this issue by proposing systems based ultrasonic wave sensors, video cameras, and radio-frequency identification (RFID). However, the RFID technology, constitutes the most viable technology for smart homes. Recently, several RFID localization algorithms have been developed, mainly for commercial and industrial uses, but they are not precise enough to be used in an assistive context. Furthermore, the majority of them focuses on systems exploiting active RFID tags, which need batteries and are much more expensive. We present, in this paper, a new algorithmic approach for passive RFID localization in smart homes based on elliptical trilateration and fuzzy logic. This new algorithm has been implemented in a real smart home infrastructure. It has been rigorously tested and outperformed the comparable approaches. More... »

PAGES

32-47

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10776-013-0234-4

DOI

http://dx.doi.org/10.1007/s10776-013-0234-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1019782053


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138 schema:name LIARA Laboratory, UQAC, G7H 2B1, Chicoutimi, QC, Canada
139 rdf:type schema:Organization
 




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