An experimental comparative study of RSSI-based positioning algorithms for passive RFID localization in smart environments View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-10

AUTHORS

Jean-Sébastien Bilodeau, Abdenour Bouzouane, Bruno Bouchard, Sebastien Gaboury

ABSTRACT

The rapid adoption of wireless technologies has increased the interest of many laboratories about the field of wireless sensor network or the radio-frequency identification (RFID) technology which has emerged as a winning combination for the implementation of an advanced assistance system within smart environments. To fulfill the important mission of a technological assistance, a technique first had to identify the ongoing activities of its user by tracking everyday life objects in real time using, for example, passive RFID tags. To increase the quality of information extracted from the objects localization by properly using the received signal strength indicator, this paper explores Kalman filter, particle filter and few others filtering algorithm that enhances the tracking performance. It also discusses three of the most interesting methods that can be applied for the localization of objects in smart environments without requiring the installation of references tags everywhere. Finally, to increase the value, we include experiments that were conducted within a real smart home infrastructure to review the positive and negative elements of each method. More... »

PAGES

1327-1343

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12652-017-0531-3

DOI

http://dx.doi.org/10.1007/s12652-017-0531-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1090285664


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58 schema:description The rapid adoption of wireless technologies has increased the interest of many laboratories about the field of wireless sensor network or the radio-frequency identification (RFID) technology which has emerged as a winning combination for the implementation of an advanced assistance system within smart environments. To fulfill the important mission of a technological assistance, a technique first had to identify the ongoing activities of its user by tracking everyday life objects in real time using, for example, passive RFID tags. To increase the quality of information extracted from the objects localization by properly using the received signal strength indicator, this paper explores Kalman filter, particle filter and few others filtering algorithm that enhances the tracking performance. It also discusses three of the most interesting methods that can be applied for the localization of objects in smart environments without requiring the installation of references tags everywhere. Finally, to increase the value, we include experiments that were conducted within a real smart home infrastructure to review the positive and negative elements of each method.
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