Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Evaluating Ambient Assisted Living Components and Systems
Guest editors: Stefano Chessa, Juan Antonio Alvarez García and Paolo Barsocchi
Article type: Research Article
Authors: Moschevikin, Alex; * | Galov, Aleksandr | Volkov, Alexander | Mikov, Alexander | Reginya, Sergey | Voronov, Roman | Reut, Oleg | Serezhina, Maria | Zaitsev, Alexey | Lunkov, Pavel | Malodushev, Sergey | Kirienko, Dmitry | Fedorov, Alexander | Sementsov, Alexey | Podryadchikov, Sergey | Spiridonov, Konstantin | Tershukov, Ivan | Yushev, Artem | Nuikin, Alexander | Gostev, Kirill | Pashinsky, Sergey | Soloviev, Alexei
Affiliations: RTL-Service JSC and Petrozavodsk State University, Lenin Str., 31, 185910 Petrozavodsk, Russian Federation. E-mail: alexmou@rtlservice.com
Correspondence: [*] Corresponding author. E-mail: alexmou@rtlservice.com.
Abstract: In this paper, we examine the results of the EvAAL-2013 localization competition. We present a comprehensive description of RealTrac™ technology, the winner of this competition. Focused on real-time location technology, RealTrac hardware includes a server, access points (gateways and repeaters), and mobile devices (voice intercoms and tags). A location calculation engine is based on Bayesian algorithms fusing data from time-of-flight and received signal strength measurements, inertial measurement units, building structure, and optionally, from context events. The peculiarity of the embedded navigation system is that it works effectively independent of the place where the mobile tag is actually attached, i.e., it could be mounted on one’s foot, carried freely in a jacket pocket, held in one’s hand, or even hung on a shoestring. The RealTrac system can easily be combined with third-party systems via the Real Time Location System Communication Protocol that consists of an open API and uses a common Keyhole Markup Language format for geo-data presentation. Furthermore, in this paper, we show that the scores obtained in the competition regarding positioning accuracy might be significantly higher when the applied particle filter is appropriately configured and a probability-based approach for area-of-interest determination is introduced.
Keywords: Local positioning system, indoor navigation, Bayesian filter, time-of-flight, received signal strength
DOI: 10.3233/AIS-150318
Journal: Journal of Ambient Intelligence and Smart Environments, vol. 7, no. 3, pp. 353-373, 2015
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl