Indoor Localization Based on Neural Networks for Non-dedicated ZigBee Networks in AAL

Authors:
Rubén Blasco;Álvaro Marco;Roberto Casas;Alejando Ibarz;Victorián Coarasa;Ángel Asensio
Affiliations:
Tecnodiscap group, University of Zaragoza, Zaragoza, Spain 50018;Tecnodiscap group, University of Zaragoza, Zaragoza, Spain 50018;Tecnodiscap group, University of Zaragoza, Zaragoza, Spain 50018;Tecnodiscap group, University of Zaragoza, Zaragoza, Spain 50018;Tecnodiscap group, University of Zaragoza, Zaragoza, Spain 50018;Tecnodiscap group, University of Zaragoza, Zaragoza, Spain 50018
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

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Abstract

Indoor localization is one of the most appealing technologies in Ambient Assisted Living (AAL) applications, providing support for diverse services such as personal security, guidance or innovative interfaces. Dedicated systems can be deployed to provide that information, but it is possible to gain advantage of available elements to compute a location without requiring additional hardware. In this paper, a ZigBee network designed for a home control application is improved with a localization functionality based on neural networks, achieving room-level accuracy, and non introducing additional infrastructure constraints to the original application.