A case-based approach for indoor location
Pages 78 - 90
Abstract
Location is an important dimension for context-awareness in ubiquitous devices. Nowadays different techniques are used alone or together to determine the position of a person or object. One aspect of the problem concerns to indoor location. Various authors propose the analysis of Radio Frequency (RF) footprints.
In this paper we defend that case-based reasoning can make an important contribution for location from RF footprints. We apply an empirical dissimilarity metric for footprint retrieval and compare this approach with the results obtained with a neural network and C5.0 learning algorithms.
The RF footprints are obtained from a Global System for Mobile Communications and General Packet Radio Service (GSM/GPRS) network. Signals from these networks are particularly complex when compared to the ones obtained from WiFi or Bluetooth networks.
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- Kaidara Software
- Naval Research Laboratory: Naval Research Laboratory
- PricewaterhouseCoopers: PricewaterhouseCoopers
- empolis GmbH: empolis GmbH
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- AAAI: American Association for Artificial Intelligence
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Springer-Verlag
Berlin, Heidelberg
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Published: 23 August 2005
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