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Enhancing Indoor Localization with Proximity Information in WSN

A novel way of enhancing indoor localization in wireless sensor networks - .
Book on DemandKartoniert, Paperback
100 Seiten
Englisch
VDM Verlag Dr. Müllererschienen am12.12.2010
Several studies have pointed out that RSS-based localization methods for indoor environments are inaccurate and faulty. In my work, I hypothesize that RSS-based localization can be enhanced by utilizing proximity information. Instead of considering solely the radio-signals of the item of interest, we also consider the signals of nearby items to enhance localization. Therefore, a information fusion algorithn was developed. In order to test my hypothesis, I developed an infrastructure to collect data from sensors equipped with a CC2420 radio interface.mehr

Produkt

KlappentextSeveral studies have pointed out that RSS-based localization methods for indoor environments are inaccurate and faulty. In my work, I hypothesize that RSS-based localization can be enhanced by utilizing proximity information. Instead of considering solely the radio-signals of the item of interest, we also consider the signals of nearby items to enhance localization. Therefore, a information fusion algorithn was developed. In order to test my hypothesis, I developed an infrastructure to collect data from sensors equipped with a CC2420 radio interface.
Details
ISBN/GTIN978-3-639-31092-4
ProduktartBook on Demand
EinbandartKartoniert, Paperback
Erscheinungsjahr2010
Erscheinungsdatum12.12.2010
Seiten100 Seiten
SpracheEnglisch
Gewicht150 g
Artikel-Nr.10267081

Autor

Martin Osterloh was born in 1985 in Muehlhausen, Germany. He received his Diploma (M. Sc.) in Computer Science in October 2010 from Ilmenau, University of Technology. His main interests are wireless sensor networks and their arising challenges. He is working since 2009 for the Digital Enterprise Research Institute in Galway, Ireland.