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.
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Osterloh MartinMartin 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 a. Bestandsnummer des Verkäufers 4976454
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9783639310924
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