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NRC Publications Archive Archives des publications du CNRCFor the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous.A 3-D indoor location tracking and visualization system based on wireless sensor networks Bal, M.; Xue, H.; Shen, W.; Ghenniwa, H. The material in this document is covered by the provisions of the Copyright Act, by Canadian laws, policies, regulations and international agreements. Such provisions serve to identify the information source and, in specific instances, to prohibit reproduction of materials without written permission. For more information visit http://laws.justice.gc.ca/en/showtdm/cs/C-42Les renseignements dans ce document sont protégés par la Loi sur le droit d'auteur, par les lois, les politiques et les règlements du Canada et des accords internationaux. Ces dispositions permettent d'identifier la source de l'information et, dans certains cas, d'interdire la copie de documents sans permission écrite. Pour obtenir de plus amples renseignements : http://lois.justice.gc.ca/fr/showtdm/cs/C-42 Abstract-This paper describes a 3-D location tracking and visualization system using wireless sensor nodes in indoor environments. The system is based on a modified radio-location fingerprinting algorithm and it uses inexpensive, programmable wireless embedded platforms operating in a ZigBee wireless network protocol. The main emphasis of this study is on the ability to estimate the location of mobile wireless nodes in 3-D indoor spaces, without any costly infrastructure. The wireless nodes have been deployed in an experimental test bed, for location tracking and motion estimation. A K-nearest neighbor algorithm has been implemented for location estimation over a set of radio location fingerprints collected in a 3-D space. A 3-D visualization interface has been developed in VRML in order to display the real-time sensor positions and the data in the 3-D world. Preliminary experimental results show that the proposed scheme can achieve accurate and stable location tracking in indoor environments.