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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/45615

Title: Sensor network and inertial positioning hybridisation for indoor location and tracking applications
Author(s): Álvarez López, Yuri
Álvarez Narciandi, Guillermo
Las Heras Andrés, Fernando Luis
Keywords: Internet of Things
Sensor networks
Issue date: 2017
Publisher: Inderscience (Geneva, SWITZERLAND)
Publisher version: http://dx.doi.org/10.1504/IJSNET.2017.085977
Citation: International Journal of Sensor Networks, 24(4), p. 242-252 (2017); doi:10.1504/IJSNET.2017.085977
Format extent: p. 242-252
Abstract: An indoor location system (ILS) for practical asset and people tracking in indoor scenarios using received signal strength (RSS) ZigBee-based sensor network and inertial sensors is presented. A novel algorithm that uses differential signal levels gathered from a set of transmitter nodes is developed for processing RSS data. These levels are introduced into a cost function whose minimum gives the asset location estimation. The use of differential field levels-based algorithm avoids the need of system calibration due to signal strength fluctuation. Moreover, position accuracy is improved by adding inertial sensor information. The method is tested in a real scenario, demonstrating practical indoor positioning when combining ZigBee-based sensor network and inertial sensors information. The influence of the number of ZigBee nodes on the position estimation accuracy has been analysed
URI: http://hdl.handle.net/10651/45615
ISSN: 1748-1287
Sponsored: This work has been supported by the ‘ministerio de Economía y Competitividad’ of Spain/European regional development fund (ERDF) under project TEC2014-54005-P (MIRIIEM) and by the ‘Gobierno del principado de asturias’, asturias (Spain), under project GRUPIN14-114
Project id.: MINECO/TEC2014-54005-P
Principado de Asturias/GRUPIN14-114
Appears in Collections:Artículos
Ingeniería Eléctrica, Electrónica, de Computadores y Sistemas
Investigaciones y Documentos OpenAIRE

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