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Sensors 2017, 17(10), 2391; doi:10.3390/s17102391

An Improved Indoor Positioning System Using RGB-D Cameras and Wireless Networks for Use in Complex Environments

1
Departamento de Ingeniería de Software y Sistemas Informáticos, ETSI Informática, UNED, C/Juan del Rosal, 16, 28040 Madrid, Spain
2
School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Edinburgh EH14 4AS, UK
*
Author to whom correspondence should be addressed.
Received: 19 September 2017 / Revised: 10 October 2017 / Accepted: 16 October 2017 / Published: 20 October 2017
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Abstract

This work presents an Indoor Positioning System to estimate the location of people navigating in complex indoor environments. The developed technique combines WiFi Positioning Systems and depth maps, delivering promising results in complex inhabited environments, consisting of various connected rooms, where people are freely moving. This is a non-intrusive system in which personal information about subjects is not needed and, although RGB-D cameras are installed in the sensing area, users are only required to carry their smart-phones. In this article, the methods developed to combine the above-mentioned technologies and the experiments performed to test the system are detailed. The obtained results show a significant improvement in terms of accuracy and performance with respect to previous WiFi-based solutions as well as an extension in the range of operation. View Full-Text
Keywords: indoor positioning; WPS; RGB-D sensors; WiFi; fingerprinting; trajectory; skeletons; depth map; IPS; Kinect indoor positioning; WPS; RGB-D sensors; WiFi; fingerprinting; trajectory; skeletons; depth map; IPS; Kinect
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Duque Domingo, J.; Cerrada, C.; Valero, E.; Cerrada, J.A. An Improved Indoor Positioning System Using RGB-D Cameras and Wireless Networks for Use in Complex Environments. Sensors 2017, 17, 2391.

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