Authors: Fabian Höflinger ; Joan Bordoy ; Rui Zhang ; Amir Bannoura ; Nikolas Simon ; Leonhard Reindl and Christian Schindelhauer

Affiliation: University of Freiburg, Germany

ISBN: 978-989-758-284-4

ISSN: 2184-4380

Keyword(s): Indoor Localization, Ultra-wideband, On-demand, Wake-up, Low Power.

Related Ontology Subjects/Areas/Topics: Applications and Uses ; Home Monitoring and Assisted Living Applications ; Sensor Networks

Abstract: In this paper we present a novel indoor localization system using external reference landmarks as a guidance system for emergency responders. The landmarks are based on low-power wake-up nodes which can be integrated into smoke detectors. The radio wake-up technology is equipped in the system to extend the lifetime of landmarks. While in sleep mode our landmarks have an overall power consumption of 66μW making them ready-to-use in case of an emergency for up to 5 years. The landmarks are small and cost-efficient and may be integrated into the building infrastructure. The positioning is achieved by combining the radio ranging and IMU based dead reckoning to overcome the disadvantages of both systems. The experimental results show that the proposed system is able to outperform both standalone systems and meanwhile maintain the low power consumption.

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Paper citation in several formats:
Höflinger, F.; Bordoy, J.; Zhang, R.; Bannoura, A.; Simon, N.; Reindl, L. and Schindelhauer, C. (2018). Localization System based on Ultra Low-power Radio Landmarks.In Proceedings of the 7th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-284-4, ISSN 2184-4380, pages 51-59. DOI: 10.5220/0006608800510059

author={Fabian Höflinger. and Joan Bordoy. and Rui Zhang. and Amir Bannoura. and Nikolas Simon. and Leonhard Reindl. and Christian Schindelhauer.},
title={Localization System based on Ultra Low-power Radio Landmarks},
booktitle={Proceedings of the 7th International Conference on Sensor Networks - Volume 1: SENSORNETS,},


JO - Proceedings of the 7th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Localization System based on Ultra Low-power Radio Landmarks
SN - 978-989-758-284-4
AU - Höflinger, F.
AU - Bordoy, J.
AU - Zhang, R.
AU - Bannoura, A.
AU - Simon, N.
AU - Reindl, L.
AU - Schindelhauer, C.
PY - 2018
SP - 51
EP - 59
DO - 10.5220/0006608800510059

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