Abstract:
Multiple Radio Access Technology (multi-RAT) communication with Low Power WideArea Networks (LPWAN) significantly increases the flexibility of Internet of Things (IoT) applications.Location-based services that build upon such a multimodal communication architecture are ableto switch to an optimal localization method depending on the constraints of the active wirelesstechnology. Furthermore, the resulting location estimate can aid location-based handover mechanismsto reduce the energy consumption of a multi-RAT IoT device. In this research, we present our designof a multimodal localization framework and illustrate the benefit of such a framework with twoIoT use case examples. For the first use case, valuable artwork is tracked during transportation toa museum. In the second use case, we monitor the usage and location of large construction tools.Finally, we propose how our localization framework can be improved to deal with implementationchallenges and to reduce location estimation errors.

Authors:
Michiel Aernouts, Maarten Weyn, Rafael Berkvens – IDLab – Faculty of Applied Engineering, University of Antwerp – imec, 2000 Antwerp, Belgium
Filip Lemic, Jeroen Famaey – IDLab – Department of Computer Science, University of Antwerp – imec, 2000 Antwerp, Belgium
Jeroen Hoebeke, Bart Moons – IDLab—Department of Information Technology, University of Ghent – imec, 9000 Ghent, Belgium

Published in:
Sensors — Open Access Journal, 17 August, 2020

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A Multimodal Localization Framework Design for IoT Applications

Abstract:
Due to the limited bandwidth of Low-Power Wide-Area Networks (LPWAN), the application layer is currently often tied straight above the link layer, limiting the evolution of sensor networks distributed over a large area. Consequently, the highly efficient Static Context Header Compression (SCHC) standard was introduced, where devices can compress the IPv6 and upper layer protocols down to a single byte. This approach, however, assumes that every compression context is distributed before deployment, again limiting the evolution of such networks. Therefore, this paper presents two context registration mechanisms leveraging on the SCHC adaptation layer. This is done by analyzing current registration solutions in order to find limitations and optimizations with regard to very constrained networks. Both solutions and the current State-of-The-Art (SoTA) are evaluated in a Lightweight Machine to Machine (LwM2M) environment. In such situation, both developed solutions decrease the energy consumption already after 25 transmissions, compared with the current SoTA. Furthermore, simulations show that Long Range (LoRa) devices still have a 80% chance to successfully complete the registration flow in a network with a 50% Packet Error Ratio. Briefly, the work presented in this paper delivers bootstrapping tools to constrained, SCHC-enabled networks while still being able to reduce energy consumption.

Authors:
Bart Moons, Eli De Poorter, Jeroen Hoebeke

IDLab, Department of Applied Engineering,
University of Ghent— imec, 9056 Gent, Belgium

Published by:
MDPI – Publisher of peer-reviewed, open access journals
16 February 2021

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Device Discovery and Context Registration in Static Context Header Compression Networks