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Wireless Positioning and Tracking for Internet of Things in Heavy Snow Regions

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Human Centred Intelligent Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 189))

Abstract

The adaptation of localization in a real-world environment can be observed by popular commercial and non-commercial GPS applications. However, with the advent of the Internet of Things (IoT), wireless sensor networks (WSNs), these problems are again brought into focus. The requirements, such as low-cost, nodal resource, and multihop characteristics, have made difficult problems such as localization. WSNs in snowy environments can support a wide range of applications such as environmental monitoring, the rescue of snow avalanche and winter sports activities. All these applications require knowing the position of the nodes to process the event. Of course, the obvious solution to equip all nodes with a GPS module is extremely expensive and is subject to many constraints. Besides, the node position estimation is most often influenced by measurement errors. These errors depend on the nature of the environmental media in which the sensors are deployed. In this paper, the problem of node localization at 2.425 GHz in icy and snowy environments is investigated.

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Author information

Authors and Affiliations

  1. Department of Applied Sciences, University of Québec, Chicoutimi, QC, G7H 2B1, Canada

    Abdellah Chehri

  2. Department of Electrical and Computer Engineering, Laval University, Québec City, QC, G1V 0A6, Canada

    Paul Fortier

Authors
  1. Abdellah Chehri
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  2. Paul Fortier
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Corresponding author

Correspondence to Abdellah Chehri .

Editor information

Editors and Affiliations

  1. Faculty of Informatics, Reutlingen University, Reutlingen, Baden-Württemberg, Germany

    Alfred Zimmermann

  2. KES International and Bournemouth University, Shoreham-by-sea, UK

    Robert J. Howlett

  3. University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

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Chehri, A., Fortier, P. (2021). Wireless Positioning and Tracking for Internet of Things in Heavy Snow Regions. In: Zimmermann, A., Howlett, R., Jain, L. (eds) Human Centred Intelligent Systems. Smart Innovation, Systems and Technologies, vol 189. Springer, Singapore. https://doi.org/10.1007/978-981-15-5784-2_32

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