Chehri Abdellah et Fortier Paul. (2020). Wireless positioning and tracking for Internet of Things in heavy snow regions. Dans Alfred Zimmerman, Robert J. Howlett et Lakhmi C. Jain (dir.), Human centred intelligent systems. (p. 395-404). Smart Innovation, Systems and Technologies. Singapore : Springer.
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URL officielle: http://dx.doi.org/doi:10.1007/978-981-15-5784-2_32
Résumé
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.
| Type de document: | Chapitre de livre |
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| Date: | 30 Mai 2020 |
| Lieu de publication: | Singapore |
| Sujets: | Sciences naturelles et génie > Génie Sciences naturelles et génie > Génie > Génie informatique et génie logiciel Sciences naturelles et génie > Sciences appliquées |
| Département, module, service et unité de recherche: | Départements et modules > Département des sciences appliquées > Module d'ingénierie |
| Éditeurs: | Zimmerman, Alfred Howlett, Robert J. Jain, Lakhmi C. |
| Liens connexes: | |
| Mots-clés: | wireless sensor network, localization, snowy environment, linear least square, RMSE, maximum likelihood estimator, réseau de capteurs sans fil, localisation, environnement enneigé, moindres carrés linéaires, estimateur du maximum de vraisemblance, Proceedings |
| Déposé le: | 18 mai 2021 17:20 |
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| Dernière modification: | 18 mai 2021 17:20 |
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