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Wireless In the Woods: Monitoring the Snow Melt Process in the Sierra Nevada (en Anglais) | |||
Droits : © Inria Paris - Rocquencourt Auteur(s) : WATTEYNE Thomas 03-09-2015 Description : Historically, the study of mountain hydrology and the water cycle has been largely observational, with meteorological forcing and hydrological variables extrapolated from a few infrequent manual measurements. Recent developments in IoT technology are revolutionizing the field of mountain hydrology. Low-power wireless networks can now generate denser data in real-time and for a fraction of the cost of labor-intensive manual measurement campaigns. The American River Hydrological Observatory (ARHO) project has deployed thirteen low-power wireless IoT networks throughout the American River Basin to monitor the melting process of California's snowpack. The networks feature a total of 945 environmental sensors, each reporting a reading every 15 min. The data reported is available online to the scientific community minutes after it was generated. This presentation will give you an in-depth overview of the ARHO project. We will detail the different requirements and technical options, describe the technology deployed today, and discuss the challenges associated with large-scale environmental monitoring in extreme conditions. This work is done as part of the REALMS associate team between the Inria EVA team, Prof. Glaser's team at UC Berkeley and Prof. Kerkez' team at the University of Michigan. Mots-clés libres : montagne,hydrologie,internet des objets,surveillance de l'environnement,réseau de capteurs sans fil | TECHNIQUE Type : image en mouvement Format : video/x-flv Source(s) : rtmpt://fms2.cerimes.fr:80/vod/fuscia/wireless.in.the.woods.monitoring.the.snow.melt.process.in.the.sierra.nevada_18818/demie_heure_de_science_03092015_t_watteyne.mp4 | ||
Entrepôt d'origine : Canal-u.fr Identifiant : oai:canal-u.fr:18818 Type de ressource : Ressource documentaire |
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Wireless In the Woods: Monitoring the Snow Melt Process in the Sierra Nevada (en Anglais) | |||||||
Identifiant de la fiche : 18818 Schéma de la métadonnée : LOMv1.0, LOMFRv1.0 Droits : libre de droits, gratuit Droits réservés à l'éditeur et aux auteurs© Inria Paris - Rocquencourt Auteur(s) : WATTEYNE THOMAS Éditeur(s) : INRIA (Institut national de recherche en informatique et automatique) 03-09-2015 Description : Historically, the study of mountain hydrology and the water cycle has been largely observational, with meteorological forcing and hydrological variables extrapolated from a few infrequent manual measurements. Recent developments in IoT technology are revolutionizing the field of mountain hydrology. Low-power wireless networks can now generate denser data in real-time and for a fraction of the cost of labor-intensive manual measurement campaigns. The American River Hydrological Observatory (ARHO) project has deployed thirteen low-power wireless IoT networks throughout the American River Basin to monitor the melting process of California's snowpack. The networks feature a total of 945 environmental sensors, each reporting a reading every 15 min. The data reported is available online to the scientific community minutes after it was generated. This presentation will give you an in-depth overview of the ARHO project. We will detail the different requirements and technical options, describe the technology deployed today, and discuss the challenges associated with large-scale environmental monitoring in extreme conditions. This work is done as part of the REALMS associate team between the Inria EVA team, Prof. Glaser's team at UC Berkeley and Prof. Kerkez' team at the University of Michigan. Mots-clés libres : montagne, hydrologie, internet des objets, surveillance de l'environnement, réseau de capteurs sans fil
| PEDAGOGIQUE Type pédagogique : cours / présentation Niveau : master, doctorat TECHNIQUE Type de contenu : image en mouvement Format : video/x-flv Taille : 2.21 Go Durée d'exécution : 40 minutes 11 secondes RELATIONS Cette ressource fait partie de : | ||||||
Entrepôt d'origine : Canal-u.fr Identifiant : oai:canal-u.fr:18818 Type de ressource : Ressource pédagogique |
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