Article (Scientific journals)
Edge Computing and Artificial Intelligence for Landslides Monitoring
El Moulat, Meryem; Debauche, Olivier; Mahmoudi, Said et al.
2020In Procedia Computer Science, 177, p. 480-487
Peer reviewed
 

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Keywords :
[en] early warning system; [en] Landslides susceptibility; [en] landslides monitoring; [en] Internet of Things; [en] Artificial Intelligence
Abstract :
[en] Landslides are phenomena widely present around the world and responsible each year of numerous life loss and extensive property damage. Researchers have developed various methodologies to identify area of high susceptibility of landslides. However, these methodologies cannot predict 'when' landslides are going to take place. Indeed, Wireless Sensors Network (WSN), Internet of Things (IoT) and Artificial Intelligence (AI) offer the possibility to monitor in real-time parameters causing the triggering factors of rapid landslides. In this paper, we suggest a real-time monitoring of landslides in order to precociously alert population in dangerous situation by means of a warning system. The novelty of this paper is the coupling of wireless sensors network and a multi-agent system deployed on an edge AI-IoT architecture by means of Kubernetes and Docker.
Disciplines :
Electrical & electronics engineering
Agriculture & agronomy
Author, co-author :
El Moulat, Meryem
Debauche, Olivier  ;  Université de Mons > Faculté Polytechnique > Service Informatique, Logiciel et Intelligence artificielle
Mahmoudi, Said  ;  Université de Mons > Faculté Polytechnique > Service Informatique, Logiciel et Intelligence artificielle
Mahmoudi, Sidi  ;  Université de Mons > Faculté Polytechnique > Service Informatique, Logiciel et Intelligence artificielle
Manneback, Pierre ;  Université de Mons > Faculté Polytechnique > Service Informatique, Logiciel et Intelligence artificielle
Lebeau, Frédéric
Language :
English
Title :
Edge Computing and Artificial Intelligence for Landslides Monitoring
Publication date :
12 November 2020
Journal title :
Procedia Computer Science
Publisher :
Elsevier, Amsterdam, Netherlands
Volume :
177
Pages :
480-487
Peer reviewed :
Peer reviewed
Research unit :
F114 - Informatique, Logiciel et Intelligence artificielle
Research institute :
R300 - Institut de Recherche en Technologies de l'Information et Sciences de l'Informatique
R450 - Institut NUMEDIART pour les Technologies des Arts Numériques
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