Edge Computing and Artificial Intelligence for Landslides Monitoring | Zendy

Meryem Elmoulat | Zendy; Olivier Debauche | Zendy; Saïd Mahmoudi | Zendy; Sidi Ahmed Mahmoudi | Zendy; Pierre Manneback | Zendy; Frédéric Lebeau | Zendy

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Edge Computing and Artificial Intelligence for Landslides Monitoring

Author(s) -

Meryem Elmoulat,

Olivier Debauche,

Saïd Mahmoudi,

Sidi Ahmed Mahmoudi,

Pierre Manneback,

Frédéric Lebeau

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.10.066

Subject(s) - landslide , computer science , enhanced data rates for gsm evolution , novelty , internet of things , property (philosophy) , wireless sensor network , warning system , the internet , wireless , population , computer security , artificial intelligence , telecommunications , computer network , world wide web , geology , seismology , philosophy , demography , theology , epistemology , sociology

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.

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