International Conference on Mobile Systems and Pervasive Computing ( MobiSPC 2018 ) Monitoring System Using Internet of Things For Potential Landslides

Abstract The North-Western RIF of Morocco is considered as one of the most mountainous zone in the Middle East and North Africa. This area is more serious in the corridor faults region, where the recent reactivation of those tectonic layering may greatly contribute to the triggering of landslides. The consequences of this phenomenon can be enormous property damage and human casualties. Furthermore, this disaster can disrupt progress and destroy developmental efforts of government, and often pushing nations back by many years. In our previous works of Tetouan-Ras-Mazari region, we identified the areas that are prone to landslides by different methods like Weights of Evidence (WofE) and Logistic Regression (LR). In fact, these zones are built and susceptible. Undoubtedly, the challenge to save human lives is vital. For this reason, we develop a robust monitoring model as part of an alert system to evacuate populations in case of imminent danger risks. This model is ground-based remote monitoring system consist of more than just field sensors; they employ data acquisition units to record sensor measurements, automated data processing, and display of current conditions usually via the Internet of Things (IoT). To sum up, this paper outlines a new approach of monitoring to detect when hillslopes are primed for sliding and can provide early indications of rapid and catastrophic movement. It reports also continuous information from up-to-the-minute or real-time monitoring, provides prompt notification of landslide activities, advances our understanding of landslide behaviors, and enables more effective engineering and planning efforts.

[1]  Lionel Benoit,et al.  Monitoring landslide displacements with the Geocube wireless network of low-cost GPS , 2015 .

[2]  Shigeru Takayama,et al.  Wireless sensor network in landslide monitoring system with remote data management , 2018 .

[3]  L. Ait Brahim,et al.  Application Of Logistic Regression Method To Produce Landslide Susceptibility Map: A Case Study Of Tetouan Mazari, Morocco , 2018 .

[4]  Arnold K. Bregt,et al.  Do landslides follow landslides , 2016 .

[5]  D. Varnes SLOPE MOVEMENT TYPES AND PROCESSES , 1978 .

[6]  Michel JaboyedoffThierry Use of LIDAR in landslide investigations: a review , 2012 .

[7]  Olivier Debauche,et al.  Web-based cattle behavior service for researchers based on the smartphone inertial central , 2017, FNC/MobiSPC.

[8]  Olivier Debauche,et al.  Web Monitoring of Bee Health for Researchers and Beekeepers Based on the Internet of Things , 2018, ANT/SEIT.

[9]  M. Rossi,et al.  Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory , 2017, Landslides.

[10]  D. Alexander On the causes of landslides: Human activities, perception, and natural processes , 1992 .

[11]  Jason W. Kean,et al.  Real-time monitoring of landslides , 2012 .

[12]  Olivier Maquaire,et al.  The use of Global Positioning System techniques for the continuous monitoring of landslides: application to the Super-Sauze earthflow (Alpes-de-Haute-Provence, France) , 2002 .

[13]  Meryem Elmoulat,et al.  Landslides susceptibility mapping using GIS and weights of evidence model in Tetouan-Ras-Mazari area (Northern Morocco) , 2018 .

[14]  Sidi Ahmed Mahmoudi,et al.  Cloud architecture for digital phenotyping and automation , 2017, 2017 3rd International Conference of Cloud Computing Technologies and Applications (CloudTech).

[15]  L. Bryson,et al.  Assessment of active landslides using field electrical measurements. , 2018 .

[16]  Meryem El Moulat,et al.  A linear indexing approach to mass movements susceptibility mapping. The case of the Chefchaouen province (Morocco) , 2015, Rev. Int. Géomatique.

[17]  Manuel Díaz,et al.  State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing , 2016, J. Netw. Comput. Appl..

[18]  Jean-Philippe Malet,et al.  Image-based correlation of Laser Scanning point cloud time series for landslide monitoring , 2014, Int. J. Appl. Earth Obs. Geoinformation.

[19]  Olivier Debauche,et al.  Cloud services integration for farm animals’ behavior studies based on smartphones as activity sensors , 2019, J. Ambient Intell. Humaniz. Comput..

[20]  Olivier Debauche,et al.  Irrigation pivot-center connected at low cost for the reduction of crop water requirements , 2018, 2018 International Conference on Advanced Communication Technologies and Networking (CommNet).