IoT-based local landslide early warning system framework tested on unsaturated slope in Norway

Luca Piciullo & Vittoria Capobianco & Håkon Heyerdahl

27d ago· 9 min readenInsight

Summary

This paper presents a framework for an IoT-based local landslide early warning system (Lo-LEWS) applied to an unsaturated slope adjacent to a railway track in Eastern Norway. The study focuses on monitoring and modelling phases, using GeoStudio SEEP software to simulate hydrological behavior (volumetric water content and pore water pressure). Key findings include: (1) calibration of VWC profiles and consideration of climate/vegetation are crucial for accurate modeling; (2) the hydrological model effectively represents real conditions for up to 1 year before recalibration is needed; (3) a random forest machine learning model identified monitored VWC as the most important factor for forecasting the safety factor. The work represents a first step toward real-time IoT-based slope stability analysis for early warning systems.

Source

bskyIoT-based local landslide early warning system framework tested on unsaturated slope in Norwayideas.repec.org

Key quotes

· 5 pulled

A framework for a IoT-based local landslide early warning system (Lo-LEWS) has been proposed.

The results show that a preliminary calibration for matching the in situ VWC, as well as considering climate conditions and vegetation, are crucial aspects to model the response of the studied unsaturated slope.

The results show that the hydrological model can adequately represent the real monitored conditions up to a 1-year period, a recalibration is needed afterward.

A random forest model highlighted the importance of the monitored VWC for forecasting the FS.

The findings presented in this paper can be seen as a first step towards an Internet of Things (IoT)-based real-time slope stability analysis that can be employed as Lo-LEWS.

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A framework for a IoT-based local landslide early warning system (Lo-LEWS) has been proposed. Monitoring, modelling, forecasting and warning represent the main phases of the proposed framework. In this study, the first two phases have been applied to capt

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