An operational IoT-based slope stability forecast using a digital twin

The Hut  published an innovative paper titled “An operational IoT-based slope stability forecast using a digital twin,” authored by Luca Piciullo, Minu Treesa Abraham, Ida Norderhaug Drøsdal, and Erling Singstad Paulsen. This pioneering study explores how the integration of Internet of Things (IoT) sensors with digital twin models can provide real-time, accurate predictions of slope stability, offering new tools for disaster prevention and infrastructure safety.

Highlights from the paper:

•An automated IoT-based real-time slope stability analysis is developed.
•Real-time hydrological monitoring, modelling and data-driven approaches are integrated for slope stability forecasting.
•Polynomial regression and Random Forest model are trained with daily hydro, weather, vegetation data to forecast the stability.
•The system forecasts the slope stability in real-time for the rolling three days.
•A daily web service is fetching data, running three-day forecasts, and visualizing results in real-time.

Find the full paper published here.

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