Towards smart cities: Predicting soil liquefaction risk using artificial intelligence

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Towards smart cities: Predicting soil liquefaction risk using artificial intelligence
EngineeringEngineering And ConstructionLandslides
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Soil liquefaction that results in infrastructure damage has long been a point of contention for urban planners and engineers. Accurately predicting the soil liquefaction risk of a region could help overcome this challenge.

Accordingly, researchers applied artificial intelligence to generate soil liquefaction risk maps, superseding already published risk maps.

Soil liquefaction is an example of a natural hazard where saturated soil substantially loses strength and stiffness in response to stress, typically due to earthquake-related shaking or other rapid loading. This process causes the soil to behave like a liquid, reducing its ability to support infrastructure. Overcoming challenges such as soil liquefaction is, thus, the need of the hour.

Notably, the developed model used a combination of machine learning model -- such as artificial neural networks and gradient-boosting decision trees -- to improve the accuracy in predicting soil liquefaction risk. The researchers achieved high accuracy in predicting soil classifications and N-values . They validated the effectiveness of the model against extensive geotechnical survey data.

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