Application of Artificial Intelligence in Reactive Soil Research: A Scientometric Analysis

Abstract Reactive soils present significant challenges in geotechnical engineering due to their unpredictable behaviour, which can severely impact buildings and infrastructure. While artificial intelligence (AI) has been applied to improve numerical modelling of reactive soils, the scope of its application and future potential remains unclear. AI methods, such as neural networks, support vector machines, genetic algorithms, fuzzy logic, and image analysis, have shown promise in soil characterisation, strength prediction, performance evaluation, clay cracking analysis, and soil stabilisation. However, a systematic understanding of these advancements is lacking. This research addresses the gap by conducting a scientometric analysis using tools like VOSviewer®, Citespace®, and Sci2® to map scientific knowledge, identify trends, and uncover future opportunities. Findings suggest that integrating nanotechnology, real-time monitoring, multidisciplinary forecasting, and shared knowledge databases can enhance AI applications. This analysis provides a foundation for advancing AI-driven solutions in geotechnical engineering and addressing the challenges posed by reactive soils.