Emerging Artificial Intelligence tools in Geotechnical Engineering Advancements

Geotechnical engineering has experienced transformative growth over the past decades, influenced significantly by technological innovations and collaborations across disciplines. A key revolutionary force within this field has been the integration of artificial intelligence (AI), which has reshaped traditional methodologies and enhanced the analysis and management of complex geotechnical challenges. These challenges range from soil mechanics and foundation engineering to slope stability and site characterization, all of which benefit immensely from AI-driven approaches.

This Research Topic is designed to highlight cutting-edge research, innovative methodologies, and practical applications that merge AI with geotechnical engineering. By employing AI technologies such as machine learning, deep learning, evolutionary algorithms, and data analytics, this field has seen a leap in the capability to address geotechnical issues with enhanced precision, efficiency, and reliability. The goal is not only to showcase these advances but also to spur further integration of AI in tackling geotechnical problems.

To foster a comprehensive understanding and encourage continued innovation in this field, this Research Topic welcomes contributions on a diverse array of themes, including but not limited to:

● AI algorithms for predictive modeling of soil behavior and geotechnical parameters.
● Automated site characterization using AI to analyze data from field investigations.
● AI-driven risk assessment methods for addressing geotechnical hazards like landslides and liquefaction.
● Use of AI in optimizing the design and development of geotechnical structures.
● Development of AI-based decision support systems for enhancing project planning and management in geotechnical engineering.

Our aim with this collection is to enhance dialogue and collaboration amongst academicians, practicing engineers, and industry leaders at the AI-geotechnical engineering interface. We seek to provide a platform that facilitates the exchange of insights, experiences, and best practices, thereby fostering the broader adoption and effectiveness of AI technologies in enhancing infrastructure resilience and safety globally.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Keywords: AI Algorithms, AI-geotechnical Engineering

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.