1st Edition

Applications of AI and IoT in Geotechnical Engineering for Sustainable Infrastructure

368 Pages 132 B/W Illustrations
by CRC Press

Artificial Intelligence (AI) and the Internet of Things (IoT) are transforming the way geotechnical engineers monitor, analyze, and manage soil-structure systems. Applications of AI and IoT in Geotechnical Engineering for Sustainable Infrastructure explores how these emerging digital technologies can enhance decision-making, improve infrastructure resilience, and support sustainable development... Read more

Chapter 1: A Review on Integration of AI and IoT in Geotechnical Engineering

Govindarajan Kannan and Evangelin Ramani Sujatha

 

Chapter 2: Enhancing Resilience of Geotechnical Structures with AI and IoT

Rashma R S V

 

Chapter 3: AI-Based Soil Classification and Characterization: Techniques and Case Studies

Ifeyinwa Ijeoma Obianyo, Frank Nnebe, Gloria Nkeiruka Matthew, Abubakar Dayyabu, Abdulhameed Danjuma Mambo, andAzikiwe Peter Onwualu

 

Chapter 4: Harnessing Artificial Intelligence Techniques for Prediction of Compaction Parameters of Soil

Utkarsh, Pradeep Kumar Jain, Kaustav Chatterjee, and Sudhir Bhatt

 

Chapter 5: Application of Data-Driven Techniques for Prediction of Soil Water Characteristics Curve: A State-of- the-Art Review

Mohak Desai and Kaustav Chatterjee

 

Chapter 6: AI-Driven Prediction Models for Geotechnical Failures: Models and Real-World Case Studies

V. Murugesh

 

Chapter 7: AI and Machine Learning Approaches for Predicting Geotechnical Failures in Civil Infrastructure

Shital Marlapalle, Ravindra Budania, and Vedprakash maralapalle

 

Chapter 8: Surrogate Modelling and Reliability Analysis for Complex Geotechnical Systems Using AI

Kumar Harsh, Kumar Shubham, KVNS Raviteja, and Abdhesh Kumar Sinha

 

Chapter 9: Development and Application of an MR Model for Slope Stability Assessment: A Case Study on the Jorabat–Shillong Expressway

Balendra Mouli Marrapu and Ippili Saikrishnamacharyulu

 

Chapter 10: Identification of Landslide Susceptibility Areas in Pettimudi Hills Using Frequency Ratio and Logistic Regression Models

Surendar Natarajan and Kamalanandhini Mohan

 

Chapter 11: AI and IoT-Driven Prediction Models for Stone Column Performance under Liquefaction

Priyanka Ahirwar and Pradeep Kumar Jain

 

Chapter 12: Development of Mobile Application for Calculating the Bearing Capacity of a Pile

Rakesh Kumar Dutta, Tammineni Gnananandarao, Amit Kumar, and V. Gayathri

 

Chapter 13: Sustainable Earthwork Practices through AI Optimization

Asiqur Rahman Abir, Rayhan A. Shium, and Md Fahim Faisal Tanha

 

Chapter 14: Optimizing Earthwork Operations for Sustainable Infrastructure Using AI Techniques

Chatrabhuj and Kundan Meshram

 

Chapter 15: Earthquakes in the Age of AI: Redefining Risk, Resilience, and Responsibility

Shima Al-Balushi, Anas Ansari, and Abdullah Ansari

 

Chapter 16: Seismic Data Analysis for Tsunamigenic Earthquake Detection Using Soft Computing Techniques

Tammineni Gnananandarao, CH. Ajay, B.A.V. Ram Kumar, Hemanth Kumar Yerrabolu, and J. Y. V. Shiva Bhushan

 

Chapter 17: Application of Non-Parametric Machine Learning Models in estimating Penetration Rate of Tunnel Boring Machines

Shreyas S K and Arindam Dey

 

Chapter 18: Real-time Monitoring and Health Assessment of Pile Foundations Using IoT and AI Technologies

Shital Marlapalle, Ravindra Budania, and Vedprakash Maralapalle

Biography

Vedprakash C. Maralapalle is an Associate Professor at the L. S. Raheja School of Architecture, Mumbai, India. He holds a Ph.D. in Civil Engineering from NMIMS University, Mumbai, with research focused on the physical modelling and numerical analysis of vertical piles.His research interests include geotechnical engineering, pile foundations, physical and centrifuge modelling, numerical analysis using advanced software tools, artificial intelligence applications in civil engineering, smart infrastructure systems, and sustainable urban development.

Jayatheja Muktinutalapati is a researcher and academician in the domain of civil engineering. He holds a Ph.D. in civil engineering from Birla Institute of Technology and Science (BITS) - Pilani, and master’s degree in geotechnical engineering from Jawaharlal Nehru Technological University Hyderabad (JNTUH). He is currently working as an Assistant Professor in the RICS School of Built Environment, Amity University Maharashtra, Mumbai. His areas of research include recyclable materials, retaining structures, life cycle assessments, and AI applications in civil engineering.

Bogireddy Chandra is currently a Foreign Scientist at the ALT University in Almaty, Kazakhstan, and a Visiting Scholar in the Department of Civil and Intelligent Construction Engineering at Shantou University in China. Dr. Bogireddy's areas of research interest includes basic geomechanics, numerical modeling, image analysis, site characterization, earthquake engineering, biogeotechnology, sustainable and carbon reduction ground engineering (MICP, Biochar), consolidation, pipeline geotechnical engineering, and the study of atmospheric aerosols in geo-environmental systems.

Gangadhara Reddy Narala is an academician and researcher in Civil Engineering with a specialization in Geotechnical Engineering. He holds a Ph.D. in Civil Engineering from the IIT Bhubaneswar and a Master’s degree in Geotechnical Engineering from the NIT Bhopal. He is currently serving as an Assistant Professor at the Fiji National University, Suva, Fiji. His research interests lie in geotechnical and geoenvironmental engineering, particularly the beneficial utilization of industrial waste materials, pavement geotechnics, climate-resilient infrastructure, sustainable soil stabilization, the application of biopolymers and biochar in landfill engineering, slope stabilization, and climate change adaptation.

Abdullah Ansari currently serves as a Research Professor at the Earthquake Monitoring Center (EMC), Sultan Qaboos University, Muscat, Oman. His research focuses on seismic risk assessment, geotechnical earthquake engineering, tunnel and underground structure performance, and infrastructure resilience under multi-hazard conditions. He has extensive experience in developing analytical, numerical, and data-driven models for evaluating the seismic vulnerability of critical infrastructure systems. A key aspect of his research involves integrating artificial intelligence and machine learning techniques with traditional geotechnical engineering approaches to improve the prediction of seismic damage and infrastructure performance.