Guest Editors: Hong-Hu Zhu, Ankit Garg, Xiong (Bill) Yu, Hannah Wan-Huan Zhou

 

For efficient construction and maintenance of geotechnical infrastructures (slopes, tunnels, pipelines and other ground infrastructures), there is a need to access and examine measured data in real time for further decision making. Over the last decade, the application of Internet of Things (IoT) and Artificial Intelligence (AI) has increased rapidly to enhance automation in various industries such as manufacturing, healthcare and construction. Unfortunately, less studies are available that focus on the application of IoT and AI to geotechnical engineering both in field and at laboratory scales. Data collection, data transmission, data management and data analysis are essential for analyzing serviceability or stability of geotechnical infrastructures. Furthermore, variation in data type due to usage of UAV photogrammetric sensors, LiDAR and fiber optic sensing techniques makes data management and analysis more complicated. There is an urgent need to automate process of collecting, integrating and analyzing data from different types of sensors for further decision making. Moreover, advanced artificial intelligence, metaheuristic optimization, and data-science can be reliable methods for geotechnical engineering for exploration, risk assessment, construction, design, and maintenance at a higher level.

 

In addition to research, IoT has been applied very extensively to improve education and learning environment. The purpose of IoT is to connect physical phenomenon as well as mathematics and virtual worlds (Internet, Computers and Mobile devices) with an aim to create an immersive learning environment.

 

This Special Issue in 2023 invites you to share recent developments and advances in IoT techniques and its application in geotechnical engineering infrastructure. Authors are encouraged to share case studies and laboratory-scale investigations. Further, any development of laboratory-based workshop for enhanced learning in geotechnical underground engineering problems through IoT is welcome. 

 

We kindly invite you to contribute new and original researches to this Special Issue, attributing at least one of below topics:

 

• Sensors and intelligent methods for geotechnical engineering infrastructure
• Development of real-time monitoring, early failure systems, and risk assessment for geotechnical engineering infrastructure
• Applications of AI in geotechnical engineering
• Interface development (APP, web-based interface) in geotechnical engineering
• Real-life case studies of applied sensors, geospatial data science, and intelligence techniques in geotechnical engineering
• Case studies on application of IoT in geotechnical engineering
• Education and learning in geotechnical engineering using IoT
• Authors are encouraged to share data and codes for considering the reproducibility of their works as well as future improvements of research.
• Any other application of IoT in geotechnical engineering.

 

It may be noted that all papers will be reviewed through a peer review process as per the JRMGE policy and guidelines. JRMGE is indexed by several indexing agencies, including SCIE, SCOPUS and CSCD (Chinese Science Citation Database) and has Impact factor of 2.829.

 

Journal Pages:

http://www.jrmge.cn

and

https://www.journals.elsevier.com/journal-of-rock-mechanics-and-geotechnical-engineering

 

During submission, please click the button ‘’IoT and AI” of the Special Issue.

 Submission deadline: 31 December 2021

 

Guest Editors

 

1. Hong-Hu Zhu, Ph.D., Professor

School of Earth Sciences and Engineering, Nanjing University, Nanjing, China

Email: zhh@nju.edu.cn

 

2. Ankit Garg, Ph.D., Associate Professor

Department of Civil and Environmental Engineering, Shantou University, China

Foreign Specialist, L.N Gumilyov Eurasian National University, Kazakhstan

Email: ankit@stu.edu.cn

 

3. Xiong (Bill) Yu, Ph.D., P.E., Fellow ASCE, Interim Chair and Frank H. Neff Professor

Department of Civil and Environmental Engineering, Case Western Reserve University, USA

Email: xxy21@case.edu

 

4. Hannah Wan-Huan Zhou, Ph.D., Associate Professor and Head of Department

Department of Civil and Environmental Engineering, University of Macau, Macau, China

Email: hannahzhou@um.edu.mo