Smart Infrastructure and Construction (SMIC) journal is focused on the physical infrastructure assets and the construction processes where the integrate digital technologies are integrated. The topics covered by the SMIC journal are the following (but not limited to):
advanced materials;
structural health monitoring relevant to civil infrastructures;
intelligent and integrated digital delivery systems in; infrastructure and construction;
three-dimensional (3D)-printed materials and additive manufacturing techniques;
computer-aided structural integrity; and
digital twins.
The objective of this journal is to contribute to the theoretical and practical principles, adaptive technologies, and advanced solutions that facilitate the construction and management of smarter and more environmentally friendly infrastructures.
SMIC is abstracted and indexed in various databases, such as Scopus, Journal Citation Reports, COPE, DORA, CNKI, Compendex Engineering Village, and IET Inspec. The journal publishes one volume per year comprising four issues. The co-editors-in-chief invite leading researchers, university professors, designers, and consultants to submit proposals for themed issues that address key challenges and trends related to the scope of the SMIC journal.
Concerning the issue on the 30th EG-ICE: International Conference on Intelligent Computing in Engineering, was held from 4th to 7th July at University College London, UK, was intended to focus on the following topics: life-cycle support; advanced computing in engineering; automation and robotics; building information modelling (BIM) and engineering ontologies; monitoring and control algorithms in engineering; computer-supported construction management; engineering optimisation and search; and, enhancing sustainability and resilience.
The first paper (Hu et al., 2025) proposed a semantic web-based method to enhance the reasoning of crane monitoring data, validated through laboratory experiments. The transient crane behaviours, during a 242.7-s lifting operation, were accurately detected with an average error of 0.32 s. All recognised lifts were successfully matched to the six lifting orders. According to the authors, the results of this study were expected to advance crane lifting monitoring and management practices, leading to increased crane utilisation and project performance.
In the second paper (Xie et al., 2025) explored the concept and application of DT in the field of HR, given that there are currently a limited number of reviews on this topic. In this study, the authors found that most studies in this area show promising results. However, it is still considered exploratory. The authors suggest that future studies could experiment with the application of DT frameworks with higher levels of maturity.
In the third paper (Ying et al., 2025) suggested a semi-automated approach by the transformation of 3D point cloud data of bridges into accurate and editable computer-aided design (CAD) drawings, achieving high accuracy in mapping essential bridge components, accurately regularising and delineating key structural features such as supports and deck structures. The proposed methodology is also used to update finite element (FE) models of bridges, enabling more advanced structural analyses and proactive maintenance protocols. Combining automated CAD modelling with FE model refinement provides a new methodology for streamlining the assessment and preservation of bridge infrastructure.
In the fourth paper (Oyeyipo et al., 2025) assessed the Nigerian construction industry and identified impediments to the adoption of AR and VR to increase safety on construction sites. The impediments to the adoption of AR and VR were identified and classified to improve safety and accident prevention in the Nigerian construction industry. The authors also proposed recommendations for achieving a safer construction industry.
In the latest paper (Sivakumar et al., 2025), Sivakumar et al. (2025) proposed an integrated approach that combines BIM, providing detailed 3D models of drainage infrastructure, and geographic information systems, providing a geospatial context, to increase the efficiency and resilience of stormwater network planning. This methodology was developed and applied to a selected urban district in Chennai.
Co-editors-in-chief and associate editors of the Smart Infrastructure and Construction (SMIC) journal would like to express their sincere gratitude to the guest editor, the authors, the reviewers, and other contributors who contributed to this themed issue. In addition, editorial staff extend a special thank you to the ICE Publishing and Emerald staff for their dedicated effort in preparing this themed issue.
