The evolution of the construction industry is associated with the continuous implementation of new technologies. Building Information Modelling (BIM) has revolutionised the collaboration and data sharing processes in the architecture, engineering, and construction (AEC) industry. However, it needs to be supported by new technologies that can embrace digital construction by transforming the construction industry into a dynamic environment. There is a lack of understanding of the cutting-edge technologies that have emerged to help with the digital transformation of the construction industry. There is a need to understand all these technologies and how they can be leveraged holistically towards future BIM innovations. Therefore, this article conducts a literature review to evaluate how targeted cutting-edge technologies can be utilised to release the full potential of BIM from a technical perspective. A bibliometric analysis focusing on the co-occurrence of keywords related to various technologies, their links with BIM, and their related research themes was conducted based on the Web of Science (WoS) database holdings from 2010 to 2019. The findings demonstrate that one type of technology can help with solving a specific issue. However, using one technology alone does not solve an issue entirely. The current technology has been utilised independently and not as a coherent system. Thus, a weak information integration and management approach can restrict the leveraging of a smart BIM environment. This paper is not meant to be exclusive. Many new technologies, concepts, and ideas can be added to help realise BIM potentials that are not covered in this study. Furthermore, the analysis was based on the dataset retrieved from WoS and only included the literature in English. Based on those findings, the authors indicated a technology fusion to support BIM development.

Structure health inspection is the way to ensure that structures stay in optimum condition. Traditional inspection work has many disadvantages in dealing with the large workload despite using remote image-capturing devices. This research focuses on image-based concrete crack pattern recognition utilizing a deep convolutional neural network (DCNN) and an encoder–decoder module for semantic segmentation and classification tasks, thereby lightening the inspectors’ workload. To achieve this, a series of contrast experiments have been implemented. The results show that the proposed deep-learning network has competitive semantic segmentation accuracy (91.62%) and over-performs compared with other crack detection studies. This proposed advanced DCNN is split into multiple modules, including atrous convolution (AS), atrous spatial pyramid pooling (ASPP), a modified encoder–decoder module, and depthwise separable convolution (DSC). The advancement is that those modules are well-selected for this task and modified based on their characteristics and functions, exploiting their superiority to achieve robust and accurate detection globally. This application improved the overall performance of detection and can be implemented in industrial practices.

Sustainable building design has become a hot topic over the past decades. Many standards, databases, and tools have been developed for achieving a sustainable building. Not until recently have the importance of structural engineering and its contribution to sustainable building design been full recognised. However, due to the highly fragmented and diversity of knowledge across building and infrastructure domains, there is a lack of approach that can address all the sustainable issues within the structural design. This paper reviews the sustainable design from the perspective of structural engineering: (1) reviewing the current situation; (2) identifying the gaps and difficulties; and (3) making recommendations for future improvements. The strategies and indicators, as well as BIM‐enabled methodology, for sustainable structural design (SSD) are also discussed in a holistic way. The results of this investigation show that most of the methods are not doing well in terms of delivering a successful sustainable structural design. It is expected that the future BIM could probably provide such a platform to address these issues.

Knowledge management in construction health and safety is an intensive process involving different stakeholders. However, this domain’s information is still fragmented and stored in various disordered formats that require systematic structure for reusing and sharing. This study aims to develop a domain ontology, HSM-Onto (Health and Safety Management-Ontology), to construct health and safety knowledge and improve health and safety management decision making. The HSM-Onto could implement the organization, storage and reuse of construction health and safety knowledge. It comprises two primary domain knowledge contexts, including construction project context and risk context. Based on the conducted analyses, the findings show that the HSM-Onto’s health and safety knowledge sharing is effective and equips health and safety employees with sound recommendations for decision making.

Public-private partnerships (PPPs) have proliferated and adapted to public development in recent decades; within it, the value for money (VfM) assessment defines the feasibility of the project procurement model as one of the essential components of PPP. However, evaluating the VfM in PPPs remains problematic. Given concerns about PPP profitability, a more integrated VfM evaluation is urgently needed to manage multiple indicators along the project lifecycle. Building information management (BIM), popular in architecture, engineering, and construction, provides resources that could support the VfM to a great extent. This paper uses a review approach to identify the current issues that are affecting VfM assessments and suggests that BIM, functioning throughout the PPP lifecycle, could support decision-making in VfM processes in order to satisfy service targets.