Ibukun Awolusi

The construction industry continues to experience high rates of serious injury and fatality worldwide, motivating an increasing interest in advanced digitalization strategies that combine building information modeling (BIM) with digital twin (DT) capabilities. By linking static semantic site models with continuous field data, these systems offer a powerful approach to proactive risk management. However, while individual remote sensing and predictive analytics components are well researched, a unified understanding of how these BIM and DT safety systems are integrated remains critically limited. Specifically, there is a clear need to understand how system capabilities evolve across different maturity stages and what underlying factors drive this progression across the construction lifecycle. This paper presents a comprehensive scoping review of BIM and DT integration for construction safety management across the entire project lifecycle. Using a tiered evidence strategy and structured thematic coding, the existing literature is synthesized through three main analytical lenses: integration mechanisms and data exchange patterns, maturity characteristics and capability horizons, and the socio-technical factors that systematically influence maturity transitions. This review clarifies the dominant architectural integration approaches and maps current proof-of-concept efforts against the requirements for more predictive and governance-ready safety twins. The findings indicate that most implementations remain at the interactive monitoring stage, with predictive capability emerging mainly in data-rich contexts and autonomous adaptation not yet realized. Furthermore, it identifies persistent bottlenecks in data interoperability and real-time processing that currently hinder widespread industry adoption. Finally, the study proposes a focused research agenda designed to help transition these intelligent monitoring systems from isolated prototypes to robust, scalable applications suitable for safety-critical construction environments.

Trenchless construction technologies enable pipeline installation with reduced surface disruption. Despite the advantages, trenchless operations continue to experience safety and operational challenges, particularly utility strikes and unintended interactions with existing underground assets. Sensing technologies can capture positional, proximity, and operational data from equipment, workers, and the subsurface, yet their application in trenchless construction remains fragmented. This study presents a systematic review and integrated analysis of sensing technologies applied to trenchless construction contexts. The literature was analyzed by sensor type, placement, data modality, and application stage, using a combined thematic and scientometric approach. Results show sensing technologies are mainly used for preconstruction detection, standalone monitoring, or post-installation inspection, with limited real-time integration. A five-layer integration framework is proposed that connects (1) sensing and data acquisition, (2) communication and synchronization, (3) data fusion with trenchless equipment telemetry and utility information systems, (4) analytics and decision support, and (5) operational feedback and control.

Construction project delivery fosters progress and development in society, whereas failures can lead to diverse and sometimes severe consequences, particularly for the most affected stakeholders. The purpose of this paper is to investigate the multifaceted effects of construction project failure, with an emphasis on understanding their impact on key stakeholders, including clients, the general public, contractors, and consultants, in the context of developing countries such as Nigeria. Data were collected through a purposively administered questionnaire survey of stakeholders consisting of clients, contractors, and consultants in Lagos, Nigeria. Analysis was done using thematic analysis, the relative importance index, and Spearman's correlation coefficient. The findings reveal that the financial and economic impact, characterized by loss of revenue, bankruptcy, and cost escalation, stands as the most significant consequence of project failure. Among the stakeholders, clients were perceived as being most severely affected by the failure of construction projects, followed by the general public, contractors, and consultants. This study using qualitative analysis provided broad categories that encompass the identified effects of construction project failure, offering a foundational template for future research. The research findings on the disproportionate impact of project failures on clients, positioning them as the primary affected stakeholder group, are pivotal. This information shifts the focus toward understanding the unique challenges faced by clients in construction project failures. Lastly, delving into the effects of construction project failure underscores the need for robust management strategies to mitigate these impacts, particularly for the most vulnerable stakeholders.

Purpose: The Nigerian construction industry accounted for more than 40% of Nigeria's 3,461 recorded occupational accidents/injuries and 238 fatalities between 2014 and 2016, which is the highest of any sector. The emergence of the metaverse offers an innovative platform for enhancing planning, supervision and safety in hazardous construction environments. The metaverse technology has gained significant importance in safety training across various economic sectors, including construction, due to its numerous benefits. The study aimed at assessing the critical success factors (CSFs) for the adoption and implementation of metaverse-based safety training in the Nigerian construction industry. Design/methodology/approach: A quantitative research design was adopted, utilising a structured questionnaire administered to 73 construction companies registered with the Federation of Construction Industry (FOCI) in Nigeria. The aim was to assess the CSFs for adopting and implementing metaverse-based safety training in construction project delivery. With a high response rate of 91.25%, the collected data were analysed using mean analysis, relative importance index (RII), coefficient of variation (CV) and factor analysis through principal component analysis (PCA) to extract meaningful insights. Findings: The descriptive analysis (mean and RII) revealed that the top four CSFs for the adoption and implementation of metaverse-based safety training in the Nigerian construction industry include user training and skill development, customisation to construction site realities, integration with existing training frameworks and alignment with organisational goals. Secondly, factor analysis yielded a three-factor solution comprising: (1) technological and regulatory factors, (2) communication and training factors and (3) organisational and economic factors. These findings emphasise the importance of leadership support, infrastructure readiness, user training and regulatory alignment. Originality/value: The study is novel in identifying and categorising the CSFs for the adoption of metaverse-based safety training in the Nigerian construction industry. The originality lies in the context-specific contribution revealing factors relevant to the industry. The study provides actionable insights for safety managers and construction firms on the prerequisite for the successful implementation of metaverse platforms for safety enhancement.

The assembly of steel structures is a complex and labour-intensive process that poses significant safety risks to workers. The Intermeshed Steel Connection (ISC) is an emerging type of structural steel connection that requires fewer bolts and can benefit from the use of robotics. The assembly process for traditional structural steel connections requires humans to work-at-height, which is unsafe and unergonomic, and the few robotic and automatic steel building assembly systems are not readily adoptable. In response, this paper proposes a novel strategy for automating the ISC assembly using offthe-shelf robotic manipulators. The proposed method aims to enhance safety and efficiency by incorporating a collaborative human-robot approach in the assembly process, which leverages computer vision and robotic manipulation technologies. A detailed workflow for the robotic assembly of the ISC is conceptualized by dividing the assembly process into multiple stages. A small-scale experimental setup has been created for future demonstration. The experimental setup includes a scaled-down ISC column-to-column connection, utilizing a KUKA LBR iiwa14 manipulator equipped with multiple cameras and computer vision algorithms for precise alignment and assembly.