Hazard identification in the construction industry is subject to a larger number of variables and unknowns than in other manufacturing industries making the hazard identification process more difficult and resulting in many injuries and fatalities. Moreover, previous research identified a research gap with regards to a universal hazard identification method. The results presented in this paper are a prerequisite for the development of such a method. Specifically, this paper proposes a novel classification of hazards in order to enable a more accurate hazard identification process which can take all possible hazards into consideration. Based on the theoretical framework, three hazard types are proposed in the research: self-induced hazards, peer-induced hazards, and global hazards. This classification is based on who is the source (who causes) the hazards in relation to who is affected by the hazards. Such classification was not identified in previous literature. This research also has practical implications. Such classification of hazards may influence safety experts to more actively focus on peer-induced hazards which are the hardest to identify. Finally, the outputs of the entire research should enable a more accurate and comprehensive hazard identification resulting in reduced injury and fatality rates in the construction industry.

Construction industry is one of the most hazardous industries to work in. This problem is further exacerbated by the fact that safety performance improvement is stagnating. Information technologies (ITs) are however identified as one of the most promising methods of improving the performance of construction safety. The goal of this paper was therefore to present previous research in the application of innovative ITs to the field of construction health and safety (H&S), classified by their underlying technology and application, to identify research gaps, as well as to evaluate and describe the potential of their implementation into construction safety practice. To achieve the set goals, the research consisted of identifying and studying the existing research published in the leading journals in the field of construction H&S. The review identified 72 papers dealing with development or application of innovative ITs. The research had also identified several research gaps, which have a significant impact on the construction safety practice. These gaps focus on the construction phase, while neglecting earlier project phases; industry and project levels, while neglecting construction activity and task levels; building projects, while neglecting infrastructure projects and specific hazard types, while neglecting a universal approach. Focussing research effort on these gaps would benefit all construction safety stakeholders but mostly the prominent contractors and H&S professionals. Furthermore, recommendations for directing research focus on solving the identified issues are given in this paper.

The potential uses of 3D scan data in the construction industry have been extensively researched in the last 20 years, with many benefits over traditional methods proclaimed by researchers. However, despite their advocated benefits, their implementation in actual construction sites remains low. This research aims to discover the potential uses of 3D scan data for construction management purposes and the limitations and barriers to their implementation and widespread adoption. Previous research into the topic was analysed to discover what technologies were used for generating 3D scan data, for what purpose and what issues were identified. These discoveries were then used to specify the potential uses of 3D scan data for, primarily, progress monitoring and quality control, which were then cross-referenced with all known limitations and barriers from the literature and the researchers’ own experience. Research has shown that, currently, there are numerous issues with both the capabilities of current technical solutions and with the construction industry’s readiness, which hinder mass adoption. Potential for breakthroughs, fortunately, does exist; however, greater impetus from the construction industry is needed to drive forward the demand for better technical solutions, which would resolve current issues and lead to the widespread adoption of 3D scan data for construction management-related uses.

Construction industry is extremely hazardous with construction workers almost three times more likely than average to suffer a fatal accident in the workplace. Although great improvement in safety performance has been noted, in recent...

The European Union's (EU) main goal, as stated in the EU Green Deal, is to achieve climate neutrality by 2050, and the construction sector plays a significant role in this achievement through efforts to make infrastructure, commercial, and private projects more sustainable. For many years, Cost-Benefit Analysis (CBA) has been used to evaluate and make

This paper represents initial research with the aim to establishes a baseline for subsequent research into AI-based construction monitoring, building upon the NORMENG project in Croatia, which previously integrated photogrammetry, laser scanning, and BIM-based methods. The study tests general purpose AI’s ability to detect materials and estimate quantities, aiming to assess whether a broad, context-aware AI system can match the precision of specialized, domain-specific tools or even human work needed for productivity estimations. While the AI demonstrated potential for basic entity detection and preliminary quantity estimations, it showed significant limitations in delivering fine-grained, temporally accurate breakdowns without targeted adaptation. The findings underscore the need for domain-specific fine-tuning and human-in-the-loop validation to transform AI into a reliable tool for construction management. This initial contribution provides empirical insights and actionable recommendations for advancing automated progress monitoring in the construction sector.