Health and safety (H&S) is a major concern in the construction industry. Recent and historical data from the construction industry world wide demonstrates that the human, social, and economic burden, inflicted as a result of H&S fatalities, is still significant. Training is considered one of the main strategies to reduce H&S risks. In recent years, the use of serious games for H&S training in construction has emerged in an attempt to overcome issues associated with traditional training methods. Current research in serious games has mainly focused on scenario-led training where trainees interact with the same environment through a pre-selected number of options in discrete sections. This approach has limitations in terms of variety and amount of skills that trainees perceive from the game. In this paper, an approach that combines serious games design with 4D (3D + time) modelling is presented and tested in terms of its influence on increasing the capability of labourers to spot hazards at different time periods during the construction process, providing them with increased immersion in the virtual training environment. The results demonstrated that a combination of serious games and 4D approaches can improve users' engagement and affect their abilities to spot H&S hazards.

The issue of interoperability in the Architecture, Engineering, and Construction (AEC) industry represents a challenge on a scale that spans across the project life cycle. This is predominant in the infrastructure sector that usually comprises a more versatile Operations and Maintenance (O&M) phase in comparison with the buildings sector. To this end, an important stage in the information life cycle is the asset information capture and validation during product procurement at the O&M phase. The water industry in the United Kingdom relies on Product Data Templates (PDTs) to fulfil such task, which is usually an error prone manual process. This paper presents an ongoing research, which investigates the application of Semantic Web Technologies (SWT) for improving product data exchange during product procurement at the O&M phase for the water industry in the United Kingdom (UK). Therefore, focus group sessions with industry experts were held to discuss current inefficiencies and solution requirements. Based on these results, a semantic common model named Asset Specification Ontology (ASO) was developed to capture and validate asset information during product procurement at the O&M phase. The common model (ontology) is based on available technologies, namely Web Ontology Language (OWL) and Shapes Constraint Language (SHACL). This gives the advantage of semantically rich data which can be linked and queried in a meaningful way to facilitate the exchange and validation of water industry assets’ data. The uniqueness of this paper is manifested in the issue it tackles, as efficient product procurement, and hence, data exchange in the water industry is an industrial challenge that is seldom researched. Results from the focus group sessions showed that information exchange within the UK water industry is impeded due to the lack of structured and semantic data. However, for a robust semantic interoperability, there needs to be a robust semantic data infrastructure, which would require semantic mappings from standards to product properties, from standards to other standards, and from standards to dictionaries. These conclusions were further supported by the common model, which was created from existing schemas, standards, and dictionaries. Generally, this paper recommends a common model/product library for phase-specific product data exchange in the water industry.