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The construction industry is a complex environment where high accident rates make significant contributions to cost overruns and time delays. Safety education is important in promoting a safe and healthful working environment in construction; however current pedagogical methods and tools at the tertiary level are unable to provide students with real practical and safety experiences. This study proposes an online social virtual reality (VR) system framework which allows students to perform role-playing, dialogic learning, and social interaction for construction safety and health education. The framework includes the following three modules: 1) Cooperative Distributed Safety Learning (CDSL) to understand root causes of accidents in construction site; 2) Hazard Inspection and Safety Cognition (HISC) to reflect on safety theories through hazard inspection within a social VR environment; 3) Active Safety Game-based Learning (ASGL) to enhance practical capacities by playing the safety training game in a 3D virtual environment. The system prototype is developed and evaluated with virtual scenarios derived from real safety cases to identify the system’s benefits and limitations. The results concluded that the social/collaborative virtual reality platform would improve construction safety & health education effectively.

Accident, injury, and fatality rates remain disproportionately high in the construction industry. Information from past mishaps provides an opportunity to acquire insights, gather lessons learned, and systematically improve safety outcomes. Advances in data science and industry 4.0 present new unprecedented opportunities for the industry to leverage, share, and reuse safety information more efficiently. However, potential benefits of information sharing are missed due to accident data being inconsistently formatted, non-machine-readable, and inaccessible. Hence, learning opportunities and insights cannot be captured and disseminated to proactively prevent accidents. To address these issues, a novel information sharing system is proposed utilizing linked data, ontologies, and knowledge graph technologies. An ontological approach is developed to semantically model safety information and formalize knowledge pertaining to accident cases. A multi-algorithmic approach is developed for automatically processing and converting accident case data to a resource description framework (RDF), and the SPARQL protocol is deployed to enable query functionalities. Trials and test scenarios utilizing a dataset of 200 real accident cases confirm the effectiveness and efficiency of the system in improving information access, retrieval, and reusability. The proposed development facilitates a new “open” information sharing paradigm with major implications for industry 4.0 and data-driven applications in construction safety management.

Accidents still prevail in the construction industry, resulting in injuries and fatalities all over the world. Educational programs in construction should deliver safety knowledge and skills to students who will become responsible for ensuring safe construction work environments in the future. However, there is a gap between the competencies current pedagogical approaches target, and those required for safety in practice. This study contributes to addressing this issue in three steps. Firstly, a vision for competency-based construction safety education is conceived. Building upon this, a research scheme to achieve the vision is developed, and the first step of the scheme is initiated in this study. The critical competencies required for safety education are investigated through analyses of literature, and confirmed through surveys with construction and safety management professionals. Results from the study would be useful in establishing and orienting education programs towards current industry safety needs and requirements

In order to proactively prevent accidents and injuries in construction, tertiary safety education should equip students with adequate safety knowledge and skills. However, in most construction curricula, safety is considered a low priority, and safety education is delivered in isolation, without sufficient interaction and practical experience to improve safety learning. On the other hand, anatomical theory in medicine has been adopted by and proved advantageous to various scientific disciplines. With this regard, this study presents an interactive construction safety education system using building anatomy modelling (BAM) based on the integration of anatomical theory and state-of-the-art visualization technologies. The BAM system comprises two modules: (1) knowledge acquisition module, which delivers safety knowledge to students; and (2) practical experience module, which enables students to interact with BAM to improve their hazard identification and elimination skills. The building anatomy concept (BAC) and BAM prototype are evaluated through interactive system trials with educators and learners. Findings suggest the BAC has significant pedagogic potential, and the proposed system can effectively provide safety knowledge and interactively support the development of practical safety skills of learners.

This chapter comprehensively synthesizes research efforts on visualization technologies in construction education with a systematic review of studies from 2005 to 2016. As visualization technologies consistently become more pervasive and commonplace in society, research which consolidates extant knowledge, achievements and trends on their application would be beneficial to pave the way for future research in the construction education. Similarly, construction education has had its share of VR systems and environments with applications in building construction, construction safety, equipment training and so on. In the context of construction education, effectiveness evaluations pertained to learning outcomes, i.e. quantitative improvements in learners' knowledge, skills and performance (e.g. number of errors, or time required to execute an activity), as well as qualitative feedback from subjects. The use of advanced visualization technologies is rapidly growing in entertainment and education, and permeating into industry practice in various disciplines.

Despite the consistent growth of global markets and emergence of cutting-edge technologies, construction jobsites remain among the most dangerous workplaces with extremely high accidents rates. In the safety management process, it is necessary to review and assess a variety of safety documents and data. Numerous public agencies provide open access to accident data, safety checklists, templates and other useful documents for safety management. However, these safety related contents are multifarious, fragmented and often stored in unstructured ways. As a result, the process of finding and utilizing required safety information for specific safety tasks is challenging and inefficient. In order to address this issue, this paper proposes an innovative approach using linked data and semantic web technologies for integrating and sharing construction safety information from diverse sources. A construction safety contents ontology is developed, and construction safety information from accident cases, Job Hazard Analyses (JSA), safety rules and training contents is integrated through RDF formats and SPARQL queries. In order to enable convenient and effective retrieval of information, this study develops a categorization and classification of safety-related contents for safety management processes. The proposed system is expected to improve access and sharing construction safety information, reduce data search time and improve data accuracy. Through this, the approach may enable reductions in safety incidents and overall improvements in safety management and performance.

Accident, injury, and fatality rates remain disproportionately high in the construction industry. Information from past mishaps provides an opportunity to acquire insights, gather lessons learned, and systematically improve safety outcomes. Advances in data science and industry 4.0 present new unprecedented opportunities for the industry to leverage, share, and reuse safety information more efficiently. However, potential benefits of information sharing are missed due to accident data being inconsistently formatted, non-machine-readable, and inaccessible. Hence, learning opportunities and insights cannot be captured and disseminated to proactively prevent accidents. To address these issues, a novel information sharing system is proposed utilizing linked data, ontologies, and knowledge graph technologies. An ontological approach is developed to semantically model safety information and formalize knowledge pertaining to accident cases. A multi-algorithmic approach is developed for automatically processing and converting accident case data to a resource description framework (RDF), and the SPARQL protocol is deployed to enable query functionalities. Trials and test scenarios utilizing a dataset of 200 real accident cases confirm the effectiveness and efficiency of the system in improving information access, retrieval, and reusability. The proposed development facilitates a new “open” information sharing paradigm with major implications for industry 4.0 and data-driven applications in construction safety management.

Background Nigeria accounts for the greatest burden of malaria disease globally. Malaria control requires an effective treatment after diagnosis. The efficacy of antimalarial drugs can be assessed through the analysis of genetic changes associated with reduced drug sensitivity. Methods This study includes the analysis of the markers associated with artemisinin ( pfk13 ), sulfadoxine–pyrimethamine ( pfdhfr and pfdhps ), and chloroquine and its derivatives ( pfmdr1 and pfcrt ) resistances, in blood samples collected from asymptomatic children in south-western Nigeria. Results The 25.95% of samples showed a number of mutations in pfk13 gene. Among those, the validated, C580Y, and the candidate, R515K, mutations by WHO were detected. Twenty-seven pfdhps different haplotypes were observed, with the haplotype IS G KAA as the most prevalent (18.80%), followed by I FG KAA (12.78%) and I AG KAA (11.28%). The VAG K GS was the most common haplotype carrying the I431V mutation (10.53%). Combinations of alleles in pfdhfr and pfdhps genes provided a 40.98% of samples with the partially resistant haplotype ( IRNG ). No samples exhibited the ‘fully resistant’ or ‘super resistant’ pfdhprf – pfdhps combinations, but one sample contained mutations at pfdhfr 51I, 59R, and 108N with pfdhps 431V, 436A, A437G and 540E. The analysis of pfcrt 72–76 variants disclosed a 12.12% of samples with the mutant-type (CV IET ). No double mutant pfmdr1 haplotypes 86Y/1246Y (YY) were detected, nor was the haplotype formed by the alleles 86Y pfmdr1  +  pfcrt 76 T (YT). Conclusions There was no evidence of parasite genomes harbouring multilocus mutations conferring multidrug resistance, although evidence of a validated (C580Y) and a candidate (R515K) mutation in pfk13 gene, high frequency pfdhfr mutant alleles and high variability of pfdhps haplotypes were found in this study, which provides a baseline information essential in monitoring P. falciparum resistances.

Schistosomiasis and soil-transmitted helminthiases (STH) are two parasitic diseases mainly affecting school children. The purpose of this study was to estimate the current prevalence and infection intensity, in addition to the associations of these infections with age and sex, in children aged 4–17 years living in Osun State, Nigeria. From each participant (250 children), one urine and one stool sample were taken for the study, for the microscopic detection of eggs or larvae in faeces by means of the Kato–Katz method and eggs in filtrated urine. The overall prevalence of urinary schistosomiasis was 15.20%, with light infection. The intestinal helminthic species identified (and their prevalence) were S. stercoralis (10.80%), S. mansoni (8%), A. lumbricoides (7.20%), hookworm (1.20%), and T. trichiura (0.4%), all of them being classified as light infections. Single infections (67.95%) are more frequent than multiple infections (32.05%). With this study, schistosomiasis and STH are still endemic in Osun State, but with a light to moderate prevalence and light infection intensity. Urinary infection was the most prevalent, with higher prevalence in children over 10 years. The >10 years age group had the highest prevalence for all of the intestinal helminths. There were no statistically significant associations between gender and age and urogenital or intestinal parasites.

Schistosomiasis and soil-transmitted helminthiases (STH) are two parasitic diseases mainly affecting school children. The purpose of this study was to estimate the current prevalence and infection intensity, in addition to the associations of these infections with age and sex, in children aged 4–17 years living in Osun State, Nigeria. From each participant (250 children), one urine and one stool sample were taken for the study, for the microscopic detection of eggs or larvae in faeces by means of the Kato–Katz method and eggs in filtrated urine. The overall prevalence of urinary schistosomiasis was 15.20%, with light infection. The intestinal helminthic species identified (and their prevalence) were S. stercoralis (10.80%), S. mansoni (8%), A. lumbricoides (7.20%), hookworm (1.20%), and T. trichiura (0.4%), all of them being classified as light infections. Single infections (67.95%) are more frequent than multiple infections (32.05%). With this study, schistosomiasis and STH are still endemic in Osun State, but with a light to moderate prevalence and light infection intensity. Urinary infection was the most prevalent, with higher prevalence in children over 10 years. The >10 years age group had the highest prevalence for all of the intestinal helminths. There were no statistically significant associations between gender and age and urogenital or intestinal parasites.