The construction industry has hit a plateau in terms of safety performance. Safety climate is regarded as a leading indicator of safety performance; however, relatively little safety climate research has been done in the Canadian construction industry. Safety climate may be geographically sensitive, thus it is necessary to examine how the construct of safety climate is defined and used to improve safety performance in different regions. On the other hand, more and more attention has been paid to job related stress in the construction industry. Previous research proposed that individual resilience may be associated with a better safety performance and may help employees manage stress. Unfortunately, few empirical research studies have examined this hypothesis. This paper aims to examine the role of safety climate and individual resilience in safety performance and job stress in the Canadian construction industry. The research was based on 837 surveys collected in Ontario between June 2015 and June 2016. Structural equation modeling (SEM) techniques were used to explore the impact of individual resilience and safety climate on physical safety outcomes and on psychological stress among construction workers. The results show that safety climate not only affected construction workers' safety performance but also indirectly affected their psychological stress. In addition, it was found that individual resilience had a direct negative impact on psychological stress but had no impact on physical safety outcomes. These findings highlight the roles of both organizational and individual factors in individual safety performance and in psychological well-being. Construction organizations need to not only monitor employees' safety performance, but also to assess their employees' psychological well-being. Promoting a positive safety climate together with developing training programs focusing on improving employees' psychological health - especially post-trauma psychological health - can improve the safety performance of an organization.

Real-time monitoring of heavy equipment can help practitioners improve machine-intensive and cyclic earthmoving operations. It can also provide reliable data for future planning. Surface earthmoving job sites are among the best candidates for vision-based systems due to relatively clear sightlines and recognizable equipment. Several cutting-edge computer vision algorithms are integrated with spatiotemporal information, and background knowledge to develop a framework, called server-customer interaction tracker (SCIT), which recognizes and measures the dirt loading cycles. The SCIT system detects dirt loading plants, including excavator and dump trucks, tracks them, and then uses captured spatiotemporal data to recognize loading cycles. A novel hybrid tracking algorithm is developed for the SCIT system to track dump trucks under visually noisy conditions of loading zones. The developed framework was evaluated using videos taken under various conditions. The SCIT system with novel hybrid tracking eng...

Accurate and proactive inspection of constructed objects and identification of their defects and design conformity is vital to both facility management and construction projects. A project’s building information model (BIM) needs to be regularly updated to more accurately reflect the actual site conditions. However, conventional practices lack site-data integration with models and rely on manual, error-prone, and costly updates. This paper proposes and demonstrates a robust technique that uses the industry foundation classes (IFC) schema to automatically update an as-designed BIM based on site observations for inspected building elements. It receives as input an inspected object’s actual type and inspection details including the detected defects/changes, responsible actors, as-built/as-is type, captured images, and time and the date of the inspection. The algorithm automatically analyzes the IFC data model to retrieve the element’s semantics and identifies discrepancies between the as-built/as-is and as-designed object conditions. Based on the results of the discrepancy analysis, the IFC data model is populated with new semantics, resulting in the update of object types, properties, and three-dimensional (3D) shape representations. Inspection details and user entries are automatically documented in the BIM and assigned to objects to enable potential diagnostics and tractability. This automates site-to-BIM data transfer and supports reality-capture techniques.

Earthmoving plants are essential but costly resources in the construction of heavy civil engineering projects. In addition to proper allocation, ongoing control of this equipment is necessary to ensure and increase the productivity of earthmoving operations. Captured videos from construction sites are potential tools to control earthmoving operations; however, the current practice of manual data extraction from surveillance videos is tedious, costly, and error prone. Cutting-edge computer vision techniques have the potential to automate equipment monitoring tasks. This paper presents research in the evaluation of combinations of existing object recognition and background subtraction algorithms to recognize off-highway dump trucks in noisy video streams containing other active machines. Two detection algorithms, namely, Haar–histogram of oriented gradients (HOG) and Blob-HOG, are presented and evaluated for their ability to recognize dump trucks in videos as measured by both effectiveness and timel...

Interpersonal conflicts at work (ICW) have been widely regarded as a job stressor; however, it is rarely linked to physical safety outcomes. The ICW primarily has two forms on a construction site: conflicts with supervisors (${\mathrm{ICW}}_S$ ) and conflicts with coworkers (${\mathrm{ICW}}_C$ ). This study examined the occurrences of ${\mathrm{ICW}}_S$ and ${\mathrm{ICW}}_C$ on construction sites, and investigated the relationship among ${\mathrm{ICW}}_S$ , ${\mathrm{ICW}}_S$ , and physical safety outcomes together with job stress. In addition, possible antecedents of ${\mathrm{ICW}}_S$ and ${\mathrm{ICW}}_C$ including workhours, mobility, and individual resilience were also examined. The research was based on 837 surveys collected from more than 100 construction sites in Ontario, Canada between July 2015 and July 2016. Structural equation modeling (SEM) techniques were used to test the hypothesized relationships. This paper leads to the following conclusions. Although ICW was reported as quite often or very often by only 6.3% of respondents, it had a significant effect on both physical safety outcomes, including physical injuries and unsafe events, and job stress. Individual resilience (IR) had a significant negative correlation with both ${\mathrm{ICW}}_S$ and ${\mathrm{ICW}}_C$ , which in turn could decrease the frequency of physical safety outcomes and job stress. The contributions of this study are that safety professionals may consider adding coping skill training safety programs to improve the individual resilience of their workforce and reduce conflict-related safety outcomes.