Browsing by Subject "Construction safety"
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Item 4-dimensional process-aware site-specific construction safety planning(2015-12) Choe, Sooyoung; Leite, Fernanda; Caldas, Carlos; Thomas, Stephen; Zhang, Zhanmin; Alves, ThaisThe construction industry has one of the worst occupational health and safety records of all industries. In spite of stringent regulations and much attention towards reducing risks in the physical environment, the construction industry continues to be associated with high levels of accidents, injuries, and illnesses. Construction safety management activities are typically categorized into safety planning and execution processes. Despite the interdependent relationship between safety planning and execution processes, current safety planning processes lack a systematic approach because of limited safety tools and site-specific information available. As a result, safety planning and execution processes are generally segregated and, consequently, most safety execution processes rely on ad-hoc safety activities during construction. The objective of this research is to systematically formalize the construction safety planning process in a 4-dimensional (4D) environment to address site-specific temporal and spatial safety information, by leveraging project schedules and information technology to improve current construction safety management practices. Prior to developing a specific framework, this research presents a safety risk generation and control model to describe the phenomenon of dynamic safety risk, incorporating construction domain knowledge. The proposed model addresses how the inherent risk of a worker can be transformed by different measurable contexts of activities. Based on the theoretical model, this research assessed safety risk of different construction trades in a quantitative manner. By integrating multiple national injury databases, safety risks of different construction occupations were analyzed to explain common risk types, sources of injury, and risk scenarios associated with each occupation type. With results of safety risk analysis as a reference, a formalized safety planning framework to aid in developing a long-term safety risk prediction plan was proposed. The proposed framework analyzed activity, work period, and work zone safety by integrating a project schedule and a 3D model. The proposed safety planning process was tested in a real-world project. This research advances safety knowledge, integrating site-specific temporal and spatial information, and significantly affecting the construction safety planning process. The proposed safety planning approach can provide safety personnel with a site-specific proactive safety planning tool that can be used to better manage jobsite safety by predicting activity risk, work period risk, and work zone risk in advance. In addition, visual safety materials can also aid in training workers on safety and, consequently, being able to identify site-specific hazards and respond to them effectively.Item Modeling object identification and tracking errors on automated spatial safety assessment of earthmoving operations(2010-05) Chi, Seok Ho; Caldas, Carlos H.; O'Brien, William J.; Menches, Cindy L.; Zhang, Zhanmin; Kuipers, BenjaminRecent research studies have been conducted for automating the safety assessment process in order to identify risks and safety hazards on a job site without human intervention. Regardless of the benefits of automated assessment, safety planners still face challenges selecting applicable devices, methods, and algorithms for safety assessment. This is due to the fact that (1) such devices, methods, and algorithms typically have measurement and processing errors, (2) construction operations and sites are unique and complex, and (3) the impact of the errors is different depending on workspaces. The primary objective of this research is to develop an error impact analysis method to model data collection and data processing errors caused by image-based devices and algorithms and to analyze the impact of the errors for spatial safety assessment of earthmoving and surface mining activities. The literature review revealed the possible causes of accidents on earthmoving activities, investigated the spatial risk factors of these types of accident, and identified spatial data needs for safety assessment based on current safety regulations. Image-based data collection devices and algorithms for safety assessment were then evaluated. Analysis methods and rules for monitoring safety violations were also discussed. A testbed to model and simulate workspaces and related spatial safety violations was finally designed. Using the testbed, the impacts of image-based algorithm and device errors―more specifically, object identification and tracking errors―on the data collected and processed were investigated for the safety planning purpose. Field experiments assessed the feasibility of automated spatial data collection and analysis methods. Industrial project and safety experts verified the proposed safety rules and the testbed design. Computer simulations were conducted for testing the proposed testbed. The testbed was used to model several earthmoving operation scenarios, detect simulated safety violations using safety rules, and finally evaluate the impact of different object identification and tracking errors on the safety analyses. The result of this research could be used for improving site safety assessment and planning by assisting safety planners to understand workspaces and to evaluate errors related to the use of different image-based technologies for safety assessment of earthmoving and surface mining activities.Item Requirements, specifications and deployment models for autonomous jobsite safety proximity monitoring(2013-05) Luo, Xiaowei; O'Brien, William J.; Leite, FernandaConstruction has a higher injury and fatality rate than most of the other industries. Given this situation, existing research has studied various issues and factors affecting construction safety management and has attempted to use all available methods to improve the construction safety performance. However, the construction accident rate remains among the highest in the United States and the world. The primary objective of this research is to advance autonomous proximity monitoring and hence provide a safer environment for construction workers. In particular, I seek to advance current evaluations of proximity warning technologies to a more robust engineering approach to the design and deployment of autonomous safety monitoring systems. The contributions of the research are demonstrated through specifications, deployments, and testing of proximity monitoring systems for crane loads and falling from height. My research advances current knowledge in three areas. First, I develop specifications for proximity safety monitoring in a sensed environment, built from existing guidelines and expert interviews. Second, I translate the specifications to computer interpretable rules and deploy them in a distributed computing environment. This demonstrates the feasibility of a systems approach and reusability of components to speed deployment. Third, I evaluate the accuracy of the specifications and systems under imperfect data. I further evaluate some approaches to dealing with imperfect data. Collectively, these advances move existing proximity warning research from evaluation of specific systems to an engineering approach to development and deployment of distributed systems with reusable components that explicitly treats imperfect data.