Workforce location tracking to model, visualize and analyze workspace requirements in building information models for construction safety planning
Graphical abstract
Introduction
Traditional safety planning mainly relies on manual observation, which is labor-intensive, time-consuming, and potentially highly inefficient. The link between planning for safety and work-task execution is often weak: for example, many contractors use two-dimensional drawings or field observations to determine hazard-prevention techniques [1], [2]. The resulting safety plans are often error-prone due to subjective judgments of the available decision makers. Currently, historical workspace information for an activity and the corresponding contextual information depicting the condition under which the activity is accomplished are not stored. Hence, workspace planning for work activities in construction planning is often overlooked.
Although knowledge is typically transferred from one project to the next, this important task could be optimized, especially when experienced field staff is hired elsewhere. These circumstances lead to workspace congestion often at the beginning of projects. This may then largely impede worker safety, health, and productivity on a construction project. There is a need for an approach to collect, formalize, and reuse historical activity-specific workspace information.
The selected approach, other than previous approaches [1], describes an empirical study method that collects the active workspace, obtains its geometric parameters, visualizes the workspace, and detects workspace conflicts in building information models (BIM). A BIM-based application prototype for workspace visualization is eventually presented which demonstrates how this approach can assist activity-level construction planning.
This paper is structured as follows: Section 2 reviews workspace representation techniques and existing studies on the application of advanced location tracking technology in the construction industry. Section 3 presents the objective and scope of this study. In Section 4, workspace conflict taxonomy and representations are presented. The computation of workspace parameters based on location tracking data and visualization of workspace in BIM are explained in Section 5. Workspace conflict detections are discussed in Section 6. Section 7 presents a case study to the proposed workspace conflict detection using the developed prototype system. A summary of the contributions and discussions about future research needs is presented in the final section of this paper.
Section snippets
Construction workspace representation
Experts witness another phenomenon on construction sites: fast tracking and schedule compression create task overlaps on construction sites due to pressure for completion on time. This conflict occurs often, because multiple concurrent tasks compete for the limited workspace on site. Dealing with the planning and execution of simultaneous tasks and their workspaces is a main challenge that has been addressed in multiple workspace planning studies.
For this reason, 4D (3D and time) representation
Motivation to use novel technology and methods
According to US Occupational Safety and Health Administration (OSHA), “routes for the suspended loads should be pre-planned in order to ensure that no worker has to work directly below a suspended load (except for those workers who must hook up or unhook the load, or work on the initial connection of the steel members).” [34]. From 1992 to 2006, 307 crane accidents in the private U.S. construction industry sector killed 323 workers [35]. In 2006, cranes contributed both as primary and secondary
Workspace modeling
The goal and intention is to develop an activity-based workspace modeling method, and to create a framework to integrate activity-based workspace modeling with BIM. The workspace sets considered in this study include:
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Building component space: the space building component itself occupies; typically it is shown in BIM as a final product.
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Worker space: the required space for a crew to perform its work;
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Space for material handling path: the handling path required for the material movement, for
Workspace parameter computation and visualization
It is assumed that analyzing worker location data can result in the approximate workspace that was used to complete a work task. The geometric data then generates the workspace parameters for a type of work activity. An occupancy grid model [40], [41], [42], [43] is used for calculating the frequency of the visits of a worker to a predefined virtual cube, which represents part of the entire work area. After creating the occupancy grid map following Cheng et al. [29], algorithms were developed
BIM-based workspace conflict detection
Workspace conflicts are detected based on the geometric conditions of different settings in the workspace. According to Table 2, this research intends to mainly detect two types of major workspace conflicts: (1) workspace congestion and (2) safety hazards. In terms of congestion, the degree of workspace congestion can be determined for each of the activities based on their conflict volume, and it is defined after the conflict ratio in [8] and the space capacity factor in [3]. In terms of the
Case study
A case study was conducted to test the workspace conflict detection method. Three major concerns when optimizing workspaces for safer and more productive work are addressed:
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Workspace congestion detection: Aside interior finishing, one of the most frequent workspace congestions observed at tight construction sites is during formwork and concrete pouring of column construction. Projects facing ever tighter finishing schedules through lean management approaches make accomplishing these tasks more
Conclusions and outlook
This paper developed a novel framework and prototype methods that collect, formalize, and reuse historical activity-specific workspace information for automated activity-based workspace modeling and visualization of work congestion identification and safety analysis in BIM. Global Positioning Systems (GPS) data to worker location tracking were collected to compute accurate workspace occupation parameters based on the occupancy level for all of the work activities involved in building concrete
Acknowledgments
The authors would like to thank the McCarthy Building Companies, Inc. for the generous access to their construction site. Any opinions, findings, or conclusions included in this paper are those of the authors and do not necessarily reflect the views of anyone else.
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