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  • 1
    Publication Date: 2020-03-02
    Description: Fires pose an enormous threat to human safety and many spectacular fires in under-construction buildings were reported over the past few years. Many construction sites only rely on fire extinguishers, as under-construction buildings do not contain a permanent fire protection system. Traditional safety planning lacks a justified approach for the firefighting equipment installation planning in the construction job site. Even though many government agencies made safety regulations for firefighting equipment installations, it is still a challenge to translate and execute these rules at the job site. Currently, the construction industry is devoted to discovering all the possible applications of Building Information Modelling (BIM) technology in the entire phases of the project life cycle. BIM technology enables the presentation of facilities in 3-D and offers rule-based modeling through visual programming tools. Therefore, this paper focuses on a visual language approach for rule translation and a multi-agent-based construction fire safety planning simulation in BIM. The proposed approach includes three core modules, namely: (a) Rule Extraction and Logic Development (RELD) Module, (b) Design for Construction Fire Safety (DCFS) Module, and (c) Con-fire Safety Plan Simulation (CSPS) Module. In addition, the DCFS module further includes three submodules, named as (1) Firefighting Equipment Installation (FEI) Module, (2) Bill of Quantities (BoQs) for firefighting Equipment (BFE) Module, and (3) Escape Route Plan (ERP) Module. The RELD module converts the OSHA fire safety rule into mathematical logic, and the DCFS module presents the development of the Con-fire Safety Planning approach by translating the rules from mathematical logic into computer-readable language. The three sub-modules of the DCFS module visualize the outputs of this research work. The CSPS module uses a multi-agent simulation to verify the safety rule compliance of the portable firefighting equipment installation plan the system in a BIM environment. A sample project case study has been implemented to validate the proof of concept. It is anticipated that the proposed approach has the potential to helps the designers through its effectiveness and convenience while it could be helpful in the field for practical use.
    Electronic ISSN: 2076-3417
    Topics: Natural Sciences in General
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  • 2
    Publication Date: 2021-02-18
    Description: Construction sites are considered as complicated work environments. Various concurrent activities may overlap apropos to time and workspace, predisposing them to spatial–temporal exposure and repetitive accidents. Detecting the characteristics of repetitive accidents before the construction stage contributes to prevent injuries and fatalities caused by spatial—temporal conditions at construction job sites. To resolve this problem, this study proposes a novel hazard identification approach through spatial–temporal exposure analysis called HISTEA, which integrated scenario analysis of accident cases into 4D building information modeling (BIM). The proposed approach consists of three modules: (1) spatial–temporal hazard investigation (SHI) to analyze the accident cases and develop the hazard database of the spatial–temporal overlap condition of pair-wise activities; (2) spatial–temporal condition identification (SCI) to determine the conflict among different activities, considering the workspace and time overlap from the 4D BIM model; and (3) safety information integration (SII) to deliver safety knowledge to the project team through a web-based application. To illustrate and validate this approach, a HISTEA prototype for foundation work has been developed to be used at the pre-construction stage. The developed prototype is based on the analysis of 496 accident reports extracted from the integrated management information system (IMIS) of the Occupational Safety and Health Administration for the SHI module database. The proposed approach is expected to proactively aid project teams in detecting hazards that ultimately reduce repetitive accidents caused by overlapping activities.
    Electronic ISSN: 2071-1050
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 3
    Publication Date: 2021-02-20
    Description: Construction Progress monitoring noticed recent expansions by adopting vision and laser technologies. However, inspectors need to personally visit the job-site or wait for a time gap to process data captured from the construction site to use for inspection. Recent inspection methods lacks automation and real-time data exchange, therefore, it needs inspection manpower for each job-site, the health risk of physical interaction between workers and inspector, loss of energy, data loss, and time consumption. To address this issue, a near real-time construction work inspection system called iVR is proposed; this system integrates 3D scanning, extended reality, and visual programming to visualize interactive onsite inspection for indoor activities and provide numeric data. The iVR comprises five modules: iVR-location finder (finding laser scanner located in the construction site) iVR-scan (capture point cloud data of job-site indoor activity), iVR-prepare (processes and convert 3D scan data into a 3D model), iVR-inspect (conduct immersive visual reality inspection in construction office), and iVR-feedback (visualize inspection feedback from job-site using augmented reality). An experimental lab test is conducted to verify the applicability of iVR process; it successfully exchanges required information between construction job-site and office in a specific time. This system is expected to assist Engineers and workers in quality assessment, progress assessments, and decision-making which can realize a productive and practical communication platform, unlike conventional monitoring or data capturing, processing, and storage methods, which involve storage, compatibility and time-consumption issues.
    Electronic ISSN: 2071-1050
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 4
    Publication Date: 2021-08-01
    Print ISSN: 0166-3615
    Electronic ISSN: 1872-6194
    Topics: Computer Science , Technology
    Published by Elsevier
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  • 5
    Publication Date: 2024-04-07
    Description: The construction industry faces significant challenges, including a high prevalence of occupational incidents, often involving fires, explosions, and burn-related accidents due to worker non-compliance with safety protocols. Adherence to safety guidelines and proper utilization of safety equipment are critical to preventing such incidents and safeguarding workers in hazardous work environments. Consequently, a monitoring system tailored for construction safety during welding operations becomes imperative to mitigate the risk of fire accidents. This paper conducts a brief analysis of OSHA rules pertaining to welding work and introduces the iSafe Welding system, an advanced real-time safety monitoring and compliance enforcement solution designed specifically for construction site welding operations. Harnessing the real-time object detection algorithm YOLOv7 in conjunction with rule-based scene classification, the system excels in identifying potential safety violations. Rigorous evaluation, encompassing precision, recall, mean Average Precision (mAP), accuracy, and the F1-Score, sheds light on its strengths and areas for improvement. The system showcases robust performance in rule-based scene classification, achieving high accuracy, precision, and recall rates. Notably, the iSafe Welding system demonstrates a formidable potential for enhancing construction site safety and regulatory compliance. Ongoing enhancements, including dataset expansion and model refinement, underscore its commitment to real-world deployment and its strength in ensuring worker safety
    Keywords: Safety monitoring ; scene classification ; welding work ; fire prevention ; construction safety ; OSHA rules compliance ; thema EDItEUR::U Computing and Information Technology
    Language: English
    Format: image/jpeg
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