BIM-Based Construction Noise Hazard Prediction and Visualization for Occupational Safety and Health Awareness Improvement

Wei, Weile; Wang, Chao; Lee, Yongcheol

doi:10.1061/9780784480823.032

Cited by 12 publications

(9 citation statements)

References 11 publications

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“…Sensors are a significant underpinning technology component when formulating a typical DT application. There are many types of sensor, including global positioning system (GPS) sensors, radio frequency identification (RFID) sensors, wireless local area network (WLAN) sensors, Bluetooth low-energy (BLE) sensors, ultra-wideband (UWB) sensors, and others [12][13][14][15][16][17]. Machine learning technology has been well integrated into computer vision to enable object recognition, tracking, and pattern analysis [18,19].…”

Section: Introductionmentioning

confidence: 99%

Literature Review of Digital Twins Applications in Construction Workforce Safety

et al. 2020

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For many decades, safety has been a challenge in the construction sector. Despite extensive efforts to improve overall safety, the sector’s casualty rate still remains high. In practice, dynamic and complex construction processes may lead to on-site risks and safety plans being overlooked, likely leading to a variety of safety accidents. Nowadays, under the guidance of the digital twins (DT) concept, the advent of state-of-the-art sensing and visualisation technologies has offered the possibility to improve construction health and safety in the workplace. To understand the research advances of these technologies, identify their gaps and challenges, and propose solutions to further advance the industry’s safety, we conducted and report a thorough review on the state-of-the-art technological studies, and elaborate upon the key findings in detail. For instance, despite DT being proven to be effective in improving construction workforce safety, the construction industry has yet to fully exploit and streamline these innovations in practice. Overall, this review provides insights into technological clustering, improvement strategies, as well as workforce safety, which can benefit from formulating effective digital technology paradigms.

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Section: Introductionmentioning

confidence: 99%

Literature Review of Digital Twins Applications in Construction Workforce Safety

et al. 2020

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“…[32,[45][46][47][48]. As shown in keywords co-occurrence network, BIM and VR can be applied as the auxiliary tools of safety management thus achieving visualization [42][43][44].…”

Section: Discussion On Further Research Trendsmentioning

confidence: 99%

“…The keywords for cluster 3 were mainly about safety management in terms of personnel characteristics. For instance, visual simulation and proximity warning system were recognized as effective tools for safety training and management [42][43][44]. Moreover, research on safety management inclined to combine with the characteristics of vulnerable groups, such as minority, elderly, and females (gender issue) [45][46][47][48].…”

Section: Structural Equation Modellingmentioning

confidence: 99%

“…Although cluster 6 involved only four keywords (safety behavior, safety awareness, social identity, and social influence), its extensive correlation with clusters 3, 4, and 1 revealed its significance (i.e., connected with safety perception in cluster 3, safety management in cluster 4, and safety climate in cluster 1). For instance, the significance of construction personnel awareness on work safety and its relationship with safety climate were revealed [28], which provided the linkage between cluster 6 and cluster 1; Wei et al, combined safety awareness and building information modeling technology as a systematic model of safety management, which contributed to the correlation between clusters 6 and 4 [43]; Gyekye and Salminen discussed safety perception of construction workers and provided the connection between clusters 6 and 3 [49].…”

Section: Structural Equation Modellingmentioning

confidence: 99%

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Current States and Future Trends in Safety Research of Construction Personnel: A Quantitative Analysis Based on Social Network Approach

Meng

Chan

2021

IJERPH

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The construction industry is recognized as a high-risk industry given that safety accidents and personnel injuries frequently occur. This study provided a systematic and quantitative review of existing research achievements by conducting social network approach to identify current states and future trends for the occupational safety of construction personnel. A total of 250 peer-reviewed articles were collected to examine the research on safety issues of workers in construction industry. Social network approach was applied to analyze the interrelationship among authors, keywords, and citations of these articles using VOS viewer and CitNetExplorer. A knowledge structure map was drawn using main path analysis (MPA) towards the collected papers, which was implemented by Pajek. In line with the findings of social network analysis, five research groups, and six keyword themes were identified in accordance with the times of cooperation of researchers and correlation among keywords of the papers. Core papers were identified by using main path analysis for each research domain to represent the key process and backbone for the corresponding area. Based on the finding of the research, significant implications and insights in terms of current research status and further research trends were provided for the scholars, thus helping generate a targeted development plan for occupational safety in construction industry.

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“…In subway spaces, Marzouk and Abdelaty [57] visualized the readings of air temperature and humidity levels based on BIM and a wireless sensor network to monitor thermal comfort and to predict problems in the subway heating, ventilation and air conditioning (HVAC) systems. In terms of noise, Wei, et al [58] predicted noise spatial distribution by collecting scattered data from wearable noise sensors in combination with BIM, aiming to prevent construction workers from noise-induced hearing loss. In addition to the real-time monitoring of the safety environment, BIM can also integrate with virtual reality to enhance construction safety.…”

Section: Discussionmentioning

confidence: 99%

BIM-Based Visualization Research in the Construction Industry: A Network Analysis

Chen

Cai

et al. 2019

IJERPH

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Visualization is one of the main features of Building Information Modeling (BIM). It has many advantages throughout the lifecycle of a construction project, and it has become a timely research topic in recent years. However, no attempt has been made to give a holistic understanding of the existing BIM-based visualization research status. Thus, this study aims to conduct a scientometric analysis of the existing BIM-based visualization literature and to gain a snapshot of the research status during the period 2010–2019. A total of 255 articles were abstracted from the Scopus database. Then, the VOSviewer program was employed to visualize the research status from the perspectives of scholars, countries/regions, journals, articles, and co-occurring keywords. Results revealed that Wang X. published the greatest number of articles, while Cheng J.C.P. received the greatest average normalized citations. Furthermore, Automation in Construction was identified as the most influential journal and the article “Building information modeling (BIM): trends, benefits, risks, and challenges for the AEC industry” was the most cited paper. Through the keywords co-occurrence analysis, “virtual reality” and “visual programming language” were identified as the emerging themes in this field. The research findings can provide both researchers and practitioners with a better understanding of the status quo and trends of the BIM-based visualization research.

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BIM-Based Construction Noise Hazard Prediction and Visualization for Occupational Safety and Health Awareness Improvement

Cited by 12 publications

References 11 publications

Literature Review of Digital Twins Applications in Construction Workforce Safety

Literature Review of Digital Twins Applications in Construction Workforce Safety

Current States and Future Trends in Safety Research of Construction Personnel: A Quantitative Analysis Based on Social Network Approach

BIM-Based Visualization Research in the Construction Industry: A Network Analysis

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