Evaluating Construction Workers’ Understanding of Safety Signs

2013 ◽  
Vol 291-294 ◽  
pp. 3024-3027 ◽  
Author(s):  
Gwang Hee Kim ◽  
Seok Hoon Nam ◽  
Sang Jun Hwang ◽  
Hee Bok Choi ◽  
Yoon Seok Shin

It has been suggested that many construction workers are never properly educated on the meaning of safety signs. In particular, considering that any safety accident can lead directly to a serious disaster, understanding safety signs is a critical part of safety management. Therefore, the purpose of this study is to analyze construction workers’ awareness of and understanding of safety signs. The research found that most construction workers perceived that safety signs play an important role in preventing safety accidents. However, almost half of construction workers did not understand what construction safety signs convey, which indicates an urgent need for education on safety signs at construction sites.

2018 ◽  
Vol 7 (1) ◽  
pp. 80-100 ◽  
Author(s):  
Muhammad Arslan ◽  
Christophe Cruz ◽  
Ana-Maria Roxin ◽  
Dominique Ginhac

Purpose The purpose of this paper is to improve the safety of construction workers by understanding their behaviors on construction sites using spatio-temporal (ST) trajectories. Design/methodology/approach A review of construction safety management literature and international occupational health and safety statistics shows that the major reasons for fatalities on construction sites are mobility-related issues, such as unsafe human behaviors, difficult site conditions, and workers falling from heights and striking against or being struck by moving objects. Consequently, literature has been reviewed to find possible technological solutions to track the mobility of construction workers to reduce fatalities. This examination has suggested that location acquisition systems, such as Global Positioning System (GPS), have been widely used for real-time monitoring and tracking of workers on construction sites for hazard prevention. However, the raw data captured from GPS devices are generally available as discrete points and do not hold enough information to understand the workers’ mobility. As a solution, an application to transform raw GPS data into ST trajectories using different preprocessing algorithms is proposed for enhancing worker safety on construction sites. Findings The proposed system preprocesses raw GPS data for stay point detection, trajectory segmentation and intersection of multiple trajectories to find significant places and movements of workers on a construction site to enhance the information available to H&S managers for decision-making processes. In addition, it reduces the size of trajectory data for future analyses. Originality/value Application of location acquisition systems for construction safety management is very well addressed in the existing literature. However, a significant gap has been found: the usage of preprocessed ST trajectories is still missing in workers’ safety monitoring scenarios in the area of construction management. To address this research gap, the proposed system uses preprocessed ST trajectories to monitor workers’ movements on a construction site to identify potentially unsafe behaviors.


Author(s):  
Yikun Su ◽  
Shijing Yang ◽  
Kangning Liu ◽  
Kaicheng Hua ◽  
Qi Yao

Case-based reasoning (CBR) has been extensively employed in various construction management areas, involving construction cost prediction, duration estimation, risk management, tendering, bidding and procurement. However, there has been a dearth of research integrating CBR with construction safety management for preventing safety accidents. This paper proposes a CBR model which focuses on case retrieval and reuse to provide safety solutions for new problems. It begins with the identification of case problem attribute and solution attribute, the state of hazard is used to describe the problem attribute based on principles of people’s unsafe behavior and objective’s unsafe state. Frame-based knowledge representation method is adopted to establish the case database from dimensions of slot, facet and facet’s value. Besides, cloud graph method is introduced to determine the attribute weight through analyzing the numerical characteristics of expectation value, entropy value and hyper entropy value. Next, thesaurus method is employed to calculate the similarity between cases including word level similarity and sentence level similarity. Principles and procedures have been provided on case revise and case retain. Finally, a real-world case is conducted to illustrate the applicability and effectiveness of the proposed model. Considering the high potential for pre-control and decision-making of construction safety accident, the proposed model is expected to contribute safety managers to take decisions on prevention measures more efficiently.


Author(s):  
SungHun Kim ◽  
Changwon Wang ◽  
Se Dong Min ◽  
Seung-Hyun Lee

In the Korean construction industry, legal and institutional safety management improvements are continually being pursued. However, there was a 4.5% increase in the number of workers’ deaths at construction sites in 2017 compared to the previous year. Failure to wear safety helmets seems to be one of the major causes of the increase in accidents, and so it is necessary to develop technology to monitor whether or not safety helmets are being used. However, the approaches employed in existing technical studies on this issue have mainly involved the use of chinstrap sensors and have been limited to the problem of whether or not safety helmets are being worn. Meanwhile, improper wearing, such as when the chinstrap and harness fixing of the safety helmet are not properly tightened, has not been monitored. To remedy this shortcoming, a sensing safety helmet with a three-axis accelerometer sensor attached was developed in this study. Experiments were performed in which the sensing data were classified whether the safety helmet was being worn properly, not worn, or worn improperly during construction workers’ activities. The results verified that it is possible to differentiate among wearing status of the proposed safety helmet with a high accuracy of 97.0%


2020 ◽  
Vol 2 (1) ◽  
pp. 68-74
Author(s):  
Om Prakash Giri

 The Construction industry is prone to risk to health and safety hazards. Construction workers should have the knowledge of health and safety and apply the knowledge while working. The main objective of this paper was to review and to identify the factors that cause accidents at construction sites and the methods to improve health and safety. The review revealed that lack of awareness about site safety and negligence of workers in wearing Personal Protective Equipment (PPE) were the main causes of poor safety practices. It is necessary to create employer’s and contractor’s interests in safety management and enhance awareness on possible risk factors to reduce these risk factors among workers. Effective implementation of training and safety awareness programs among construction workers is vital to improve health and safety of construction workers.


The construction industry plays a prominent part in the progress of a country socially and economically. Nowadays construction industry has grown profit driven and the management focuses more on completing the projects on time neglecting safety of the workers. Construction works involving intricate works leading to accidents or injuries resulting in loss of life and body parts are rampant. So a proper safety management system is required to avoid accidents and improve safety at construction sites. Factors affecting safety at construction workplaces were identified and was surveyed through a quantitative questionnaire and analysed to form a basis for the total construction safety management model. The Total Construction Safety Management (TCSM) based on the PDCA modelling is proposed to improve safety at construction sites. This model can act as a guide to the present organizations and helps them to implement safety in quicker manner at construction site.


2020 ◽  
Vol 12 (13) ◽  
pp. 5430
Author(s):  
Ji-Myong Kim ◽  
Kiyoung Son ◽  
Sang-Guk Yum ◽  
Sungjin Ahn

This study analyzed the relative risks of migrant workers, and identified risk factors based on quantitative data for the systematic safety management of migrant workers. Many studies have found that migrant workers are more vulnerable to safety accidents than non-migrant workers. Nevertheless, there are few quantitative studies of migrant workers’ accident-risk in the construction industry, where safety accidents are most frequent. In addition, safety management for the identified accident risk factors has not been implemented systematically. To fill the gap, this study uses safety accident data from construction sites, from the +, for the methodical safety management of migrant workers. The t-test and multiple regression analysis methods are used to define the variance in non-migrant and migrant workers, and the risk indicators, respectively. The two analyses show that the results for migrant construction workers were 2.2% higher in safety accident severity than non-migrant workers, and significant factors are also different. This study’s results will provide critical guidance for the safety management of migrant construction workers.


2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Tingshen Zhao ◽  
Seyed Ebrahim Kazemi ◽  
Wen Liu ◽  
Miao Zhang

To deepen the understanding of the construction safety accidents rules as well as identify and cure the crux of construction safety management failures in China, we analyzed the status quo of safety management and identified the “last mile” problem, that is, the failure of implementation of the extensive legal and regulatory systems on the construction site. The safety factors were then extracted based on a questionnaire consisting of 34 items. Through factor analysis and ranking correlation, five human factors were found to be the greatest challenge and leverage point of safety management at construction sites. Accordingly, a novel safety management framework was proposed and tested as part of the Wuhan-Shenzhen highway project. Expert auditing confirmed that the proposed framework could substantially improve the construction safety performance and thus bridge the “last mile” of safety management implementation.


2018 ◽  
Vol 8 (12) ◽  
pp. 2400 ◽  
Author(s):  
Sung Hun Kim ◽  
Changwon Wang ◽  
Se Dong Min ◽  
Seung Hyun Lee

In the Korean construction industry, legal and institutional safety management improvements are continually being pursued. However, there was a 4.5% increase in the number of workers’ deaths at construction sites in 2017 compared to the previous year. Failure to wear safety helmets seems to be one of the major causes of the increase in accidents, and so it is necessary to develop technology to monitor whether or not safety helmets are being used. However, the approaches employed in existing technical studies on this issue have mainly involved the use of chinstrap sensors and have been limited to the problem of whether or not safety helmets are being worn. Meanwhile, improper wearing, such as when the chinstrap and harness fixing of the safety helmet are not properly tightened, has not been monitored. To remedy this shortcoming, a sensing safety helmet with a three-axis accelerometer sensor attached was developed in this study. Experiments were performed in which the sensing data were classified whether the safety helmet was being worn properly, not worn, or worn improperly during construction workers’ activities. The results verified that it is possible to differentiate among wearing status of the proposed safety helmet with a high accuracy of 97.0%.


2019 ◽  
Vol 11 (5) ◽  
pp. 1264 ◽  
Author(s):  
Zhipeng Zhou ◽  
Chaozhi Li ◽  
Chuanmin Mi ◽  
Lingfei Qian

Construction project management usually has a high risk of safety-related accidents. An opportunity to proactively improve safety performance is with near-miss information, which is regarded as free lessons for safety management. The research status and practice; however, presents a lack of comprehensive understanding on what near-miss information means within the context of construction safety management. The objective of this study is to fill in this gap. The main findings enrich the comprehensive understanding of the near-miss definition, the near-miss causation model, and the process of near-miss management. Considering that near-misses are more tacit and obscure than accidents, the process for near-miss management involves eight stages: discovery, reporting, identification, prioritization, causal analysis, solution, dissemination, and evaluation. The first three stages aim to make near-misses explicit. The other five are adopted to better manage near-miss information, compiled in a well-designed near-miss database (NMDB). Finally, a case study was conducted to show how near-miss information can be utilized to assist in construction safety management. The main potential contributions here are twofold. Firstly, corresponding findings provide a knowledge framework of near-miss information for construction safety researchers who can go on to further study near-miss management. Secondly, the proposed framework contributes to the guidance and encouragement of near-miss practices on construction sites.


2013 ◽  
Vol 438-439 ◽  
pp. 1702-1705
Author(s):  
Li Shuai ◽  
Hong Li

With the rapid development of construction industry progress, construction safety is paid more attention by more and more people. At present, construction safety has become the main problem which restricted the construction industrys development. It not only reflects construction enterprises management level, but also the economic efficiency of enterprises. Therefore, adopting prevention measures about construction industry is worth researching and discussing. This paper introduces the present situation of safety management in construction sites, then analyses the major safety management problems. Finally, it pertinently advances effective countermeasures on the basis of Safety First, Prevention First, Comprehensive Treatment to achieve the aim at reducing the construction safety accident rate to the greatest extent.


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