Virtual Fence System Based on IoT Paradigm to Prevent Occupational Accidents in the Construction Sector

Digital Innovations for Occupational Safety: Empowering Workers in Hazardous Environments

BACKGROUND

The quest to increase safety awareness, make job sites safer, and promote decent work for all has led to the utilization of digital technologies in hazardous occupations. This study investigated the use of digital innovations for safety and health management in hazardous industries. The key challenges and recommendations associated with such use were also explored.

METHOD

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, a total of 48 studies were reviewed to provide a framework for future pathways for the effective implementation of these innovations.

FINDINGS

The results revealed four main categories of digital safety systems: wearable-based systems, augmented/virtual reality-based systems, artificial intelligence-based systems, and navigation-based systems. A wide range of technological, behavioral, and organizational challenges were identified in relation to the key themes.

CONCLUSION

Outcomes from this review can inform policymakers and industrial decision-makers about the application of digital innovations for best safety practices in various hazardous work conditions.

Prevention of Falls from Heights in Construction Using an IoT System Based on Fuzzy Markup Language and JFML

The main cause of fatal accidents in the construction sector are falls from height (FFH) and the inappropriate use of a harness is commonly associated with these fatalities. Traditional methods, such as onsite inspections, safety communication, or safety training, are not enough to mitigate accidents caused by FFH associated with a poor management in the use of a harness. Although some technological solutions for the automated monitoring of workers could improve safety conditions, their use is not frequent due to the particularities of construction sites: complexity, dynamic environments, outdoor workplaces, etc. Then, the integration of expert knowledge with technology is a key issue. Fuzzy logic systems (FLS) and Internet of Things (IoT) present many potential benefits, such as real-time decisions being made based on FLS and data from sensors. In the current research, the development and test of an IoT system integrated with the Java Fuzzy Markup Language Library for FLS, to support experts’ decision making in FFH, is proposed. The proposal was checked in four construction scenarios based on working conditions with different levels of risk of FFH and obtained promising results.

Investigating the Barriers to Applying the Internet-of-Things-Based Technologies to Construction Site Safety Management

The utilization of Internet-of-Things (IoT)-based technologies in the construction industry has recently grabbed the attention of numerous researchers and practitioners. Despite the improvements made to automate this industry using IoT-based technologies, there are several barriers to the further utilization of these leading-edge technologies. A review of the literature revealed that it lacks research focusing on the obstacles to the application of these technologies in Construction Site Safety Management (CSSM). Accordingly, the aim of this research was to identify and analyze the barriers impeding the use of such technologies in the CSSM context. To this end, initially, the extant literature was reviewed extensively and nine experts were interviewed, which led to the identification of 18 barriers. Then, the fuzzy Delphi method (FDM) was used to calculate the importance weights of the identified barriers and prioritize them through the lenses of competent experts in Hong Kong. Following this, the findings were validated using semi-structured interviews. The findings showed that the barriers related to “productivity reduction due to wearable sensors”, “the need for technical training”, and “the need for continuous monitoring” were the most significant, while “limitations on hardware and software and lack of standardization in efforts,” “the need for proper light for smooth functionality”, and “safety hazards” were the least important barriers. The obtained findings not only give new insight to academics, but also provide practical guidelines for the stakeholders at the forefront by enabling them to focus on the key barriers to the implementation of IoT-based technologies in CSSM.

Evaluation of a Fast Test Based on Biometric Signals to Assess Mental Fatigue at the Workplace-A Pilot Study

Non-pathological mental fatigue is a recurring, but undesirable condition among people in the fields of office work, industry, and education. This type of mental fatigue can often lead to negative outcomes, such as performance reduction and cognitive impairment in education; loss of focus and burnout syndrome in office work; and accidents leading to injuries or death in the transportation and manufacturing industries. Reliable mental fatigue assessment tools are promising in the improvement of performance, mental health and safety of students and workers, and at the same time, in the reduction of risks, accidents and the associated economic loss (e.g., medical fees and equipment reparations). The analysis of biometric (brain, cardiac, skin conductance) signals has proven to be effective in discerning different stages of mental fatigue; however, many of the reported studies in the literature involve the use of long fatigue-inducing tests and subject-specific models in their methodologies. Recent trends in the modeling of mental fatigue suggest the usage of non subject-specific (general) classifiers and a time reduction of calibration procedures and experimental setups. In this study, the evaluation of a fast and short-calibration mental fatigue assessment tool based on biometric signals and inter-subject modeling, using multiple linear regression, is presented. The proposed tool does not require fatigue-inducing tests, which allows fast setup and implementation. Electroencephalography, photopletismography, electrodermal activity, and skin temperature from 17 subjects were recorded, using an OpenBCI helmet and an Empatica E4 wristband. Correlations to self-reported mental fatigue levels (using the fatigue assessment scale) were calculated to find the best mental fatigue predictors. Three-class mental fatigue models were evaluated, and the best model obtained an accuracy of 88% using three features, β/θ (C3), and the α/θ (O2 and C3) ratios, from one minute of electroencephalography measurements. The results from this pilot study show the feasibility and potential of short-calibration procedures and inter-subject classifiers in mental fatigue modeling, and will contribute to the use of wearable devices for the development of tools oriented to the well-being of workers and students, and also in daily living activities.

Suggestion of an Improved Evaluation Method of Construction Companies' Industrial Accident Prevention Activities in South Korea

Workers in the construction industry are constantly exposed to dangers during work that can lead to death or disability. Despite recent advances in construction technology, the presence of these risks for workers has become an unresolved social problem. In particular, most companies often recognize that it is necessary to mitigate against risks posed to worker only after an accident has occurred. Recently, there has been an increasing demand for the development of new safety technologies and policy proposals to ensure the safety of workers during construction or work. However, the right solution is not coping after an accident but preventing it, and this must be accompanied by voluntary efforts by the company. To work toward such solutions, Korea is implementing an evaluation of construction companies’ industrial accident prevention activities without legal regulations or coercion to encourage voluntary accident prevention activities by companies. The purpose of this study is to propose an effective improvement direction for the system implemented by the Korea Occupational Safety and Health Agency. First, by analyzing the details of the system and the data of the evaluation results, the system’s effectiveness and rationality are reviewed, and steps for improvement are determined. Next, an evaluation model is proposed considering the size of the company to be evaluated and the level of safety and health, and its validity is verified through a survey of construction workers. Finally, a plan to induce the voluntary participation of construction companies in this system and the role of the supervisory authority are presented. This study is expected to serve as an important example of an effective safety policy model by encouraging companies’ voluntary efforts to prevent accidents in the construction industry and raise the level of potential safety and health awareness.