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

Rey-Merchán, María del Carmen; Gómez-de-Gabriel, Jesús M.; López-Arquillos, Antonio; Fernández-Madrigal, Juan A.

doi:10.3390/ijerph18136839

Cited by 11 publications

(7 citation statements)

References 61 publications

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“…Regarding the implementation of IoT into the construction safety domain, Rey-Merchán et al [ 19 ] proposed a virtual fence system based on Bluetooth Low Energy (BLE) beacon technology to avoid the intrusion of workers into hazardous areas. The designed system was then evaluated by a structured questionnaire distributed to the industry experts.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Tabatabaee

Mohandes

Ahmed

et al. 2022

IJERPH

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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.

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Section: Literature Reviewmentioning

confidence: 99%

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

Tabatabaee

Mohandes

Ahmed

et al. 2022

IJERPH

View full text Add to dashboard Cite

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“…Most of the work done is in the testing phase (Yeo et al, 2020). These studies have generally focused on the use of IoT for accident prevention (Rey-Merch an et al, 2021;Yang et al, 2020;Yeo et al, 2020) and hazard identification (Costin et al, 2019;Li et al, 2018;Thirugnanasammandamoorthi and Choi, 2021) in construction safety.…”

Section: Internet Of Things (Iot)mentioning

confidence: 99%

Investigating the impact of emerging technologies on construction safety performance

Dobrucali

Demirkesen

Sadikoglu

et al. 2022

ECAM

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PurposeConstruction safety is heavily affected by using new technologies in this growing trend of technology adoption. Especially, safety performance is enhanced through the utilization of some effective technologies such as artificial intelligence, virtual reality, BIM and wearable devices. Therefore, the main purpose of this study is to investigate the influence of emerging technologies on construction safety performance and quantify the relationship between those. The proposed components of emerging technologies are BIM, GIS, VR, RFID, AI, ML, eye tracking and serious games and wearable devices, whereas the dimensions of construction safety performance are safety planning, safety training, safety inspection and monitoring, safety audits and reviews and safety leadership.Design/methodology/approachA structural model was composed consisting of emerging technologies and safety performance indicators. Then, a questionnaire was designed and administered to construction professionals, and data from 167 projects were analyzed using structural equation modeling. The data were analyzed by using software, called SPSS AMOS.FindingsThe analysis of the structural model proves that there is a positive and significant relationship between emerging technologies and construction safety performance. Moreover, the factor loadings for each factor were found to be high indicating a good representation of the construct by the components developed. Among the technologies, BIM, robotics and automation, AI and wearable devices were detected to be the most significant technologies in terms of impacting safety performance.Originality/valueThe study contributes to the body of knowledge in that it develops a conceptual framework consisting of specific technologies in terms of emerging technologies, reveals the impact of such technologies on safety performance and proposes several tools and strategies for enabling effective safety management along the project lifecycle. Industry practitioners may benefit from the framework developed by adopting such technologies to enhance their safety performance on construction projects.

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“…This condition is subjective [12] and therefore, in order to properly assess it, multiple efforts have been made on translating self-assessment questionnaires [13] and harmonizing health and safety scales [14]. Alternatively, more modern, artificial intelligence (AI)-based proposals are capable of the following: improving safety in construction sites using internet of things (IoT) technology [15]; predicting injury outcomes and number of days away from work [16]; analyzing thermal protective and thermophysiological comfort performance of fabrics [17]; and protecting workers health, safety and well-being [18].…”

Section: Introductionmentioning

confidence: 99%

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

Ramírez-Moreno

Carrillo-Tijerina

Candela-Leal

et al. 2021

IJERPH

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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.

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

Cited by 11 publications

References 61 publications

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

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

Investigating the impact of emerging technologies on construction safety performance

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

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