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Sensor-Integrated Hybrid Blockchain System for Supply Chain Coordination in Volumetric Modular Construction

Volumetric modular construction (VMC) needs streamlined supply chain coordination to achieve its full potential benefits, such as reduced schedule and cost, with consistent quality. Studies have noted that blockchain technology has significant potential for increasing the efficacy of supply chain coordination by providing reliable information sharing among VMC stakeholders. However, it is not well known how blockchain technology’s enhanced information sharing ultimately can lead to better supply chain coordination in VMC. To address this issue, we developed and tested a blockchain-based information collecting, storing, and sharing system with an automated contract execution method. A sensor-integrated decentralized application collects project information…

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Cross-platform virtual reality for real-time construction safety training using immersive web and industry foundation classes

Virtual reality (VR) has been studied extensively in the construction industry, particularly for safety training, as it is capable of simulating the hazardous areas of a construction site in a virtual environment that enables workers to visualize the real scenario before being introduced to job sites. However, at present, VR safety training requires specialized hardware and software, thus limiting worker access as only a few workers can participate in each training session. Therefore, this paper proposes a cross-platform framework based on Industry Foundation Classes (IFC) and WebXR (Immersive Web) for conveniently accessible VR safety training (CPVR) in the construction industry.…

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Artificial Intelligence-based Safety Helmet Recognition on Embedded Devices to Enhance Safety Monitoring Process

[PDF] from researchgate.net Authors Sharjeel Anjum, Syed Farhan Alam Zaidi, Rabia Khalid, Chansik Park Publication date 2022/9/13 Conference 2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pages 1-4 Publisher IEEE Description Construction workers can be adequately protected by wearing a safety helmet while working. Due to the discomfort, the workers take…

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Fall and Normal Activity Classification via Multiple Wearable Sensors

A fall detection and classification system is crucial for reducing the severe consequences of falls, which account for the leading cause of accidents on construction sites. Wearable sensors are one of the technologies used to detect falls. Although much academic work has been dedicated to the study of this class of systems, little attention has been paid to the evaluation of simpler algorithms prior to training on complex ones. This study utilizes the open-source UP Fall Detection Dataset and proposes that effective data processing and simpler baseline models give better results for fall-direction classification. Several data-processing techniques like windowing and…

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Digital twin-driven deep reinforcement learning for adaptive task allocation in robotic construction

In order to accomplish diverse tasks successfully in a dynamic (i.e., changing over time) construction environment, robots should be able to prioritize assigned tasks to optimize their performance in a given state. Recently, a deep reinforcement learning (DRL) approach has shown potential for addressing such adaptive task allocation. It remains unanswered, however, whether or not DRL can address adaptive task allocation problems in dynamic robotic construction environments. In this paper, we developed and tested a digital twin-driven DRL learning method to explore the potential of DRL for adaptive task allocation in robotic construction environments. Specifically, the digital twin synthesizes sensory…

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Computer Vision Process Development regarding Worker’s Safety Harness and Hook to Prevent Fall Accidents: Focused on System Scaffolds in South Korea

In South Korea, industrial accidents continue to increase in frequency, with construction accidents accounting for more than a third of all industrial accidents. Specifically, by preventing fall accidents, the death rate from accidents can be reduced by 50%. Fall protection is required to prevent fall accidents, and investigating the reinforcement of the worker’s safety harness and hook fastening becomes imperative. This requires automation of computer vision confirmation of the safety harness and hook fastening. As the accident risk can be reduced by an effective safety culture in the system, it is necessary to monitor safety on site through a construction…

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Fall Prevention from Scaffolding Using Computer Vision and IoT-Based Monitoring

Fall from height (FFH) is the most significant cause of occupational fatalities in the construction industry, accounting for approximately 54% of all accidents. Such fatalities have decreased considerably due to the use of personal protective equipment (PPE). However, the manual monitoring of compliance to PPE is complex and challenging for site managers. Automation in construction safety presents multiple solutions for monitoring safety at sites. In this study, a smart safety hook (SSH) monitoring method is proposed to eliminate the risk associated with FFH accidents by integrating computer vision [closed-circuit TV (CCTV)-imagery] and Internet-of-Things (IoT)-based [inertial measurement unit (IMU) IMU and…

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Leveraging Blockchain for Scaffolding Work Management in Construction

As a temporary facility, scaffolding has an essential role in providing a work environment at height in the construction industry. According to the Occupational Safety and Health Administration (OSHA), approximately 65% of laborers work on scaffolding. Scaffolding work information needs to be effectively managed with reliability to provide a safe environment. However, managing information of the scaffolding work process remains challenging in forgery risk and manual verification. Blockchain has been widely introduced as an accountable and efficient information management solution. This study presents a blockchain-based system for scaffolding work to grant reliability and efficiency of information management. The system is…

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Fall Prevention From Ladders Utilizing a Deep Learning-Based Height Assessment Method

According to the Center for Construction Research and Training (CPWR) and the Korea Occupational Safety & Health Agency (KOSHA), falls from ladders are a leading cause of fatalities. The current safety inspection process to enforce height-related rules is manual and time-consuming. It requires the physical presence of a safety manager, for whom it is sometimes impossible to monitor an entire area in which ladders are being used. Deep learning-based computer vision technology has the potential to capture a large amount of useful information from a digital image. Therefore, this paper presents a deep learning-based height assessment method using a single…

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Tag and IoT based safety hook monitoring for prevention of falls from height

Monitoring the unsafe behavior of construction workers at risky elevations is essential for eliminating fall from height (FFH) accidents. This study aims to bridge the gap between technological advancements and their application in the construction industry by introducing real-time hybrid vision- and IoT-based systems for safety engineers to monitor the use of safety hooks at risky elevations in real-time. The proposed system for hybrid smart safety hooks (HSSH) integrates three components: 1) vision (AprilTag detection) and IoT sensors (IMU and Altimeter) based monitoring systems, 2) web-based management platform (WBMP), and 3) backend cloud server (BCS) storage system. The proposed system…

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Improving Augmentation Efficiency for Few-Shot Learning

While human intelligence can easily recognize some characteristics of classes with one or few examples, learning from few examples is a challenging task in machine learning. Recently emerging deep learning generally requires hundreds of thousands of samples to achieve generalization ability. Despite recent advances in deep learning, it is not easy to generalize new classes with little supervision. Few-shot learning (FSL) aims to learn how to recognize new classes with few examples per class. However, learning with few examples makes the model difficult to generalize and is susceptible to overfitting. To overcome the difficulty, data augmentation techniques have been applied…

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Generative planning for construction safety surveillance camera installation in 4D BIM environment

Surveillance cameras have become increasingly significant in the field of construction safety monitoring. With visual information, these cameras support safety managers to identify the potential hazards and deliver prompt feedback. However, developing the surveillance camera plan remains challenging in considering the workspace of working at height activities and the dynamic nature of the construction site. This study proposes a camera installation plan considering different site layouts with time during the optimization to resolve this problem. An approach for Generating Planning for Construction Safety Surveillance Camera Installation in 4D BIM Environment, called SCI4D. The SCI4D comprises three modules: The site profile…

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Rigorous analysis of safety rules for vision intelligence-based monitoring at construction jobsites

Construction safety rules play a vital role in mitigating accidents and fatalities at construction sites. Many researchers are currently devoted to monitoring the rule compliance using computer vision-based approaches; however, such systems are still not mature for application at construction job sites. A single autonomous source’s job-site safety control such as CCTV is a nontrivial task that requires a detailed analysis of safety rules for a work-stage based compact vision intelligence system. This paper proposes a grounded theory methodology (GTM) to systematically classify the safety rules for practical implementation using vision intelligence technology. The rules are classified into four groups…

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Blockchain-Based Network Concept Model for Reliable and Accessible Fine Dust Management System at Construction Sites

In total, 44.3% of particle matter 10 (PM10) is fugitive dust, and one of the main sources of fugitive dust generation in Korea is construction work (22%). Construction sites account for 84% of the total business places that have reported fugitive dust generation. Currently, the concentration of fine dust at construction sites is being remotely monitored by government inspection agencies through IoT sensors, but it is difficult to trust that appropriate fine dust reduction measures are being taken, because contractors can avoid taking these measures by submitting false reports or photos. In addition, since the fine dust monitoring system under…

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IMU based smart safety hook for fall prevention at construction sites

Fall from height (FFH) at the construction sites has the major portion of the total accidents; it may be due to traditional methods of monitoring at the site. For the site manager, manual monitoring is difficult, as some workers avoid wearing PPE at the risk area. To overcome this issue and eliminate the FFH accidents, a Smart Safety Hook (SSH) system is proposed. A preliminary experiment is carried out to record the kinematics and tilt angle of the safety hook from an IMU sensor in real-time through User Datagram Protocol (UDP) Communication. Machine learning algorithms (SVM, Naive Bayes, KNN, etc.)…

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Towards the adoption of vision intelligence for construction safety: Grounded theory methodology based safety regulations analysis

The construction safety rules play a vital role in mitigating accidents and fatalities at the construction site. Many researchers are currently devoted to monitoring the rule compliance using vision intelligence-based approaches; however, such systems are still not yet mature to be applied in construction job sites. A single autonomous source’s job site safety control is a non-trivial task that needs a detailed analysis of safety rules for a compact vision intelligence-based system development. This paper proposes Grounded Theory Methodology (GTM) to systematically classify the safety rules for implementation using vision intelligence technology. The rules are classified into four groups based…

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Utilizing safety rule correlation for mobile scaffolds monitoring leveraging deep convolution neural networks

Falls from height (FFH) are still a leading cause of fatalities in the construction industry, which also includes scaffolding-related accidents. Despite regular safety inspections, numerous scaffolding-related accidents occur at the construction site. The current safety monitoring practices are not only impractical but infeasible due to dynamicity of construction environment. Since a separate computer training and detection process is generally required to acquire spatiotemporal reasoning to control a single hazard; thus previous efforts in vision intelligence applications to improve safety monitoring are still limited to specific hazards. Also, in regard to detecting unsafe situations based on extracted correlations from safety rules,…

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Environmental particulate matter (pm) exposure assessment of construction activities using low-cost pm sensor and Latin hypercubic technique

Dust generation is generally considered a natural process in construction sites; ergo, workers are exposed to health issues due to fine dust exposure during construction work. The primary activities in the execution of construction work, such as indoor concrete and mortar mixing, are investigated to interrogate and understand the critical high particulate matter concentrations and thus health threats. Two low-cost dust sensors (Sharp GP2Y1014AU0F and Alphasense OPC N2) without implementing control measures to explicitly evaluate, compare and gauge them for these construction activities were utilized. The mean exposures to PM10, PM2.5 and PM1 during both activities were 3522.62, 236.46 and…

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Suggestions for Improving South Korea’s Fall Accidents Prevention Technology in the Construction Industry: Focused on Analyzing Laws and Programs of the United States

Since the enactment of the Occupational Safety and Health Act in 1981, the Korea Occupational Safety and Health Agency has endeavored to prevent fall accidents in the construction industry. However, many fatalities still occur in the South Korean construction industry. Meanwhile, the United States improved various systems and conducted studies to prevent fall accidents, significantly reducing such occurrences in the construction industry. The objective of this study is to present improvements to South Korea’s fall prevention technology by analyzing the laws and programs of the United States. To achieve this, this study has analyzed the United States’ fall prevention technology…

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Remote indoor construction progress monitoring using extended reality

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…

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