• Journal of the Korea Society of Computer and Information
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• v.23 no.2
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• pp.63-70
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• 2018

Safety management agent manages the risk behavior of the worker with the naked eye, but there is a real difficulty for one the agent to manage all the workers. In this paper, IoT device is attached to a harness safety belt that a worker wears to solve this problem, and behavior data is upload to the cloud in real time. We analyze the upload data through the deep learning and analyze the risk behavior of the worker. When the analysis result is judged to be dangerous behavior, we designed and implemented a system that informs the manager through monitoring application. In order to confirm that the risk behavior analysis through the deep learning is normally performed, the data values of 4 behaviors (walking, running, standing and sitting) were collected from IMU sensor for 60 minutes and learned through Tensorflow, Inception model. In order to verify the accuracy of the proposed system, we conducted inference experiments five times for each of the four behaviors, and confirmed the accuracy of the inference result to be 96.0%.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.91-98
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• 2019

Accidents of worker that occur in isolated places are difficult to rescue, unlike general construction accidents. There is a problem of communication limitation when an accident occurs in an isolated place. Also, it is difficult to search the accident place due to the absence of CCTV. In order to solve these problems, this paper proposes a device that combines IoT technology with a safety helmet, which must be worn in the workplace. The proposed device additionally designs and implements a real-time PPG(Photoplethysmography) sensor, body temperature sensor, accelerometer sensor and a camera sensor on the helmet. The proposed helmet system allows the user and the control center to monitor the state of the worker. In addition, when an abnormal biological signal or fall occurs to the worker, the image is transmitted to the control center. By using the proposed system, it is possible to check the status of the worker in real time, so that it has an advantage that it can cope with the accident quickly.

• Journal of Platform Technology
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• v.11 no.6
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• pp.79-88
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• 2023

Recently, industrial accidents have continued to increase due to the industrialization, and worker safety management is recognized as essential to reduce losses due to hazardous factors at work places. To manage the safety of workers, it is required to apply customized safety management artificial intelligence technology that takes into account the characteristics of industrial sites, and a service for real-time risk detection and response to workers depending on the situation based on safety accident types and risk analysis for each task and process. The proposed safety management service consists of worker devices to acquire sensor data, edge devices to collect from IoT-based sensors, and a voice chatbot to support workers' disaster response. The voice chatbot plays a major role in interacting with workers at disaster sites to respond to risks. This paper focuses on real-time risk response using an IoT-based system and voice chatbot on a server for work safety according to the worker's situation. A Scenario-based voice chatbot is used to process responses at the edge level to provide safety management services.

• Journal of Drive and Control
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• v.19 no.4
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• pp.62-69
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• 2022

Construction machinery is exposed to accidents such as collisions, narrowness, and overturns during operation. In particular, mobile crane is operated only with the driver's vision and limited information of the assistant worker. Thus, there is a high risk of an accident. Recently, some collision avoidance device using sensors such as cameras and LiDAR have been applied. However, they are still insufficient to prevent collisions in the omnidirectional 3D space. In this study, a rotating LiDAR device was developed and applied to a 250-ton crane to obtain a full-space point cloud. An algorithm that could provide distance information and safety status to the driver was developed. Also, deep-learning segmentation algorithm was used to classify human-worker. The developed device could recognize obstacles within 100m of a 360-degree range. In the experiment, a safety distance was calculated with an error of 10.3cm at 30m to give the operator an accurate distance and collision alarm.

• Smart Media Journal
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• v.12 no.3
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• pp.120-128
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• 2023

There are various ICT technologies continuously being developed to reduce damage by industrial accidents. And research is being conducted to minimize damage in case of industrial accidents by utilizing sensors, IoT, big data, machine learning and artificial intelligence. In this paper, we propose a design method for a smart device capable of multilateral communication between devices and smart repeater in the communication shaded Areas such as closed areas of industrial sites, mountains, oceans, and coal mines. The proposed device collects worker's information such as worker location and movement speed, and environmental information such as terrain, wind direction, temperature, and humidity, and secures a safe distance between workers to warn in case of a dangerous situation and is designed to be attached to a helmet. For this, we proposed functional requirements for smart devices and design methods for implementing each requirement using sensors and modules in smart device. And we derived evaluation items for performance evaluation of the smart device and proposed an evaluation environment for performance evaluation in mountainous area.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.20-25
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• 2015

It is predicted the mass retirement of the post-war generation and the lack of young people according to reduces the recruitment. Therefore, industry fields are concerned by the low level of occupational safety and health from issued problem in a variety of industries; the charge of expanding business range/multi-functional, black box of technology, difficulty of systematic training, relative decrease in the skill of workers, loss of know-how in the field of information followed restricted site information. In response to these problems, it is necessary to establish the long-termly and actively based on for the adoption of a safety and health management techniques utilizing IT, which is digital assistant(tablet PC, PDA, etc.), RFID/USN/ICT, database systems, and etc. In this study, we developed and evaluated a worker's safety sensing apparatus using smart phone. The apparatus may be useful to prevent accidents in the construction industry as well as confined space work.

• KDI Journal of Economic Policy
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• v.38 no.2
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• pp.87-101
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• 2016

A person's life consists of two important stages: the first stage as a student and the second stage as a worker. In an integrated model of education and career concerns, I analyze the welfare effects of education. In Spence's job market signaling model, education as a sorting device improves efficiency by mitigating the lemon market problem. In contrast, in the integrated model, education as a sorting device can be detrimental to social welfare, as it eliminates work incentives generated by career concerns.

• Korean Journal of Digital Imaging in Medicine
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• v.12 no.1
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• pp.5-8
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• 2010

Opened a court in February 10, 2006, a rule of safety management of the diagnosis radiation system was promulgated for safety of the radiation worker, patients and patients' family members. The purpose of this rule is to minimize the risk of being exposed to radiation during the process of handling X-ray. For this reason, we manufactured shielding device of mobile X-ray unit collimator for diminution of skin dose. Shielding device is made to a thickness of Pb 0.375mm. For portable chest radiography, we measured skin dose 50cm from center ray to 200cm at intervals of 20cm by Unfors Xi detector. As a result, a rule of safety management of the diagnosis radiation system has been strengthened. But there are exceptions, such as ER, OR, ICU to this rule. So shielding device could contribute to protect unnecessary radiation exposure and improve nation's health.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.11
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• pp.78-83
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• 2010

Since a tower crane is too high for a worker to ascend and by the wind in the high altitude, the possibility of a safety accident is very high, a lift assist is used. In this study, the hydraulic fall prevention device using the pressure generation device by Seok, et al. was developed. For this, the effects on the fall prevention performances of factors such as gear clearance, oil viscosity, rotative velocity and so on were evaluated by the analysis of fluid flow using FEM and the prototype was producted and a function test was performed.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.05a
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• pp.123-124
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• 2019

In the labor-intensive construction site, potential threats of the musculoskeletal diseases mainly caused by various repetitive physical tasks, vulnerable environment, and the aging of the labor worker exist. However, quantitative measuring method of construction labor worker's work posture has not been improved yet. This study proposed musculoskeletal measuring method by using wearable motion recognition sensor for quantitative evaluation and analysis of working posture of construction workers. This method is expected to be used as a basic data for posture analysis and prevention construction safety accidents, as well as physical workload and labor productivity analysis by labor work type.