• Title/Summary/Keyword: Worker Falling

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A Study on Falling Detection of Workers in the Underground Utility Tunnel using Dual Deep Learning Techniques (이중 딥러닝 기법을 활용한 지하공동구 작업자의 쓰러짐 검출 연구)

  • Jeongsoo Kim;Sangmi Park;Changhee Hong
    • Journal of the Society of Disaster Information
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    • v.19 no.3
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    • pp.498-509
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    • 2023
  • Purpose: This paper proposes a method detecting the falling of a maintenance worker in the underground utility tunnel, by applying deep learning techniques using CCTV video, and evaluates the applicability of the proposed method to the worker monitoring of the utility tunnel. Method: Each rule was designed to detect the falling of a maintenance worker by using the inference results from pre-trained YOLOv5 and OpenPose models, respectively. The rules were then integrally applied to detect worker falls within the utility tunnel. Result: Although the worker presence and falling were detected by the proposed model, the inference results were dependent on both the distance between the worker and CCTV and the falling direction of the worker. Additionally, the falling detection system using YOLOv5 shows superior performance, due to its lower dependence on distance and fall direction, compared to the OpenPose-based. Consequently, results from the fall detection using the integrated dual deep learning model were dependent on the YOLOv5 detection performance. Conclusion: The proposed hybrid model shows detecting an abnormal worker in the utility tunnel but the improvement of the model was meaningless compared to the single model based YOLOv5 due to severe differences in detection performance between each deep learning model

A Case Study on the Serious Accidents of Construction (건설중대재해 사례 연구)

  • 장동일;이명구
    • Journal of the Korean Society of Safety
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    • v.11 no.1
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    • pp.108-120
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    • 1996
  • It is a problems in industrial accidents that the knowledge for industrial accidents is obtained by experience, not by experiment. This experiential knowledge is obtained by Investigating accident cases and utilizing those for safety education. Therefore, in this paper, the situation about the serious accident of construction is analyzed by occupation, a kind of construction, time group, season, type of accident, and accidental cause. And the mutual · relations of these factors are studied. The most frequent type of the serious accidents of construction Is the falling accident. It happenes most frequently at apartment construction among kinds of construction and to structural worker, finishing worker, normal worker in order among occupations. And it is found that the most critical causes of the falling accident are the imperfection of safety facilities and unwearing of protection equipments, so a number of accidents can be reduced by the expansion of safety facilities and wearing of protection equipments absolutely. The counterplan of prohibition of accidents and the direction of government policy are presented by a series of nalyses for accident cases.

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A Systems Engineering Approach to Development of a Worker's Location Monitoring System in Ship and Offshore Plant (선박 및 해양플랜트 환경에서 작업자 위치 모니터링 시스템 개발을 위한 시스템엔지니어링 접근 방법)

  • Park, Jong Hee;Kim, Han June;Yoon, Jae Jun;Kim, Hyoung Min;Hong, Dae Geun
    • Journal of the Korean Society of Systems Engineering
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    • v.16 no.1
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    • pp.68-77
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    • 2020
  • The shipbuilding and offshore industry is a large and complex assembly industry, which causes many safety accidents. The major accidents in the shipbuilding and offshore industry workplaces are stenosis, falling objects, dust, fire, explosions, and gas poisoning. The accident by worker in this industry mainly has three factors: frequent movement, narrow work space, and increased use of subcontractors. To control these factors, it is necessary to monitor the worker's location and work status. In this paper, a worker location monitoring system using inaudible sound wave was designd that can be used in environments with many metal barriers. The process included deriving stakeholder requirements, transforming to system requirements, designing system architecture, and developing prototype. The prototype was validated by third-party testing agency. As a result, it satisfied the designed performance and verified its feasibility.

Evaluation of Balance Capability in Facilities Maintenance Workers using Screening Tools (스크리닝 도구를 이용한 건물관리업 종사자의 균형감각능력 평가)

  • Choi, Hyung Jin;Kim, Jung Soo
    • Journal of the Korea Safety Management & Science
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    • v.16 no.3
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    • pp.81-88
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    • 2014
  • A number of screening tools have been developed to evaluate the human balance capability. Many of them were designed to identify the elderly with falling risk. Three different screening tools, which have been well used many clinical fields, were used in this study. The purpose of this study was to evaluate balance capability in facilities maintenance workers in korea. There were no statistical significance between male and female when evaluated with three different screening tools. However, significant differences were found among the age groups irrespective of gender when evaluated with three different screening tools. The results of three different screening tools in korea showed poor values compared with previous results. These results revealed that facilities maintenance workers faced more critical falling risk in korea.

A Worker-Driven Approach for Opening Detection by Integrating Computer Vision and Built-in Inertia Sensors on Embedded Devices

  • Anjum, Sharjeel;Sibtain, Muhammad;Khalid, Rabia;Khan, Muhammad;Lee, Doyeop;Park, Chansik
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.353-360
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    • 2022
  • Due to the dense and complicated working environment, the construction industry is susceptible to many accidents. Worker's fall is a severe problem at the construction site, including falling into holes or openings because of the inadequate coverings as per the safety rules. During the construction or demolition of a building, openings and holes are formed in the floors and roofs. Many workers neglect to cover openings for ease of work while being aware of the risks of holes, openings, and gaps at heights. However, there are safety rules for worker safety; the holes and openings must be covered to prevent falls. The safety inspector typically examines it by visiting the construction site, which is time-consuming and requires safety manager efforts. Therefore, this study presented a worker-driven approach (the worker is involved in the reporting process) to facilitate safety managers by developing integrated computer vision and inertia sensors-based mobile applications to identify openings. The TensorFlow framework is used to design Convolutional Neural Network (CNN); the designed CNN is trained on a custom dataset for binary class openings and covered and deployed on an android smartphone. When an application captures an image, the device also extracts the accelerometer values to determine the inclination in parallel with the classification task of the device to predict the final output as floor (openings/ covered), wall (openings/covered), and roof (openings / covered). The proposed worker-driven approach will be extended with other case scenarios at the construction site.

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CONSTRUCTION LOST-TIME INJURIES IN LAOS: AN EXPLORATORY STUDY

  • Luu Truong Van;Soo-Yong Kim;Somsana T.K.P
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.229-238
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    • 2007
  • This paper presents a study on construction safety in the People Democratic Republic of Laos (PDRL). Fifty workers experienced certain injuries in their construction sites and 15 top managers were interviewed in twenty-six construction projects in Vientiane, the capital of PDRL. Research results show that stepping on and/or striking against objects (48%), struck by falling objects (24%), falling of persons (12%) are major types of construction injuries. The paper stresses that the ignorance of top managers about their crucial role in safety improvement, using safety incentive to raise safety performance, lack of thorough understanding about benefit from labor safety performance, and the willingness to cut off safety performance expenditures is considered as obstructions of safety improvement programs. The survey indicates that physical working conditions, relationship among workers, foremen behaviors and the monthly wage were influencing factors to worker's job satisfaction. The study also highlights afternoon as dominant time that led to a large number of injuries.

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Sickness absence and job satisfaction (직무만족도가 근로자의 질병결근에 미치는 영향 : 불건강증상 경험수의 조절효과)

  • Rhee, Kyung Yong;Park, Won Yeol
    • Journal of the Korea Safety Management & Science
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    • v.16 no.4
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    • pp.203-213
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    • 2014
  • Sickness absence is one of the most important indicators for worker's health and occupational safety and health performance. Sickness absence is primarily depended upon sickness but psycho-social factors in workplace may moderate sickness absence. Even though worker is falling into illness, sickness absence can be prevented by job satisfaction. In Korea it is very difficult to find research output about the association of sickness absence with job satisfaction. This study is planned to investigate the effect of job satisfaction on sickness absence. The third Korean Working Conditions Survey done by Occupational Safety and Health Research Institute in 2011 was used to analyze by logistic regression analysis. The result has shown that job satisfaction has statistically significant effect on sickness absence and simultaneously diminish the effect of symptoms experience on sickness absence. The effect of job satisfaction is greater in short term sickness absence than in long term sickness absence. This study has some limitation because of the cross sectional data of Korean Working Conditions Survey. In future, sophisticated statistical analysis may be done with modelling.

Investigation & Analysis about fatalities of falls from height at construction work (건설현장(建設現場) 추락(墜落) 사망재해(死亡災害) 원인(原因) 조사(調査) 분석(分析))

  • Ko, Young-Wook;Kim, Dong-Ryeong;Cho, Joung-Ho;Kang, Kyung-Sik
    • Journal of the Korea Safety Management & Science
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    • v.14 no.3
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    • pp.49-57
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    • 2012
  • Proportion of falling from height accident at construction work accounts for more than 40%, and the number of injuries is getting increased. So without considering falling from height, we can say that it's hard to achieve our goal(accident prevention). Another critical point that we have to think about theses days is the fact that construction workers are getting older. To be specific, the number of workers who are above 50 years old accounts for 65.6% among the fatalities(2007~2011, KOSHA inspection). Accordingly, to effectively prevent construction accedents, especially falls from height, we need to focus on motion analysis of older construction workers and then make suitable measures for growing accident rates at construction work.

Accuracy Analysis of Construction Worker's Protective Equipment Detection Using Computer Vision Technology (컴퓨터 비전 기술을 이용한 건설 작업자 보호구 검출 정확도 분석)

  • Kang, Sungwon;Lee, Kiseok;Yoo, Wi Sung;Shin, Yoonseok;Lee, Myungdo
    • Journal of the Korea Institute of Building Construction
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    • v.23 no.1
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    • pp.81-92
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    • 2023
  • According to the 2020 industrial accident reports of the Ministry of Employment and Labor, the number of fatal accidents in the construction industry over the past 5 years has been higher than in other industries. Of these more than 50% of fatal accidents are initially caused by fall accidents. The central government is intensively managing falling/jamming protection device and the use of personal protective equipment to eradicate the inappropriate factors disrupting safety at construction sites. In addition, although efforts have been made to prevent safety accidents with the proposal of the Special Act on Construction Safety, fatalities on construction sites are constantly occurring. Therefore, this study developed a model that automatically detects the wearing state of the worker's safety helmet and belt using computer vision technology. In considerations of conditions occurring at construction sites, we suggest an optimization method, which has been verified in terms of the accuracy and operation speed of the proposed model. As a result, it is possible to improve the efficiency of inspection and patrol by construction site managers, which is expected to contribute to reinforcing competency of safety management.

Comparison of Deep Learning Based Pose Detection Models to Detect Fall of Workers in Underground Utility Tunnels (딥러닝 자세 추정 모델을 이용한 지하공동구 다중 작업자 낙상 검출 모델 비교)

  • Jeongsoo Kim
    • Journal of the Society of Disaster Information
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    • v.20 no.2
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    • pp.302-314
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    • 2024
  • Purpose: This study proposes a fall detection model based on a top-down deep learning pose estimation model to automatically determine falls of multiple workers in an underground utility tunnel, and evaluates the performance of the proposed model. Method: A model is presented that combines fall discrimination rules with the results inferred from YOLOv8-pose, one of the top-down pose estimation models, and metrics of the model are evaluated for images of standing and falling two or fewer workers in the tunnel. The same process is also conducted for a bottom-up type of pose estimation model (OpenPose). In addition, due to dependency of the falling interference of the models on worker detection by YOLOv8-pose and OpenPose, metrics of the models for fall was not only investigated, but also for person. Result: For worker detection, both YOLOv8-pose and OpenPose models have F1-score of 0.88 and 0.71, respectively. However, for fall detection, the metrics were deteriorated to 0.71 and 0.23. The results of the OpenPose based model were due to partially detected worker body, and detected workers but fail to part them correctly. Conclusion: Use of top-down type of pose estimation models would be more effective way to detect fall of workers in the underground utility tunnel, with respect to joint recognition and partition between workers.