• Title/Summary/Keyword: Automated Construction.

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Collision Hazards Detection for Construction Workers Safety Using Equipment Sound Data

  • Elelu, Kehinde;Le, Tuyen;Le, Chau
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.736-743
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    • 2022
  • Construction workers experience a high rate of fatal incidents from mobile equipment in the industry. One of the major causes is the decline in the acoustic condition of workers due to the constant exposure to construction noise. Previous studies have proposed various ways in which audio sensing and machine learning techniques can be used to track equipment's movement on the construction site but not on the audibility of safety signals. This study develops a novel framework to help automate safety surveillance in the construction site. This is done by detecting the audio sound at a different signal-to-noise ratio of -10db, -5db, 0db, 5db, and 10db to notify the worker of imminent dangers of mobile equipment. The scope of this study is focused on developing a signal processing model to help improve the audible sense of mobile equipment for workers. This study includes three-phase: (a) collect audio data of construction equipment, (b) develop a novel audio-based machine learning model for automated detection of collision hazards to be integrated into intelligent hearing protection devices, and (c) conduct field experiments to investigate the system' efficiency and latency. The outcomes showed that the proposed model detects equipment correctly and can timely notify the workers of hazardous situations.

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Automated Optimum Design Program for Steel Box Girder Bridges (강상자형교의 자동화 최적설계 프로그램)

  • Cho, Hyo-Nam;Chung, Jee-Sung;Min, Dae-Hong
    • Journal of Korean Society of Steel Construction
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    • v.12 no.5 s.48
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    • pp.475-485
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    • 2000
  • In this study, an automated optimum design program for steel box girder bridges has been developed for the optimum design of composite steel box girder bridges. The design constraints required for the optimum design of steel box girder bridges are based on the Korean standard bridge specification. Considering characteristics of steel box girder bridges, several approximation techniques, such as artificial constraint deletion, variable linking and stress reanalysis technique etc. are also introduced to enhance the efficiency of optimization. The developed program is mainly composed of major sub-system modules including structural analysis module using commercial structural analysis program such as RM-SPACEFRAME, optimum design module, pre-process module for friendly user input, and post-processor module for office automation. In addition, in order to demonstrate the efficiency and applicability of the developed optimum design program for steel box girder bridges, a few numerical examples are applied. Based on the results of the application, it may be stated that the automatic optimum design program developed in this study can be a prototype model for the developement of optimum design program for other type of bridge.

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Development of an Automated Pavement Crack Sealing Machine and Its Economic Feasibility Analysis (크랙실링 자동화 장비의 개발 린 경제적 타당성 분석)

  • Lee, Jeong-Ho;Lee, Jun-Bok;Jeong, Hyung-Hoon;Kim, Young-Suk
    • Korean Journal of Construction Engineering and Management
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    • v.7 no.6
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    • pp.151-164
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    • 2006
  • Numerous efforts are currently underway to automate pavementcrack and joint sealing activities. Productivity improvements, improved safety and quality, and reduced road user costs motivate these developments. Recently, an automated pavement crack sealing machine has been developed to automate the process of sealing pavement cracks and joints in Korea. This paper mainly describes the results of the economic feasibility analysis revealed through its overall performance evaluation and field tests. Finally, it is concluded that the automated machine exceeds the performance in terms of productivity, safety, and quality required in conventional method, thus making the machine economically feasible.

Deformation Monitoring of Subway Track using by Automatic Measurement (자동화계측을 통한 지하철 궤도 변형 모니터링연구)

  • Jung-Youl Choi;Jae-Min Han
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.579-584
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    • 2024
  • Currently, large-scale, deep construction is being carried out adjacent to subway tracks in korea. when excavating adjacent to each other, it is very important to ensure the safety of earth retaining structures and underground structures. therefore, we are managing the safety of the subway by introducing an automated measurement system. deformation of the subway track during adjacent excavation may affect train running stability. this is a factor that can be linked to train derailments. however, current subway track safety evaluation using automated measurement systems relies only on the maximum value of measured data. therefore, a method to improve the usability of automated measurement system results is needed. in this study, we utilized a technique that can quantitatively evaluate the measurement results of a large amount of subway track deformation. a safety evaluation was conducted on subway track deformation due to adjacent excavation using a vast amount of data using probabilistic statistical analysis techniques.

Automated Print Quality Assessment Method for 3D Printing AI Data Construction

  • Yoo, Hyun-Ju;Moon, Nammee
    • Journal of Information Processing Systems
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    • v.18 no.2
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    • pp.223-234
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    • 2022
  • The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.

REQUIREMENTS FOR AUTOMATED CODE CHECKING FOR FIRE RESISTANCE AND EGRESS RULE USING BIM

  • Jiyong Jeong;Ghang Lee
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.316-322
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    • 2009
  • The more repetitive, complex and objective the work, the more effective automation is. Code checking is an example of this. Checking building codes through a thick set of drawings is error-prone and time-consuming. In order to overcome this problem, several organizations have initiated efforts to automate building-code checking. Initiated study mainly focused on checking codes for invalidation, required size and crash, and then area of checkable codes have been expanding. But, it has not been considered for codes regarding anti-disaster/egress, which is also issued these days. This study is about how to automatically check codes for anti-disaster and egress based on Korea building codes. The codes can be categorized as five sections: egress way, material/capability, principals of evacuation, evacuation stairway and fire protection partition. To check automatically, there are problems, such as expression of codes for egress and limitation of extractable information from the BIM model. This paper shows what problems exist and assignments to be resolved. Also, current developing processes are presented, and suggestions are made about the direction for the work that remains.

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Identification of target subjects and their constraints for automated MEP routing in an AEC project

  • Park, SeongHun;Shin, MinSo;Kim, Tae wan
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.776-783
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    • 2022
  • Since Mechanical, Electrical, and Plumbing(MEP) routing is a repetitive and experience-centered process that requires considerable time and human resources, if automated, design errors can be prevented and the previously required time and human resources can be reduced. Although research on automatic routing has been conducted in many industries, the MEP routing in AEC projects has yet to be identified due to the complexity of system configuration, distributed expertise, and various constraints. Therefore, the purpose of this study is to identify the target subjects for MEP routing automation and the constraints of each subject. The MEP design checklist provided by a CM company and existing literature review were conducted, and target subjects and constraints were identified through process observation and in-depth expert interviews for five days by visiting a MEP design company. The target subjects were largely divided into six categories: air conditioning plumbing, air conditioning duct, restroom sanitary plumbing, heating plumbing, and diagram. The findings from interviews show that work reduction and error reduction has the greatest effect on air conditioning plumbing while the level of difficulty is the highest in air conditioning duct and restroom sanitary plumbing. Major constraints for each subject include preventing cold drafts on air conditioning pipes, deviation in ventilation volume in air conditioning ducts, routing order on restroom sanitary plumbing, and separation distance from the wall on heating plumbing. In this way, subjects and constraints identified in this study can be used for MEP automatic routing.

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Automated Phase Identification in Shingle Installation Operation Using Machine Learning

  • Dutta, Amrita;Breloff, Scott P.;Dai, Fei;Sinsel, Erik W.;Warren, Christopher M.;Wu, John Z.
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.728-735
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    • 2022
  • Roofers get exposed to increased risk of knee musculoskeletal disorders (MSDs) at different phases of a sloped shingle installation task. As different phases are associated with different risk levels, this study explored the application of machine learning for automated classification of seven phases in a shingle installation task using knee kinematics and roof slope information. An optical motion capture system was used to collect knee kinematics data from nine subjects who mimicked shingle installation on a slope-adjustable wooden platform. Four features were used in building a phase classification model. They were three knee joint rotation angles (i.e., flexion, abduction-adduction, and internal-external rotation) of the subjects, and the roof slope at which they operated. Three ensemble machine learning algorithms (i.e., random forests, decision trees, and k-nearest neighbors) were used for training and prediction. The simulations indicate that the k-nearest neighbor classifier provided the best performance, with an overall accuracy of 92.62%, demonstrating the considerable potential of machine learning methods in detecting shingle installation phases from workers knee joint rotation and roof slope information. This knowledge, with further investigation, may facilitate knee MSD risk identification among roofers and intervention development.

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Development of Omnidirectional Object Detecting Technology for a Safer Excavator (굴삭기 작업영역의 전방위 장애물 탐지기술 개발)

  • Soh, Ji-Yune;Lee, Jun-Bok;Han, Choong-Hee
    • Journal of the Korea Institute of Building Construction
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    • v.10 no.4
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    • pp.105-112
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    • 2010
  • The demand for the development of automated construction equipments is gradually increasing to deal with the current problems of construction technology, such as a lack of experienced workers, the aging of engineers, safety issues, etc. In particular, earth work such as excavation is very machine-dependent, and there has been a great deal of research on the development of an intelligent excavator, which involves great safety concerns. Thus, the objective of this study is to develop the technology to enhance the safety of intelligent excavation systems by developing an omnidirectional object detection technology for the intelligent excavator and applying it to a user-friendly system. The existing literature was reviewed, and the function of various sensor technologies was investigated and analyzed. Then, the best laser sensor was selected for an experiment to determine its effectiveness. An omnidirectional object detection algorithm was developed for a user interface program, and this can be used as the fundamental technology for the development of a safety management system for an intelligent excavator.

A Study on the Development of Automated Gangform Climbing System for Apartment Housing Construction (공동주택 전용 갱폼 인양 자동화 기술 개발에 관한 연구)

  • Yang, Sang-Hoon;Cho, Jae-Yong;Cho, Ji-Won;Lee, Jeong-Ho;Kim, Young-Suk
    • Korean Journal of Construction Engineering and Management
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    • v.13 no.1
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    • pp.53-66
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    • 2012
  • Gangform compared with conventional wood and steel form is systemized form which has a capability to install and dismantle form at a time without repeating to assembly and disassembly small members. Gangform compared with ACS has some problems such as 1) Tower Crane load increase, 2) increase in safety incidence during climbing Gangform, 3) decrease in detachment operation productivity, 4) stop work due to climate impacts, and 5) decrease in labor cost, productivity, quality. A conceptual design model of automated Gangform climbing system is suggested for apartment housing construction to show its technical/economic feasibility and workers' safety while increasing operation productivity and concrete quality.