• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.319-327
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• 2022

Robots for construction sites, although not deeply widespread, are finding applications in the duties of project monitoring, material movement, documentation, security, and simple repetitive construction-related tasks. A significant shortcoming in the use of robots is the complexity involved in programming and re-programming an automation routine. Robotic programming is not an expected skill set of the traditional construction industry professional. Therefore, this research seeks to deliver a low-cost approach toward re-programming that does not involve a programmer's skill set. The researchers in this study examined an approach toward programming a terrestrial-based drone so that it follows a taped path. By doing so, if an alternative path is required, programmers would not be needed to re-program any part of the automated routine. Changing the path of the drone simply requires removing the tape and placing a different path - ideally simplifying the process and quickly allowing practitioners to implement a new automated routine. Python programming scripts were used with a DJI Robomaster EP Core drone, and a terrain navigation assessment was conducted. The study examined the pass/fail rates for a series of trial run over different terrains. The analysis of this data along with video recording for each trial run allowed the researchers to conclude that the accuracy of the tape follow technique was predictable on each of the terrain surfaces. The accuracy and predictability inform a non-coding construction practitioner of the optimal placement of the taped path. This paper further presents limitations and suggestions for some possible extended research options for this study.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 봄 학술논문 발표대회
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• pp.133-134
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• 2022

This study proposed vision artificial intelligence-based automated supervision technology for external insulation and finishing system, and basic research was conducted for it. The automated supervision technology proposed in this study consists of the object detection model (YOLOv5) and the part that derives necessary information based on the object detection result and then determines whether the external insulation-related adhesion regulations are complied with. As a result of a test, the judgement accuracy of the proposed model showed about 70%. The results of this study are expected to contribute to securing the external insulation quality and further contributing to the realization of energy-saving eco-friendly buildings. As further research, it is necessary to develop a technology that can improve the accuracy of the object detection model by supplementing the number of data for model training and determine additional related regulations such as the adhesive area ratio.

• 한국건설관리학회논문집
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• 제24권4호
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• pp.60-73
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• 2023

The need for adopting automation technologies to improve inefficiencies in interior finishing modeling work is increasing during the Building Information Modeling (BIM) design stage. As a result, the use of visual programming languages (VPL) for practical applications is growing. However, undefined or incorrect space designations in BIM models can hinder the development of automated finishing modeling processes, resulting in erroneous corrections and rework. To address this challenge, this study first developed a rule-based automated interior finishing detailing module for floors, walls, and ceilings. In addition, an automated space integrity checking module with 86.69% ACC using the Multi-Layer Perceptron (MLP) model was developed. These modules were integrated into a design automation module for interior finishing, which was then verified for practical utility. The results showed that the automation module reduced the time required for modeling and integrity checking by 97.6% compared to manual work, confirming its utility in assisting BIM model development for interior finishing works.

• 한국컴퓨터정보학회논문지
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• 제7권1호
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• pp.62-67
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• 2002

동북아 중심 항만의 기반을 다지기 위해 자동화터미널의 건설이 시급히 요청되고 있다. 따라서 우리나라에 적합한 자동화터미널의 운영시스템 설계방안을 제시하고자 한다. 본 논문에서는 자동화터미널의 운영시스템이 추구해야할 목표를 충족시키며 각 자동화 장비를 통한 화물의 수출입 이동경로에 따라 운영시스템의 기본 모델을 4가지로 구분하고, 여러 입력 요소들을 변경시켜 가며 Trial and Error 방법을 통하여 동적으로 분석해 나감으로서 최적의 운영시스템 모델을 설계하였다 본 논문의 운영시스템에서 기술한 장비들은 Quay Crane을 제외한 모든 야드 장비가 완전자동화를 전제로 한 것이다.

• 한국CDE학회논문집
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• 제20권2호
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• pp.124-132
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• 2015

When Building Information Modeling (BIM) was introduced at the early stage, it was only utilized as a three-dimensional visualization tool. Nowadays, however, BIM is being studied for increasing design productivity and managing enormous information on building life cycle. One of the representative research is developing 'common prototype BIM libraries'. BIM data made of common prototype libraries should be utilized in various ways, quantity takeoff, code checking, energy analysis and so on. However, common prototype BIM libraries are not enough to estimate accurate cost. For example, composite wall libraries should be divided into several single objects, wall structure and finishes, for the quantity takeoff and construction cost calculation. In this paper, we are suggesting an automated division algorithm of composite wall and developing a system prototype for it. This study is expected to reduce extra modeling work and contribute to fast and accurate cost calculation in the construction.

• 한국BIM학회 논문집
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• 제1권2호
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• pp.12-18
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• 2011

건설 프로젝트 생애주기 전반에 걸쳐 생성되는 정보를 3차원 모델을 기반으로 관리하는 BIM (Building Information Modeling) 기술은 계획, 설계, 구조해석은 물론 견적 및 3차원 시뮬레이션을 통한 시공계획 등 공사관리 업무를 통합하는 방향으로 발전하고 있다. BIM 기반 견적모델은 3차원 모델의 사용 용도에 따라 상세수준의 차이와 모델정보의 차이를 보이는데, 본 연구에서는 교량 구조물을 대상으로 하여 견적을 위한 모델의 LOD 수준을 파악하였다. 또한 건설정보 분류체계에 적용되는 라이브러리의 클래스를 정의하고 Microstation의 API를 이용하여 클래스의 파라메터를 추출하여 파라메터와 연동되는 Resource의 물량정보를 산출한다. 견적 모델과 상이하게 모델링된 모델에서 하위 모델을 계층화 하고 견적수준으로 병합함으로써 BIM 기반 토목 라이브러리를 통한 견적자동화시스템을 검증하였다.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1324-1327
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• 2009

Social infrastructure is the basis of public welfare and should be recognized and managed as important assets. Bridge is one of the most important infrastructures to be managed systematically because the impact of the failure is critical. It is essential to monitor the performance of bridges in order to manage them as an asset. But current analytical methods such as predictive modeling and structural analysis are very complicated and difficult to use in practice. To apply these methods, structural and material condition data collection should be performed in each element of bridge. But it is difficult to collect these detailed data in large numbers and various kinds of bridges. Therefore, it is necessary to collect data of major measurement items and predict the life of bridges roughly with advanced information technologies. When certain measurement items reach predefined limits in the monitoring bridges, precise performance measurement will be done by detailed site measurement. This paper describes the selection of major measurement items that can represent the tendency of bridge life and introduces automated bridge data collection test-bed using wireless sensor network technology. The following will be major parts of this paper: 1) Examining the features of conventional bridge management system and data collection method 2) Mileage concept as a bridge life indicator and measuring method of the indicator 3) Test-bed of automated and real-time based bridge life indicator monitoring system using wireless sensor network

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.162-169
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• 2022

In an attempt to disseminate modernized Korean traditional housing (Hanok), a ten-year research project was initiated in 2010 by the Korean Government to reduce the construction cost, improve the facility performance, and automate the Hanok construction industry. To meet these objectives, various research areas, including public policies, planning methods, design standards, new building materials, construction standards, maintenance procedures, advanced project management tools, and integrated IT applications have been developed. In addition, comprehensive technologies developed were applied to the ten pilot Hanok buildings to validate the real-world performance as part of the research project. To further facilitate the digital transformation of the Hanok industry by using the research results, it is required to disseminate the developed technologies in an automated and standardized manner. In particular, it is crucial to systematize and manage the interoperability of various technical data and accumulated historical data for different business functions, especially within the highly fragmented industry. In this context, this paper proposes an ontology-based Hanok information dissemination platform to enable industry-wide automated knowledge and information sharing. The system architecture, standardized historical database, and advanced analytics based on ontology web language (OWL) for the Hanok industrialization platform are introduced.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.443-452
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• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.

• 콘크리트학회논문집
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• 제26권3호
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• pp.287-297
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• 2014

최근 증가 추세에 있는 화력발전소 건설에 있어서, 터빈 기초 구조물은 규모가 매우 큰 매스콘크리트이다. 매스콘크리트의 수화열은 구조물의 품질과 공기 등에 중대한 영향을 미치는 요인 중 하나이므로, 수화열 제어를 위한 적절한 방안은 필수적이다. 이 연구에서는 국내 복합화력발전소 터빈 기초 시공에 앞서 수화열 해석을 통하여 수화열 균열 발생 가능성을 예측하고, 수화열 제어 방안으로서 콘크리트 배합 및 양생방법 변경을 제안하였다. 콘크리트 배합은 기존 1종 보통시멘트 콘크리트 배합에서 슬래그시멘트 콘크리트 배합으로 변경을 제안하였고, 기존 양생포 및 살수양생방법을 개선하기 위하여 매스콘크리트 중심부와 표면부의 온도를 모니터링하여 온도차를 일정수준 이하로 일정하게 유지시켜주는 양생자동화시스템을 적용한 양생방법을 제안하였다. 실제 시공시에는 슬래그콘크리트 배합을 사용하고, 2기의 동일한 터빈 기초 구조물에 대하여 각각 보온양생공법과 양생자동화시스템을 적용하여 양생방법에 따른 온도균열 제어효과를 비교하였으며, 2기의 매스콘크리트에서 온도, 변형률 모니터링 및 균열 조사를 통하여 수화열 제어 효과를 평가하였다.