• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.433-439
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• 2007

A ubiquitous environment in construction requires integrating hardware and software systems. Currently the Construction System Integration Lab (CSIL) at Pusan National University is currently studying the application of ubiquitous technology for better communication in the construction process. In this paper, a pilot of Ubiquitous Concrete Pour System (u-CPS) has been presented to demonstrate the effectiveness of data exchange in the concrete pour process. The u-CPS environment takes advantage of the RFID technology for collecting construction data. The pilot can automatically generate the data for concrete pour work such as departure time, arrival time, concrete pour time. Construction managers can keep track of the progress of concrete pour work using the information. A case study was done for a building construction using the pilot system, the result of which demonstrated that the RFID-base system can help improve the effectiveness of data communication during the concrete pour process.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 봄 학술논문 발표대회
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• pp.323-324
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• 2021

This study is to develop a non-contact construction project management solution that can reduce cost and construction period through on-site information sharing, minimizing contact with others by COVID19, and improving the productivity of the construction industry. Decisions, checklists, and execution rates of construction costs can be checked with smart devices through sharing on-site photos and videos, exchanging opinions. Details and checklist data stored on cloud servers of sites that apply non-face-to-face construction project management solutions will be used as data for analyzing amounts and construction periods depending on the size of the construction. Real-time field information sharing will reduce expected problems and waste factors, expand communication channels with users to prevent or minimize construction disputes and claims, and contribute to the expansion and growth of new research industry markets in construction technology.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2008년도 정기학술발표대회 논문집
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• pp.329-333
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• 2008

최근 건설공사가 대형화 및 복잡화됨에 따라 건설현장에서의 진행관리 중요성은 점점 더 증대되고 있다. 현재 건설 프로젝트 현장에서는 데이터, 정보 기록 및 분석을 현장관리자가 직접 수작업으로 수행하고 있어 상당한 노력과 시간이 소비되고 있으며, 이는 생산성 저하 등 문제점을 있어 야기하고 있다. 이를 개선하기 위한 방안중의 하나로 첨단 DAT(Data Acquisition Technology) 기술 적용이 시도되고 있으며, 본 연구에서는 이러한 DAT의 포괄적 적용 가능성을 분석함으로써 효율적인 프로젝트 진행관리의 방안을 검토하고자 한다.

• 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.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.721-727
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• 2022

Construction safety remains an ongoing concern, and project managers have been increasingly forced to cope with myriad uncertainties related to human operations on construction sites and the lack of a skilled workforce in hazardous circumstances. Various construction fatality monitoring systems have been widely proposed as alternatives to overcome these difficulties and to improve safety management performance. In this study, we propose an intelligent, automatic control system that can proactively protect workers using both the analysis of big data of past safety accidents, as well as the real-time detection of worker non-compliance in using personal protective equipment (PPE) on a construction site. These data are obtained using computer vision technology and data analytics, which are integrated and reinforced by lessons learned from the analysis of big data of safety accidents that occurred in the last 10 years. The system offers data-informed recommendations for high-risk workers, and proactively eliminates the possibility of safety accidents. As an illustrative case, we selected a pilot project and applied the proposed system to workers in uncontrolled environments. Decreases in workers PPE non-compliance rates, improvements in variable compliance rates, reductions in severe fatalities through guidelines that are customized according to the worker, and accelerations in safety performance achievements are expected.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 가을학술발표대회논문집
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• pp.267-268
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• 2023

Unmanned patrol robots are currently being developed for autonomous data survey in construction sites. As the amount of data acquired by robots increases, it is important to utilize proper metadata and system to manage data flow. In this study, we developed three materials, metadata design, robot system and web system, in the purpose of automating construction site data survey using unmanned patrol robots. The metadata was mainly designed to represent when and where raw data was acquired. To identify the location of data acquired, localization data from SLAM algorithm was converted to suit the construction drawings. The robot system and web system were developed to generate, store and parse the raw data and metadata automatically. The materials developed in this study was adopted to Boston Dynamics SPOT, a quadruped robot. Autonomous data survey of 360-picture and environment sensor was tested in two construction sites and the robot worked as intended. As a further study, development on the autonomous data survey to improve the convenience and productivity will be continued.

• 한국건축시공학회지
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• 제11권3호
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• pp.319-325
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• 2011

건설공사는 수많은 자원 중 상당부분이 자재공급업체에서 제공하는 자재의 원활한 공급에 따라 작업의 원활성이 결정된다. 자재를 적기에 조달하고 배분하는 결과에 따라 작업이 순조롭게 진행되고 궁극적으로 소기의 공사기간 내에 공사를 완료할 수 있다. 본 연구는 데이터 웨어하우스 기술을 활용하여 건설공사에서 중요한 자재관리에 활용할 수 있는 방법을 제시하였다. 건설공사의 자재관리를 위해 필요한 자재리드타임, 자재조달비율, 자재설치비율 등에 대한 정보를 다차원적으로 분석하고 KPI를 설정하여 의사결정 정보로 활용할 수 있도록 하였다. 궁극적으로 본 연구는 건설공사의 운영계 시스템에서 발생하는 수많은 자재관련 데이터들을 효과적으로 활용하는 방법을 제시하였다. 즉, 주제 중심적이고 통합적인 데이터를 제공할 수 있는 데이터 웨어하우스 기술을 활용하여 체계적인 자재관리 정보를 제공할 수 있도록 하였다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2012년도 추계 학술논문 발표대회
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• pp.291-292
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• 2012

Progress in the construction project, the estimated cost of the measure is very important. Use preliminary estimate cost data for the prediction of construction cost. But, preliminary estimate cost data a clear calculation, there is no way. it is rely on the historical data and the past construction data. As a result, a significant difference in the actual construction cost and the predicted cost of the problem occurs. In this study, taking advantage of BIM Cost Prediction for efficient and rapid preliminary estimate BIM for building database through the study preliminary estimate cost data.

• 한국CDE학회논문집
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• 제6권3호
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• pp.147-156
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• 2001

In the construction industry, construction process includes a variety of design stages with cooperation and regulation by many related disciplines. In addition, the construction market is growing and becoming more complex. With this characteristic, design information has become more and more complicated and difficult to manage by the simple and traditional data management methodology. In the practical field, although CAD has been widely available for the last ten years, related disciplines have not shared digital information efficiently. This paper suggests a construction CAD data exchange model that has been developed through investigation and analysis of Korean construction CAD practices and foreign CAD standards. Moreover, this paper investigates a CAD data exchange model using STEP to improve information availability and overcome the limit of CAD systems.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.503-508
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• 2005

In the modern, distributed and dynamic construction environment it is important to exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research has demonstrated that (i) a significant percentage of construction data is stored in semi-structured or unstructured data formats (ii) locating and identifying such data that are needed for the important decision making processes is a very hard and time-consuming task. In this paper, an automated methodology for the classification and retrieval of construction images in AEC/FM model based systems will be presented. Specifically, a combination of techniques from the areas of image processing, computer vision, and content-based image retrieval have been deployed to develop a method that can retrieve related construction site image data from components of a project model.