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

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.97-100
• /
• 2015

Analysis of construction tender documents in overseas projects is a very important issue from a risk management point of view. Unfortunately, majority of construction firms are biased by winning contracts without in-depth analysis of tender documents. As a result, many contractors have incurred loss in overseas projects. Although a lot of risk analysis techniques have been introduced, most of them focus project's external unexpected risks such as country conditions and owner's financial standing. However, because those external risks are difficult to control and take preemptive action, we need to concentrate on project inherent risks. Based on this premise, this paper proposes a project-oriented risk mining approach which could detect and extract project risk factors automatically before they are materialized and assess them. This study presents a methodology regarding how to extract potential risks which exist in owner's project requirements and project tender documents using state of the art data analysis method such as text mining, data mining, and information visualization. The project-oriented risk mining approach is expected to effectively reflect project characteristics to the project risk management and could provide construction firms with valuable business intelligence.

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.39-40
• /
• 2015

As international construction market increases, the importance of risk management in international construction project is emphasized. Unfortunately, current risk management practice does not sufficiently deal with project risks. Although a lot of risk analysis techniques have been introduced, most of them focus on project's external unexpected risks such as country conditions and owner's financial standing. However, because those external risks are difficult to manage and take preemptive action, we need to concentrate on project inherent risks. Based on this premise, this paper proposes a project-oriented risk mining approach which could detect and extract project risk factors automatically before they are materialized. This study presents a methodology regarding how to extract potential risks which exist in owner's project requirements and project tender documents using state of the art data analysis method such as text mining. The project-oriented risk mining approach is expected to effectively reflect project characteristics to the project risk management and could provide construction firms with valuable business intelligence.

• 한국산업융합학회 논문집
• /
• 제26권6_3호
• /
• pp.1233-1241
• /
• 2023

This paper investigates the efficient application of drone LiDAR technology for acquiring precise point cloud data in construction and civil engineering. A structured workflow encompassing data acquisition, processing, and accuracy verification is introduced. Practical testing on a construction site affirms that drone LiDAR surveying yields accurate and reliable data across various applications. With a focus on accuracy and verification, the results contribute to the progression of surveying methodologies in construction and civil engineering. The findings provide valuable insights into the dynamic technological landscape of these fields, establishing a foundation for more effective and precise surveying techniques. This study underscores the transformative potential of drone LiDAR technology in shaping the future of construction and civil engineering survey practices.

• Geomechanics and Engineering
• /
• 제38권5호
• /
• pp.467-476
• /
• 2024

This study investigates Tunnel Boring Machine (TBM) performance prediction by employing discrete event simulation technique, which is a potential remedy highlighting its stochastic adaptability to the complex nature of TBM tunnelling activities. The new discrete event simulation model using AnyLogic software was developed and validated by comparing its results with actual performance data for Daegok-Sosa railway project that Earth Pressure Balance (EPB) TBM machine was used in Korea. The results showed the successful implementation of predicting TBM performance. However, it necessitates high-quality database establishment including geological formations, machine specifications, and operation settings. Additionally, this paper introduces a novel methodology for daily performance updates during construction, using automated data processing techniques. This approach enables daily updates and predictions for the ongoing projects, offering valuable insights for construction management. Overall, this study underlines the potential of discrete event simulation in predicting TBM performance, its applicability to other tunneling projects, and the importance of continual database expansion for future model enhancements.

• 국제학술발표논문집
• /
• The 9th International Conference on Construction Engineering and Project Management
• /
• pp.536-542
• /
• 2022

Cost overruns, schedule delays, and a shortage of skilled labor are common problems the construction industry is currently experiencing. Modularization and standardization strategies have the potential to resolve the various problems mentioned above and have been applied for various construction applications for a long time. However, the level of modularization remains low, and modular construction projects have not been getting the full benefits. Thus, this review investigated the cutting-edge technologies currently being utilized to develop the modular construction field. For this paper, qualified research papers were identified using predetermined keywords from previous related research papers. Identified literature was then filtered and analyzed. According to the included reviews, several technologies are being developed for modular construction. For example, automated design and monitoring systems for modularization were developed. In addition, research labs are utilizing robotic arms for modular construction to achieve a high level of completion in the construction industry, as is seen in the manufacturing industry. Despite these efforts, more research and development are necessary because some automation technologies still require manual activities. Thus, there is great potential for further development of modularization techniques, and further research is recommended to achieve high levels of modularization.

• 대한환경공학회지
• /
• 제35권11호
• /
• pp.795-802
• /
• 2013

도시 개발 과정에서 토지이용 특성의 변화에 기인하는 불투수면적률의 증가에 따라 일반적으로 강우시 침투율은 감소하고, 유출률은 증가한다. 이에 따라 개발 이후 도시 내 하천 및 하류부 공공수역의 수질에 미치는 영향도 커질 것으로 우려되고 있다. 이러한 문제에 대응하기 위하여 도시 개발과정에서 가능한 개발 이전의 강우 유출특성을 유지하도록 하는 저영향 개발(LID, Low Impact Development) 기법의 도입이 활발하게 검토되고 있다. 그러나 다양한 LID 기법이 검토되고 있음에도 불구하고, 각 기법별로 강우 및 오염부하 유출특성에 미치는 영향에 대한 이해는 충분치 못한 실정이다. 본 연구에서는 현재 개발이 진행되고 있는 도시 지역을 대상으로 분포형 강우유출모형을 구축하여 모의를 수행하였다. 범용성이 높은 SWMM 모형을 이용하여 LID 기법 적용에 따른 도시 개발 전 후의 유출 및 오염부하 저감효과를 분석하였다. 모의결과, 침투/저류율은 개발 전보다 개발 후 78%에서 15%로 감소하였고, LID 기법(투수성포장, 빗물저류조, 빗물정원)을 적용한 결과 24%까지 다시 증가하였다. 또한 유출률은 개발 전 20%에서 개발 후 74%로 3배 이상 증가하였고, LID 기법 적용시 66%까지 저감시킬 수 있는 것으로 나타나 그 효용성을 확인하였다. 본 모의에 적용한 LID 기법 중 강우유출 저감 측면에서는 투수성포장의 효율이 가장 높았고, 오염부하(TSS, BOD, COD, T-N, T-P) 저감 측면에서는 빗물저류조의 효율이 높은 것으로 나타났다. 따라서 도시 개발에 따른 유출 및 오염부하 저감을 고려하여 LID 기법을 선정할 경우, 강우유출 저감의 측면을 고려한다면 침투의 기능이 주요한 기법을 선정하고, 오염부하 저감의 측면을 고려한다면 저류의 기능이 주요한 기법을 선정하는 것이 효율적인 것으로 판단된다.

• 지질공학
• /
• 제12권2호
• /
• pp.179-188
• /
• 2002

최근 컴퓨터 성능 및 컴퓨터 가시화 기술의 발달에 힘입어 지반공학 분야의 지반조사결과를 가시화 할 수 있는 소프트웨어들이 출시되고 있다. 지반조사의 중요한 목적 중 하나는 건설대상 부지 내에 분포하는 건설에 불리하게 작용하는 불확실성을 예측하고 파악하는 것이다. 이들 불확실성은 시공의 안정성을 떨어뜨릴 뿐만 아니라 공기를 지연시키고 공사비를 증가시킨다. 3차원 가시화 기법은 이러한 지반의 불확실성을 극복할 수 있는 좋은 도구중 하나이다. 본 논문에서는 터널설계 및 시공분야에 3차원 가시화 기술, GIS 기술, 데이터베이스 기술을 적용하기위하여 새롭게 개발된 시스템을 소개한다. 가상현실과 3차원 가시화 기술은 지반구조 및 특성을 3차원 모델화 하는데 사용되었으며, 데이터베이스 기술과 GIS 기술을 접목하여 지반조사와 터널시공 중에 획득되는 지반정보를 데이트베이스화 하였다. 본 시스템을 이용함으로서 초목 엔지니어는 설계단계에서 계획을 세울 때 지반조사 정보를 유용하게 이용할 수 있고, 시공단계에서 공사의 안정성 및 경제성을 극대화시킬 있을 것이다.

• 국제학술발표논문집
• /
• The 10th International Conference on Construction Engineering and Project Management
• /
• pp.343-350
• /
• 2024

Mobile electroencephalography (EEG) can continuously and objectively monitor construction workers' psychological stress, thereby contributing to enhanced safety and health. Traditional EEG-based stress assessment techniques utilize headset-type devices that cover the scalp, including the frontal area, which is the most relevant brain part to stress. Yet, the invasiveness of such devices may pose a potential barrier to their field application. In response, ear-EEG technology presents a less intrusive alternative for continuous monitoring, potentially overcoming the limitations of scalp-EEG. The temporal regions monitored by ear-EEG hold anatomical and functional significance in the brain's response to stress, suggesting that ear-EEG could effectively detect stress. Despite its advantage, the effectiveness of ear-EEG in stress detection remains underexplored, largely due to the existing literature's focus on frontal brain regions. To address this gap, the authors aim to evaluate ear-EEG's effectiveness in measuring stress and compare it to high-density scalp-EEG. EEG signals were collected with ear- and scalp-EEGs from 10 subjects in a controlled laboratory while they performed the mental arithmetic tasks under time pressure and socio-evaluative threats to induce stress at different levels (high vs. low). Subsequently, the authors performed t-tests and point-biserial analysis to analyze differences between high and low-stress conditions in the most reliable stress biomarkers in literature: high-beta power in temporal regions for ear-EEG, and alpha asymmetry in frontal regions for scalp-EEG. The results indicate that both EEG techniques could effectively differentiate between stress levels, with statistical significance (p <0.001 for both) and moderate effect size. Furthermore, the results demonstrate ear-EEG's comparable effectiveness to scalp-EEG in detecting stress-induced brain activity given the comparable statistical metrics, such as p-value and effect size. This study provides a groundwork for further explorations into leveraging ear-EEG as a practical tool for the early detection of stress, aiming to enhance stress management strategies within the construction industry.

• 한국건축시공학회지
• /
• 제5권1호
• /
• pp.111-121
• /
• 2005

This study purposed to derive a model to estimate appropriate construction costs for the application of the estimation system based on historical construction data. For this purpose, it analyzed data ($1999\sim2004$) on the construction costs of reinforced concrete apartments (Long-Lamina-type apartments), which have been highly standardized and have a lot of relevant objective data using statistical analysis techniques and developed an estimation model.