Visualized information platforms through building information modeling (BIM) such as virtual reality (VR) and augmented reality (AR) improves the efficiency of architectural information exchange. Despite that, less effort has been directed to evaluate the effectiveness of different BIM visualization platforms for architectural design review. This study fills these gaps and compares three BIM visualization tools for reviewing diverse architectural review factors and technology acceptance degree. Three main BIM visualization tools, which are desktop-based, virtual reality-based and augmented reality-based, were employed and different architectural review factors and user's technology acceptance degree was measured. As a result, VR and AR environment showed better visual presentation than desktop environment during design review. In terms of the technology acceptance level, VR and AR environments have received higher ratings compared to desktop environments. The detailed findings provide guidelines for participants and researchers involved in design review process to selectively adopt VR and AR system to various architectural design review components.

As a result, the areas of knowledge that received the highest score in a positive impact were areas of risk management, while those that received the highest score in a negative impact were items of software management. In addition, each project was rated according to the score obtained. The distribution of grades by project was 71% for projects above middle grade and 29% for projects below middle grade. These results show that interest in BIM technology is increasing compared to the past, actual field application and research are actively being conducted, and that real construction sites also enjoy significant positive effects in terms of project management through BIM. In addition, the company is using BIM by applying advanced digital technologies such as AI technology, laser scanning technology and drone technology in line with the era of the fourth industrial revolution. Such a steady progress in future research on BIM technology development will reduce the number of low-grade projects and many middle-grade projects are expected to be upgraded to higher-level ones.

Many studies on BIM-based design, construction and operation have already been conducted on roads, railways, etc., but BIM research in the ports and harbors is still lacking. This research develops BIM Library and Technical contents focused on practical usability of ports and harbors infrastructure. We have developed technical content by applying various User Interfaces and workflows, considering the characteristics of ports and harbors design. In order to examine the practical utility of the developed library and contents, we tried modeling the breakwater using these. As a result, we confirmed that collaboration of BIM library and technical contents could significantly improve the productivity of BIM design by increasing library usage and automating repetitive tasks.

With Building Information Modeling(BIM) becoming the de facto standard for data sharing in the AEC industry, additional needs have increased to ensure the data integrity of BIM models themselves. Although the Industry Foundation Classes provide an open and neutral data format, its generalized schema leaves it open to data loss and misclassifications This research applied deep learning to automatically classify BIM elements and thus check the integrity of BIM-to-IFC mappings. Multi-view CNN(MVCC) and PointNet, which are two deep learning models customized to learn and classify in 3 dimensional non-euclidean spaces, were used. The analysis was restricted to classifying subtypes of architectural walls. MVCNN resulted in the highest performance, with ACC and F1 score of 0.95 and 0.94. MVCNN unitizes images from multiple perspectives of an element, and was thus able to learn the nuanced differences of wall subtypes. PointNet, on the other hand, lost many of the detailed features as it uses a sample of the point clouds and perceived only the 'skeleton' of the given walls.

Digital models for a cable-stayed bridge are defined considering data-driven engineering from design to construction. Algorithms for digital object generation of each component of the cable-stayed bridge were developed. Using these algorithms, Level-3 BIM practices can be realized from design stages. Based on previous practices, digital object library can be accumulated. Basic digital models are modified according to given design conditions by a designer. Once design models are planned, various applications using the models are linked the models such as estimation, drawings and mechanical properties. Federated bridge models are delivered to construction stages. In construction stage, the models can be efficiently revised according to the changed situations during construction phases. In this paper, measured coordinates are imported to the model generation algorithms and revised models are obtained. Augmented reality devices and their applications are proposed. AR simulations in construction site and in office condition are tested. From this pilot test of digital models, it can be said that Level-3 BIM practices can be realized by using in-house modeling algorithms according to different purposes.

In the general manufacturing sector, prototyping used to reduce the risks that can arise with new conceptual products. However, in AEC area, it does not mass-produce a building, so the prototype itself becomes a building. Therefore, it is challenging to have prototyping of the same scale as the real thing, and the prototyping process in architecture is very inefficient. The prototyping process in the design stage typically assumes making a scaled model, partial model, or digital model. However, it is difficult for these models to correspond to the actual building and the environment of time and space such as scale, material, environment, load, physical properties and deformation, corrosion, etc., unlike the actual building. When using the digital twin concept in the prototyping process, it is possible to measure performance from the design stage to the operation stage. The digital twin was found by a method for monitoring based on physical twins and real-time linkage in the operation stage. Therefore, if the digital twin concept is applied at the design stage, it is possible to predict performance using not only current performance but also history information using real-time information. In order to apply the digital twin concept to the prototyping design process, we analyze the theoretical considerations and the prototyping design process of the digital twin, analyze the cases and research results where the prototyping design was applied, Provide an applied prototyping design process. The proposed process is tested through a pilot project and analyzed for potential use.

Because the existing BIM platform is based on user services, the focus is on the development of SaaS (Software as a Service), which provides business services online. However, since a harbor is a security facility, the harbor BIM platform is preferably provided in a private form, rather than relying on the infrastructure environment provided by external cloud providers. Therefore, this study analyzes and reviews the main functions to be provided as SaaS services of the harbor BIM platform. The goal is to build a cloud-based harbor BIM platform that can provide this service to users. To this end, we built IaaS (Infrastructure as a Service) environment of the harbor BIM platform based on the open source Open Stack and integrate and develop PaaS environment with Open Shift applied with IaaS. We applied the GPU to the harbor BIM platform to verify the performance of the harbor BIM platform, and found that the rendering and loading times are improved. In particular, it is expected to reduce the cost of introduction and provide it as the basic cloud environment of similar BIM platform for infrastructure facilities.

Recent data development has made it possible to analyze each individual's daily commuting by using transportation card transaction. This research utilizes about 1 million observations from the subway line no.7 of Seoul metropolitan transportation data. By using such a massive dataset, the authors try to identify daily travel behavior of morning commute and its possible relationship between subway usage and socio-economic factors. There are 4 main types of users and their travel behavior, and top 15 stations with the most users for arrival and departure are selected. Accordingly, 15 stations have distinctive characteristics including population density and the number of businesses around stations. To identify this fact, the 4 most populated stations are selected and their socio-economic factors are examined. According to the analysis, the most departure stations are generally surrounded by hihgly populated residential areas, whereas the most arrival stations are stood within the job concentrated districts.