• Journal of KIBIM
• /
• v.11 no.2
• /
• pp.43-53
• /
• 2021

The 'public agency oil joint purchase system' was introduced to lower public sector oil prices and contribute to the stability of the overall consumer oil market. The present study used spatial regression to analyze the factors affecting domestic gasoline price, focusing on the impact of potential implicit collusion among gas stations in determining domestic gasoline prices. Also, this study investigated the effect the location characteristics of the market convention gas stations and government offices on the pressure of price competition in the market and the gasoline price at general gas stations. To summarize the results of the spatial lag model (SLM), the individual characteristics of gas stations such as convenience stores (+), self-fuelling (-), commercial areas (+), subway stations (+), population density (-), and sales (-) are correlated to gasoline prices at gas stations, and the institutional location factors of gas stations (+) affected the average of 9 won per liter, 11 won per liter. In order to solve these problems, the establishment of a monitoring system reflecting the location characteristics of the region and the ongoing review of the system should be carried out. In addition, separate, expanded and promotional measures should be prepared for the convenience of general and public oil buyers.

• Journal of KIBIM
• /
• v.11 no.1
• /
• pp.39-46
• /
• 2021

Urban residents in crowded complexes are making increasing civil complaints about noise and demanding pleasant and comfortable residential environments. Because noise is one of the most important factors related to urban residents' dissatisfaction with their living environments, the present study investigates the direct and indirect effects of noise-related outdoor environmental factors on residential level satisfaction, using noise level data from 29 noise-measuring stations in Seoul. From 62 multi-family apartment complexes near these stations, the authors collected GIS-based environmental attribute data, as well as survey data including the residents' personal characteristics and indicators designed to measure latent psychological characteristics: noise sensitivity and residential noise level satisfaction. This study then utilized structural equation models to analyze the direct variables influencing the latent variables of noise sensitivity and residential noise level satisfaction, as well as the complex relationships among all variables. The result showed that residents who are exposed to less noise, possibly due to living in apartments facing relatively quiet roads, protected by soundproof walls, or surrounded by densely planted trees, tend to be less noise sensitive, which makes them more satisfied with the ambient noise level. Therefore, critical outdoor environmental variables can be used to reduce noise sensitivity and improve residential noise level satisfaction.

• Journal of KIBIM
• /
• v.11 no.2
• /
• pp.24-32
• /
• 2021

Recently, starting with smart construction research, interest in technology that automates construction site management using artificial intelligence technology is increasing. In order to automate construction site management, it is necessary to recognize objects such as construction equipment or workers, and automatically analyze the relationship between them. For example, if the relationship between workers and construction equipment at a construction site can be known, various use cases of site management such as work productivity, equipment operation status monitoring, and safety management can be implemented. This study derives a real-time object detection platform architecture that is required when performing construction site management using deep learning technology, which has recently been increasingly used. To this end, deep learning models that support real-time object detection are investigated and analyzed. Based on this, a deep learning model development process required for real-time construction site object detection is defined. Based on the defined process, a prototype that learns and detects construction site objects is developed, and then platform development considerations and architecture are derived from the results.

• Journal of KIBIM
• /
• v.12 no.1
• /
• pp.55-61
• /
• 2022

Recently, demand for designing own space is increasing as the rapid growth of home furnishing market. However, there is a limitation that it is not easy to compare the style between before construction view and after view. This study aims to translate real image into another style with GAN model learned with interior images. To implement this, first we established style criteria and collected modern, natural, and classic style images, and experimented with ResNet, UNet, Gradient penalty concept to CycleGAN algorithm. As a result of training, model recognize common indoor image elements, such as floor, wall, and furniture, and suitable color, material was converted according to interior style. On the other hand, the form of furniture, ornaments, and detailed pattern expressions are difficult to be recognized by CycleGAN model, and the accuracy lacked. Although UNet converted images more radically than ResNet, it was more stained. The GAN algorithm allowed us to represent results within 2 seconds. Through this, it is possible to quickly and easily visualize and compare the front and after the interior space style to be constructed. Furthermore, this GAN will be available to use in the design rendering include interior.

• Journal of KIBIM
• /
• v.11 no.4
• /
• pp.1-9
• /
• 2021

Comparing to general scanning data, the 3D digital map for large construction sites and complex buildings consists of millions of points. The large construction site needs to be scanned multiple times by drone photogrammetry or terrestrial laser scanner (TLS) survey. The scanned point cloud data are required to be registrated with high resolution and high point density. Unlike the registration of 2D data, the matrix of translation and rotation are used for registration of 3D point cloud data. Archiving high accuracy with 3D point cloud data is not easy due to 3D Cartesian coordinate system. Therefore, in this study, iterative closest point (ICP) registration method for improve accuracy of 3D digital map was employed by different overlap ratio on 3D digital maps. This study conducted the accuracy test using different overlap ratios of two digital maps from 10% to 100%. The results of the accuracy test presented the optimal overlap ratios for an ICP registration method on digital maps.

• Journal of KIBIM
• /
• v.13 no.2
• /
• pp.16-28
• /
• 2023

The concept of the Metaverse has been around not only for play but also for daily use. The interest in Metaverse is increasing, and various industries such as medicine, media, and financial started to use the new technology for diverse purposes. In addition, interest in the Metaverse is increasing in the architectural industry, but not much research has been done yet. Recently, some studies started to study focusing on the architectural design of Metaverse and the technological characteristics of Metaverse. However, there are limited studies about the utilization of the Metaverse in the architectural design process or construction process. From this perspective, the study aims to analyze the applicability of the Metaverse in the architectural design process through Metaverse case studies. In order to accomplish the research goal, the study classified user experience and technology of Metaverse in the literature review and Metaverse use in other industries such as commercial, medical, media entertainment, and construction industry. Then, this study analyzes six representative Metaverse platforms according to the application of Metaverse in the architectural design process. Finally, this study discussed the future direction and potential of Metaverse application in the Architectural design process.

• Journal of KIBIM
• /
• v.13 no.3
• /
• pp.12-20
• /
• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.

• Journal of KIBIM
• /
• v.14 no.1
• /
• pp.1-10
• /
• 2024

Virtual reality is one of the key emerging technologies of the 21th century and it has been used in a variety of ways in the fields of architectural research. Virtual reality is presented as an ideal alternative for studying the interaction between space and humans because it provides a realistic spacial experience while allowing experimenters to control environmental variables at a low cost easily. It allowed us to deepen our knowledge of human spatial experience in the built environment. However, existing reviews do not include the following points: 1) previous review research has been focused on using virtual reality technology in construction and engineering, not spatial experience, 2) recently, some review researches started to study the interaction between space and humans in the built environment, however, they do not suggest specific concepts of spatial experience. The present review aims to examine the existing literature about measuring spatial experience using virtual reality in architectural design. The study conducted a systematic qualitative review that analyzes and synthesizes the evolving literature regarding design elements, methodology, and usability. The study concludes with an overall discussion and their potential for providing further directions for future research.

• Journal of KIBIM
• /
• v.13 no.4
• /
• pp.45-53
• /
• 2023

The educational benefits and potential of XR as a new medium are well recognized. However, there are still limitations in understanding the specific effects of XR compared to the more widely utilized representation of images on computer monitors. This study therefore aims to demonstrate the differences in effectiveness between the two technologies and to draw implications from a cognitive comparison of three-dimensional objects represented on a flat surface and virtually. The study was conducted a quantitative research method with an experiment involving two independent groups, and the results were tested using regression analysis. The results showed that for low-level, two-dimensional objects, the computer monitor method may be more effective, but above a certain level of complexity, the effectiveness of learning through the monitor tends to decrease rapidly. On the other hand, the group that used extended reality technology showed relatively high comprehension compared to the monitor group even as the complexity increased, and in particular, unlike the monitor group's rapidly decreasing comprehension level, the extended reality technology group showed a trend of decreasing comprehension with the level of complexity, suggesting the potential for compatibility and predictability in the use of technology.

• Journal of KIBIM
• /
• v.7 no.3
• /
• pp.1-10
• /
• 2017

3D concrete printing technology builds structural components layer-by-layer with concrete extruded through a nozzle without using forms. This technology can simplify construction processes by optimizing design flexibility, construction time, and cost. Furthermore, the 3D printing technology is easy to make an irregularly shaped and function embedded building(or object) which is difficult to be constructed by conventional construction method. However, the 3D printing concrete is not suitable for current commercial standard and the material itself. It is also difficult to apply it to the construction site due to the lack of initial strength and the nozzle which is clogged during the process. The research of mix proportion design process for 3D printing concrete which differs from the conventional concrete is necessary in order to solve the problems. This paper aims to calculate the 3D printing concrete mix proportion design process based on the mix materials and performance information derived from the previous researches. Therefore, the usage variation range, mutual influence relationship, and the importance priority of the mix proportion are analyzed. Based on this results, the basic design process of 3D printing concrete which contains planning design phase, basic design phase and validating performance phase is suggested. We anticipate to confirm applicability verification about the actual production by referring to this 3D printing concrete mix proportion study. In the future, this study can be utilized for blueprint of the 3D printing concrete mix proportion.