• Korean Journal of Construction Engineering and Management
• /
• v.6 no.2 s.24
• /
• pp.80-91
• /
• 2005

Although construction site photos contain important as_built information, technique and knowledge, there has been lack of frameworks to store and manage construction site photos efficiently and effectively. The problems in site photo management are getting increasingly serious, as digital cameras are adapted as collection tools of site Photos. This research suggests an information framework(named CIIM: Construction Image Information Model) to manage and share construction information based on 5W1H in order to derive construction context, which includes technologies, lessons-teamed and knowledge, from construction site photos, and a site photo management system named CIMS II (Construction Image information Management system II was developed to verify the model. It is expected that the results of this research that are an information framework and an system could help more effective classification, management, search and derivation of context in a construction project.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.41 no.2
• /
• pp.181-189
• /
• 2021

In order to increase the practical usability of the virtual reality(VR)-based BIM object in the construction site, the difference between the virtual image and the real image should be resolved, and when it is applied to the construction schedule management function, it is necessary to reduce the image gap between the virtual completion and the actual completion. In this study, in order to solve this problem, a prototype of 4D model is developed in which augmented reality (AR) and 3D printing technologies are linked, and the practical usability of a 4D model linked with two technologies is verified. When a schedule simulation is implemented by combining a three-dimensional output and an AR object, it is possible to provide more intuitive information as a tangible image-based schedule information when compared to a simple VR-based 4D model. In this study, a methodology and system development of an AR implementation system in which subsequent activities are simulated in 4D model using markers on 3D printing outputs are attempted.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.11 no.2
• /
• pp.145-152
• /
• 2023

In this study, microscopic observation was made on the surface of cement paste immersed in an aquatic environment for 100 days at electrochemical treatment to mitigate the leaching of alkali ions. To quantitatively rank the hydration products, unhydrated grains and porosity in the interfacial region, the backscattered electron(BSE) images were obtained by scanninng electron microscopy. As a result, it was found that the porosity on the surface was significantly reduced by the electrochemical treatment, while unhydrated grains were more or less increased presumably limited hydration reaction under electric charge. At electrochemical treatment, Ca²⁺ ions present in C-S-H gel could be precipitated with OH^- to form Ca(OH)₂ then to lower C-S-H gel and simultaneously to enhance Ca(OH)₂. Substantially, the risk of alkali leaching could be lowered by the limited ionized matrix under electrochemical treatment.

• Korean Journal of Construction Engineering and Management
• /
• v.25 no.2
• /
• pp.36-44
• /
• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.

• Journal of Korean Association for Spatial Structures
• /
• v.20 no.4
• /
• pp.6-13
• /
• 2020

• Journal of Korea Water Resources Association
• /
• v.56 no.6
• /
• pp.403-417
• /
• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Land and Housing Review
• /
• v.14 no.3
• /
• pp.145-155
• /
• 2023

Recently, with the widespread adoption of Building Information Modeling (BIM) technology in the construction industry, various object detection algorithms have been used to verify errors between 3D models and actual construction elements. Since the characteristics of objects vary depending on the type of construction facility, such as buildings, bridges, and tunnels, appropriate methods for object detection technology need to be employed. Additionally, for object detection, initial object images are required, and to obtain these, various methods, such as drones and smartphones, can be used for image acquisition. The study uses a 360° camera optimized for internal tunnel imaging to capture initial images of the tunnel structures of railway and road facilities. Various object detection methodologies including the YOLO, SSD, and R-CNN algorithms are applied to detect actual objects from the captured images. And the Faster R-CNN algorithm had a higher recognition rate and mAP value than the SSD and YOLO v5 algorithms, and the difference between the minimum and maximum values of the recognition rates was small, showing equal detection ability. Considering the increasing adoption of BIM in current railway and road construction projects, this research highlights the potential utilization of 360° cameras and object detection methodologies for tunnel facility sections, aiming to expand their application in maintenance.

• Journal of the Korean Geographical Society
• /
• v.40 no.5 s.110
• /
• pp.491-513
• /
• 2005

The Republic of Korea is planning to build the now Multi-functional Administrative city (NMAC). The purpose of this paper is to suggest the conceptual framework for this new city that relies on the Korean geomancy, oriental viewpoint on man and nature relationship, particularly in Korea. According to the Geomancy which could conceptualize the human-environment relationship in the site, the overall landscape image of the city could be symbolized by two flying crane with three Taegueks. In transforming the overall landscape image to urban form, two diamonds which means eternity and strength arises from the western spatial viewpoint, as means to protect and harmonize the human, land and mountain relationship in this site and the symbolic meaning of this site as generative and sacred place in Korean people's mind. On the one hand, through juxtaposing of the two diamonds a geometric structure shows up, on the other hand the main axis of the city could be established from two crane and three Taegueks. On the North-South axis from the core of the symbolic green axis, symbolic things will be located, and the administrative offices will be Placed on the East-West axis. Peripherals of the central axis also play a role in developing overall land use from image. The buildings and residents could be arranged and located according to undulations and this is based on the oriental theory of geomancy. We can build cultural amenities on the head part of the crane and on the core area.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.26 no.4
• /
• pp.57-64
• /
• 2022

Chloride, which is one of the main deterioration factors in reinforced concrete structures, can degrade the performance of the structure due to chloride-induced corrosion of steel. Chloride content at steel depth or the rate of chloride penetration is necessary to determine deterioration of reinforced concrete or to calculate initiation time of steel corrosion caused by chloride attack. Chlorides in concrete are generally identified with typical two methods including chloride profiling using potentiometric titration method and discoloration method using AgNO₃ solution. The former is advantageous to estimate chloride penetration rate (diffusion coefficient in general) with measured chloride contents directly, but it is laborious. In the case of latter, while the result is obtained easily with the range of discoloration, the error may occur depending on workmanship when the depth of chloride ingress is measured. This study shows that chloride penetrated depth is evaluated with the results obtained from discoloration method through image analysis, thereby the error is minimized by workmanship. In addition, the effect of micro-crack in concrete is studied on chloride penetration. In conclusion, the depth of chloride penetration was quantified with image analysis and as it was confirmed that chlorides can rapidly penetrate through micro-cracks, caution is especially required for cracks in concrete structure.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2021.11a
• /
• pp.223-224
• /
• 2021

The process before the model learning stage in AI R&D can be subdivided into data collection/cleansing-data purification-data labeling. After that, according to the purpose of development, it goes through a stage of verifying the model by performing learning by using the algorithm of the artificial intelligence model. Several studies describe an important part of AI research as the learning stage, and try to increase the accuracy by changing the structure and layer of the AI model. However, if the refinement and labeling process of the learning data is tailored only to the model format and is not made for the purpose of development, the desired AI model cannot be obtained. The latest research reveals that most AI research failures are the failure of the learning data rather than the structure of the AI model. analyzed.