• 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 Institute of Rural Architecture
• /
• v.25 no.2
• /
• pp.1-8
• /
• 2023

This study reveals the absence of standard design guidelines by region through investigation and analysis centered on public design cases by region in Jeollabuk-do and design elements that can reflect the integration, identity, and diversity of public design in each region by five regions. Through this, the following conclusions could be obtained. First, to improve the quality of street facilities in Jeollabuk-do, the design elements (design motif, color, pattern) applicable to the standard design were analyzed by dividing them into five regions. As a design motif, it was possible to extract patterns containing straight lines, sophistication, dignity, and smartness. In the Northeast region, it is comfortable with the motif of the mountain ridge reflecting geographical characteristics, and it can be extracted elements that contain warm and natural colors. In the southeastern region, patterns that reflect design elements were extracted by applying safe, lively, and peaceful colors with the design motif of curves that blend nature and agriculture. In the southwestern region, design pattern elements that highlight nature, history, and culture were extracted with various cultural assets and natural greenery as motifs. Lastly, in the Saemangeum region, the ocean flow and greenery could be used as a design motif to reflect a positive, clear, future-oriented image in the design spot zones by region. Second, based on the standard design elements (design motive, color, pattern) by region extracted for the standard design development of street facilities in each region in Jeollabuk-do, an integrated zone(Form, structure, material, color, functional element) to which regional design guidelines can be applied. Third, an integrated zone (form, structure, material, color, functional elements) was composed. In addition, design spot zones (patterns and colors in city and county units) that can contain the diversity and identity of each region were designated. By designating design spot zones (patterns and colors in city and county units) that can contain the diversity and identity of each region, standard design development plans (integrated pillars, jaywalking prevention fences, roundabouts (urban type, rural type), street trees) Eight standard designs, including protective covers, street planters, flat benches, light benches, visual media for user guidance, and parking zones for personal mobile devices) were presented.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.3D
• /
• pp.407-415
• /
• 2008

This study presents the methodology to link with aerial photos for advancing the accuracy of topographic survey data that is used to calculate water volume in urban stream. First, GIS spatial interpolation technique as Inverse Distance Weight (IDW) and Kriging was applied to construct the terrain morphology to the sand-bar and grass area using cross-sectional survey data, and also validation point data was used to estimate the accuracy of created topographic data. As the result of comparison, IDW ($d^{-2}_{ij}$, 2nd square number) in Sand-bar area and Kriging Spherical model in grass area showed more efficient results in the construction of topographic data of river boundary. But the differences among interpolation methods are very slight. Image classification method, Minimum Distance Method (MDM) was applied to extract sand-bar and grass area that are located to river boundary efficiently and the elevation value of extracted layers was allocated to the water level point value. Water volume with topographic data from aerial photos shows the advanced accuracy of 13% (in sand-bar) and 12% (in grass) compared to the water volume of original terrain data. Therefore, terrain analysis method in river linking with aerial photos is efficient to the monitoring about sand-bar and grass area that are located in the downstream of Dam in flooding season, and also it can be applied to calculate water volume efficiently.

• Korean Journal of Remote Sensing
• /
• v.39 no.2
• /
• pp.143-156
• /
• 2023

To precisely and reliably analyze the contents of the satellite imagery, recognizing the clouds which are the obstacle to gathering the useful information is essential. In recent times, deep learning yielded satisfactory results in various tasks, so many studies using deep neural networks have been conducted to improve the performance of cloud detection. However, existing methods for cloud detection have the limitation on increasing the performance due to the adopting the network models for semantic image segmentation without modification. To tackle this problem, we introduced the multi-branch neural architecture search to find optimal network structure for cloud detection. Additionally, the proposed method adopts the soft intersection over union (IoU) as loss function to mitigate the disagreement between the loss function and the evaluation metric and uses the various data augmentation methods. The experiments are conducted using the cloud detection dataset acquired by Arirang-3/3A satellite imagery. The experimental results showed that the proposed network which are searched network architecture using cloud dataset is 4% higher than the existing network model which are searched network structure using urban street scenes with regard to the IoU. Also, the experimental results showed that the soft IoU exhibits the best performance on cloud detection among the various loss functions. When comparing the proposed method with the state-of-the-art (SOTA) models in the field of semantic segmentation, the proposed method showed better performance than the SOTA models with regard to the mean IoU and overall accuracy.

• Smart Structures and Systems
• /
• v.30 no.5
• /
• pp.521-535
• /
• 2022

Efficient management of deteriorating civil infrastructure is one of the most important research topics in many developed countries. In particular, the remote displacement measurement of bridges using linear variable differential transformers, global positioning systems, laser Doppler vibrometers, and computer vision technologies has been attempted extensively. This paper proposes a remote displacement measurement system using closed-circuit televisions (CCTVs) and a computer-vision-based method for in-situ bridge bearings having relatively large displacement due to temperature change in long term. The hardware of the system is composed of a reference target for displacement measurement, a CCTV to capture target images, a gateway to transmit images via a mobile network, and a central server to store and process transmitted images. The usage of CCTV capable of night vision capture and wireless data communication enable long-term 24-hour monitoring on wide range of bridge area. The computer vision algorithm to estimate displacement from the images involves image preprocessing for enhancing the circular features of the target, circular Hough transformation for detecting circles on the target in the whole field-of-view (FOV), and homography transformation for converting the movement of the target in the images into an actual expansion displacement. The simple target design and robust circle detection algorithm help to measure displacement using target images where the targets are far apart from each other. The proposed system is installed at the Tancheon Overpass located in Seoul, and field experiments are performed to evaluate the accuracy of circle detection and displacement measurements. The circle detection accuracy is evaluated using 28,542 images captured from 71 CCTVs installed at the testbed, and only 48 images (0.168%) fail to detect the circles on the target because of subpar imaging conditions. The accuracy of displacement measurement is evaluated using images captured for 17 days from three CCTVs; the average and root-mean-square errors are 0.10 and 0.131 mm, respectively, compared with a similar displacement measurement. The long-term operation of the system, as evaluated using 8-month data, shows high accuracy and stability of the proposed system.

• International Journal of High-Rise Buildings
• /
• v.12 no.3
• /
• pp.225-234
• /
• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Smart Media Journal
• /
• v.12 no.11
• /
• pp.175-184
• /
• 2023

The elderly in rural areas are faced with the dilemma of poor community environment, weak social communication ability and insufficient pension knowledge reserve. In addition, due to the serious shortage of social security facilities in rural areas and medical resources, the elderly are struggling, and the suicide rate is far higher than that in urban areas. In order to make the elderly have a comfortable pension environment and face the increasingly serious aging problem with a positive attitude, this paper takes the community environment of the Baima Tibetan elderly in Tielou Township, Gansu Province as the research object of aging transformation. First of all, literature data were used to carry out research on the aging transformation in rural areas. On the basis of sorting out previous research topics, ERG theory was determined as the guide. Secondly, the research methods of on-site investigation, interview and other research methods are adopted to investigate the number of left-behind elderly people in this area, and classify them according to the national standards. At the same time, the image of the current situation of the community environment of the elderly. Finally, combined with the ERG theory, the transformation design of the elderly living environment is implemented, mainly from the three aspects of survival, mutual relationship and growth.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.37 no.4
• /
• pp.86-93
• /
• 2009

This study analyzes the systematic visual images and factors in and outside of the main courtyard in Byungsan-seowon. The results are as follows; In terms of space distribution, Ip-kyo-dang is located at an elevation of 85m and the distance to Byung-san is 365m. Byung-san with the mean gradient over $50^{\circ}$ looked so stiff, and the east side of that cliff is higher than west. In terms of the angle of elevation relationship between Man-dae-ru and Byung-san draw 10.5 degree and it suits with human scale. The D/H ratio of 1:3 makes the given place very spacious but the linear stiff shape of Byung-san may cause the feeling of closeness. The results of the visual image analysis of the main yard facing Byung-san is very positive with a score of 1.70 in openness, 1.78 in wideness, 1.96 in beauty, 1.96 in harmony for the spacious arrangement which overall, makes the seowon beautiful with many open spaces. There are 4 main implicated factors analyzed which are uniqueness, aesthetic, openness and nature. Out of the total variables, these factors' descriptive ability is 55.90% and the remaining 44.10% is error and peculiarities variables. The factor which contributed most to Byungsan-seowon's main yard's visual preference was the 'aesthetic' with B-values of 0.661 and 0.455 in the nature category.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.13 no.1
• /
• pp.89-100
• /
• 2010

The aim of this study is to produce land cover maps using satellite imagery with various degrees of high resolution and then compare the accuracy of the image types and categories. For the land cover map produced on a small-scale classification the estuary area around the Nakdong river, including an urban area, farming land and waters, was selected. The images were classified by analyzing the aerial photos taken from KOMPSAT2, Quickbird and IKONOS satellites, which all have a resolution of over 1m to the naked eye. Once all of the land cover maps with different images and land cover categories had been produced they were compared to each other. Results show that image accuracy from the aerial photos and Quickbird was relatively higher than with KOMPSAT2 and IKONOS. The agreement ratio for the large-scale classification across the classification methods ranged between 0.934 and 0.956 for most cases. The Kappa value ranged between 0.905 and 0.937; the agreement ratio for the middle-scale classification was 0.888~0.913 and the Kappa value was 0.872~0.901. The agreement ratio for the small-scale classification was 0.833~0.901 and the Kappa value was 0.813~0.888. In addition, in terms of the degree of confusion occurrence across the images, there was confusion on the urbanized arid areas and empty land in the large-scale classification. For the middle-scale classification, the confusion mainly occurred on the rice paddies, fields, house cultivating area and artificial grassland. For the small-scale classification, confusion mainly occurred on natural green fields, cultivating land with facilities, tideland and the surface of the sea. The findings of this study indicate that the classification of the high resolution images with the naked eye showed an agreement ratio of over 80%, which means that it can be used in practice. The findings also suggest that the use of higher resolution images can lead to increased accuracy in classification, indicating that the time when the images are taken is important in producing land cover maps.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.39 no.3
• /
• pp.51-63
• /
• 2011

The purpose of this study is to create a landscape image that considers the selection of techniques that can enhance landscape reproduction in streetscape evaluation using 3 dimensional simulations and to evaluate ways to verify similarities and the psychological changes on the part of users by season. In the comparison of technique, the Low(apply normal map) technique was selected for the natural representation of trees in a near and middle view and the Plane technique was selected for the distant view. As the result of the verification, all indicators of physical similarity were evaluated over 4.50 points and most indicators of psychological similarity were found to have no difference except for indicators of 'disordered orderly' and 'dirty - clean'. According to the results of analyzing the landscape simulation by season, images of 'bright', 'beautiful', and 'static', etc., were evaluated high for the spring streetscape. The images of 'open', 'refresh', and 'animate' appeared high in summer and images of 'warm' and 'dark' were found to be high in fall. On the other hand, all images were evaluated as low except for the 'orderly' image. In the preference of streetscape by season, summer and spring were highly preferred at 5.01 and 4.98 with winter as the lowest at 3.48. As the results of the analysis of preference factor, the spring streetscape was found to be a major influence in preference by 0.540 in 'aesthetics'. In the case of summer, 'order' was found to be high at 0.417 while influences in preference included 'variety' and 'aesthetics' in fall and 'variety', 'aesthetics', and 'order' in winter. A determination of suitable spatial planning using a comparative analysis of various city streets will be enabled through the methods of this study.