• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.95-101
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• 2023

Colmap is one of the innovative artificial intelligence technologies, highly effective as a tool in 3D reconstruction tasks. Moreover, it excels at constructing intricate 3D models by utilizing images and corresponding metadata. Colmap generates 3D models by merging 2D images, camera position data, depth information, and so on. Through this, it achieves detailed and precise 3D reconstructions, inclusive of objects from the real world. Additionally, Colmap provides rapid processing by leveraging GPUs, allowing for efficient operation even within large data sets. In this paper, we have presented a method of collecting 2D images of traditional Korean towers and reconstructing them into 3D models using Colmap. This study applied this technology in the restoration process of traditional stone towers in South Korea. As a result, we confirmed the potential applicability of Colmap in the field of cultural heritage restoration.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1075-1084
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• 2022

The use of Hi-Tech in cultural heritage preservation and the promotion of cultural heritage values in general, particularly artifacts, opens new opportunities for attracting tourists while also posing a challenge due to the need to reward high-quality excursions to visitors historical and cultural values. Building Information Modeling (BIM) and Hi-Tech in new building management have been widely adopted in the construction industry; however, Historic Building Information Modeling (HBIM) is an exciting challenge in 3D modeling and building management. For those reasons, the Scan-to-HBIM approach involves generating an HBIM model for existing buildings from the point cloud data collected by Terrestrial 3D Laser Scanner integrated with Virtual Reality (VR), Augmented Reality (AR), contributes to spatial historic sites simulation for virtual experiences. Therefore, this study aims to (1) generate the application of Virtual Reality, Augmented Reality to Historic Building Information Modeling - based workflows in a case study which is a monument in the city; (2) evaluate the application of these technologies to improve awareness of visitors related to the promotion of historical values by surveying the experience before and after using this application. The findings shed light on the barriers that prevent users from utilizing technologies and problem-solving solutions. According to the survey results, after experiencing virtual tours through applications and video explanations, participant's perception of the case study improved. When combined with emerging Hi-Tech and immersive interactive games, the Historic Building Information Modeling helps increase information transmission to improve visitor awareness and promote heritage values.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.110-122
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• 2023

Over the last few decades, various innovative technologies have emerged that have significantly contributed to making life easier for humans. Various information and communication technologies (ITCs) have emerged as a result of the global technological revolution, including big data, IoT, 4G and 5G networks, cloud computing, mobile computing, and artificial intelligence. These technologies have been adopted in urban planning and development, which gave rise to the concept of smart cities in the 1990s. A smart city is a type of city that uses ITCs to exchange and share information to enhance the quality of services for its citizens. With the global population increasing at unprecedented levels, cities are overwhelmed with a myriad of challenges, such as the energy crisis, environmental pollution, sanitation and sewage challenges, and water quality issues, and therefore, have become a convergence point of economic, social, and environmental risks. The concept of a smart city is a multidisciplinary, unified approach that has been adopted by governments and municipalities worldwide to overcome these challenges. Though challenging, this transformation is essential for cities with differing technological and social features, which all have the potential to determine the success or failure of the digital transformation of cities into smart cities. In recent years, researchers, businesses, and the government have all turned their attention to the emerging field of smart cities. Accordingly, this paper aims to represent a thorough understanding of the movement toward smart cities. The key themes identified are smart city definitions and concepts, smart city dimensions, and smart city architecture of different layers. Furthermore, this article discusses the challenges and some examples of smart cities.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.555-561
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• 2009

In lieu of section profile data, a fitting of the bored tunnel shape is more significant confirmation for maintenance of a tunnel. Before the permit on the completion of a tunnel, deformation of the completed tunnel with respect to the design model are considered. And deformation can be produced at continuously along the entire of the tunnel section. This study firstly includes an analysis of algebraic approach and test it with an observed field data. And then a number of methods, line search method, genetic algorithm, and pattern search methods, are compared with the 3D tunnel shape fitting. Algebraic methods can solve a simple circular cylinder type as like a railway tunnel. However, a more complex model (compound circular curve and non circular) as like a highway tunnel has to be solved with soft computing tools in the cause of conditional constraints. The genetic algorithm and pattern search methods are computationally more intensive, but they are more flexible at a complex condition. The line search method is fastest, but it needs a narrow bounds of the initial values.

• Journal of The Geomorphological Association of Korea
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• v.18 no.4
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• pp.283-296
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• 2011

The aim of this study is to analyze the short-term changes of beach and dune morphology at Hwajin beach, Korea using by terrestrial LIDAR. Based on ArcInfo as point cloud obtained through precise analyzing studying area twice (1st : Sep 1. 2010, 2nd : Oct 2nd. 2010) by terrestrial LIDAR, alteration of beach and dune was analyzed at DEM, of which cell size is about 10cm. Consequently, during the studying period, coastlines at studying area moved backward and reduced the area of coastal zone. In a section change, the north beach moved backward with more eroded beach face and the middle section of south beach moved forward with more deposited beach face. Considering all the section changes of beach at studying area, beach section during the 1st measurement period can be defined as a summer profile, and it can be explained that the temporary storm profile was formed by the strong wave created during studying period. As a result of analyzing the alteration of beach area by terrestrial LIDAR, alteration of narrow area was able to be analyzed in detail by class of 'centimeter' and the time was able to be shortened.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.510-519
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• 2020

Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.279-286
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• 2013

This paper introduces a new method for identification of building energy performance problems. The presented method is based on automated analysis and visualization of deviations between actual and expected energy performance of the building using EPAR (Energy Performance Augmented Reality) models. For generating EPAR models, during building inspections, energy auditors collect a large number of digital and thermal imagery using a consumer-level single thermal camera that has a built-in digital lens. Based on a pipeline of image-based 3D reconstruction algorithms built on GPU and multi-core CPU architecture, 3D geometrical and thermal point cloud models of the building under inspection are automatically generated and integrated. Then, the resulting actual 3D spatio-thermal model and the expected energy performance model simulated using computational fluid dynamics (CFD) analysis are superimposed within an augmented reality environment. Based on the resulting EPAR models which jointly visualize the actual and expected energy performance of the building under inspection, two new algorithms are introduced for quick and reliable identification of potential performance problems: 1) 3D thermal mesh modeling using k-d trees and nearest neighbor searching to automate calculation of temperature deviations; and 2) automated visualization of performance deviations using a metaphor based on traffic light colors. The proposed EPAR v2.0 modeling method is validated on several interior locations of a residential building and an instructional facility. Our empirical observations show that the automated energy performance analysis using EPAR models enables performance deviations to be rapidly and accurately identified. The visualization of performance deviations in 3D enables auditors to easily identify potential building performance problems. Rather than manually analyzing thermal imagery, auditors can focus on other important tasks such as evaluating possible remedial alternatives.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.837-847
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• 2023

In this study, we explored a method for assessing the extent of damage caused by chemical substances at an accident site through the use of a vegetation index. Data collection involved the deployment of two different drone types, and the damaged area was determined using photogrammetry technology from the 3D point cloud data. To create a vegetation index image, we utilized spectral band data from a multi-spectral sensor to generate an orthoimage. Subsequently, we conducted statistical analyses of the accident site with respect to the damaged area using a predefined threshold value. The Kappa values for the vegetation index, based on the near-infrared band and the green band, were found to be 0.79 and 0.76, respectively. These results suggest that the vegetation index-based approach for analyzing damage areas can be effectively applied in investigations of chemical accidents.

• Computers and Concrete
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• v.33 no.5
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• pp.595-603
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• 2024

In the construction industry, there has been a surge in the implementation of high-tech equipment in recent years. Various technologies are being considered as potential solutions for future construction projects. Building information modeling (BIM), which utilizes advanced equipment, is a promising solution among these technologies. The need for safety inspection has also increased with the aging structures. Nevertheless, traditional safety inspection technology falls short of meeting this demand as it heavily relies on the subjective opinions of workers. This inadequacy highlights the need for advancements in existing maintenance technology. Research on building safety inspection using 3D laser scanners has notably increased. Laser scanners that use light detection and ranging (LiDAR) can quickly and accurately acquire producing information, which can be realized through reverse engineering by modeling point cloud data. This study introduces an innovative evaluation system for building safety using a 3D laser scanner. The system was used to assess the safety of an existing three-story building by implementing a reverse engineering technique. The 3D digital data are obtained from the scanner to detect defects and deflections in and outside the building and to create an as-built BIM. Subsequently, the as-built structural model of the building was generated using the reverse engineering approach and used for structural analysis. The acquired information, including deformations and dimensions, is compared with the expected values to evaluate the effectiveness of the proposed technique.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.5
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• pp.1-13
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• 2024

In this study, we applied an on-site diagnostic method for estimating the structural safety of a plastic greenhouse. A three-dimensional light detection and ranging (3D LiDAR) sensor was used to scan the greenhouse to extract point cloud data (PCD). Differential thresholds of the color index were applied to the partitions of raw PCD to separate steel frames from plastic films. Additionally, the K-means algorithm was used to convert the steel frame PCD into the nodes of unit members. These nodes were subsequently transformed into structural shape data. To verify greenhouse shape reproducibility, the member lengths of the scan and blueprint models were compared with the measurements along the X-, Y-, and Z-axes. The error of the scan model was accurate at 2%-3%, whereas the error of the blueprint model was 5.4%. At a maximum snow depth of 0.5 m, the scan model revealed asymmetric horizontal deflection and extreme bending stress, which indicated that even minor shape irregularities could result in critical failures in extreme weather. The safety factor for bending stress in the scan model was 18.7% lower than that in the blueprint model. This phenomenon indicated that precise shape estimation is crucial for safety diagnostic. Future studies should focus on the development of an automated process based on supervised learning to ensure the widespread adoption of greenhouse safety diagnostics.