• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.95-96
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• 2023

The purpose of this study is to derive the limitations of the existing management system by analyzing the characteristics of the PC process to improve the PC construction project management system process. To overcome the limitations derived, we present a process of managing integrated information from the design-production-construction stage using QR codes and clouds. This is expected to help develop a PC construction project management system.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.323-324
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• 2021

This study is to develop a non-contact construction project management solution that can reduce cost and construction period through on-site information sharing, minimizing contact with others by COVID19, and improving the productivity of the construction industry. Decisions, checklists, and execution rates of construction costs can be checked with smart devices through sharing on-site photos and videos, exchanging opinions. Details and checklist data stored on cloud servers of sites that apply non-face-to-face construction project management solutions will be used as data for analyzing amounts and construction periods depending on the size of the construction. Real-time field information sharing will reduce expected problems and waste factors, expand communication channels with users to prevent or minimize construction disputes and claims, and contribute to the expansion and growth of new research industry markets in construction technology.

• Korean Journal of Construction Engineering and Management
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• v.12 no.4
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• pp.106-116
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• 2011

It is very important to collect and manage labor information in the construction industry that is labor-intensive. Although research and cases that utilize RFID are increasing for more effective labor management, labor management is limited to the checking-in and -out information management at the entrance of a construction site due to high expense of an RFID reader. Labor and safety information is still managed based on the redundant process that is hand-written in a book and re-input of information by using a personnel-computer. Therefore, the objective of this paper is to develop more effective and efficient process for labor information record and management. This paper presents a prototype application that supports integrated labor information management by incorporating QR-code into RFID-based labor management system and verifies the application through a pilot test and comparison with the existing labor management syste.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.367-368
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• 2023

Kiscon, Seumteo, KONEPS and CSI are representative construction-related DBs. All four DBs are operated by the public. However, the characteristics of data are different depending on the purpose. Therefore, it is difficult to utilize integrated data and it is only used sparingly. Creating and sharing a unique key that can identify a construction site will enable integrated accumulation and management of construction-related data for various purposes. At this point, it is most efficient to assign a unique key based on KISCON. KISCOn data conforms to the construction site definition and covers most of the public, private, architectural and civil works. In addition, there is an advantage in that DB construction is performed in the construction situation, which is a relatively preceding process. In the future, it is necessary to create a practical construction site integrated DB through the production of an integrated key table containing linkage information of unique keys for site management, performance indicators, and statistics production.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of Construction Engineering and Project Management
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• v.3 no.4
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• pp.1-4
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• 2013

Excavation is most commonly used activity in all construction projects. All contracting agencies prefer to use bigger and heavier excavators and dumpers on site to do excavations if quantity of excavation is huge. Estimation of required number of excavators and dumpers for completion of excavation could be rather a tedious process involving repetitive calculation on which professionals spend their valuable time. As the Information Technology is highly involved in construction section there os need to have IT model for estimation of number of excavators and dumpers. The developed model is useful to calculate required equipments within short period of time. The purpose of the developed IT model is to save the time and efforts of the construction professional. The paper discusses about model which can be used on site to estimate numbers of excavators and dumpers required for completion of certain quantity of excavation within the given time. The calculation considers various existing formulas and method to generate the output. This information could certainly be useful in planning equipments on construction project sites. The tool is user friendly where any non IT background person can use it on construction sites.

• Korean Journal of Construction Engineering and Management
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• v.14 no.2
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• pp.22-34
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• 2013

As construction project has been becoming larger, specialized and complicated, it is important to utilize a lot of information that is made by diverse participants. Especially this information is mainly produced in construction site that plays a leading role in construction project. The problem of information exchange between participants of construction site causes decline of construction productivity. So as to resolve this problem, there is a many interest in BIM(Building Information Modeling) that makes and manages a necessary data during building life cycle. But in Korea construction industry, applying BIM in construction phase is less active than in design phase. Through studying previous research, this study classify the main cause of failure related to information exchange in framework construction. And by interviewing expert, it draw a work that is possible to apply BIM. Next through analyzing framework construction site that is applied with BIM, this study proposes specific information flow model for supporting work by BIM.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.669-670
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• 2015

Efficient management of the construction heavy equipment is required to reduce the rate of carbon emissions and on-site accidents. The intelligent excavation system (IES) will improve the construction quality and productivity through information technologies and efficient equipment operation, especially in large earthwork projects. Three-dimensional digitized ground data should be required for identifying the path of heavy equipment and work-site environment. Rapid development of terrain laser scanners (TLS) is more readily to acquire the digital data. This study suggests the '3D ground terrain processing platform (3DGTPP)' including data manipulating module and analyzing module of the scanned data for intelligent earthmoving equipment operation. The processing platform consists of six modules, including scanning, registering, manipulating, analyzing, transmitting, and storing. 3D ground terrain processing platform presented in this study will provide fundamental information for intelligent excavation system (IES), which will increase the efficiency of earthworks and safety of workers in significant.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.170-175
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• 2003

Ground and rock mass considered in tunnelling have characteristics such as uncertainty, heterogeneity and structural complexity because they have been formed undergoing various geological events for a long period. So, it is difficult for engineers to predict behaviors of rock mass in tunneling. In the paper the authors describe the development of an integrated expert system prototype for site investigation, design and construction in tunnelling and introduce the case applying this system to the tunnel construction site under construction. Geostructure Research Group in Korea Institute of Construction Technology (KICT) has developed the system during the past 4 years. The system mainly consists of several modules which is related to the design, construction and management of tunnelling. The test site, Neung-dong tunnel is located in Ulsan, Korea. The geology map shows it may confront big fault zone whose width is over kilometres. With the networking system of ITIS, various information of face mapping, monitoring and other construction task can be transmitted into the database and GIS Server at real time. And necessary analyses can be carried out with the modules equipped in the system.

• Journal of People, Plants, and Environment
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• v.23 no.3
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• pp.347-362
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• 2020

Background and objective: It is difficult to conclusively determine the exact cause of tree defects since multiple causes are involved such as climate change, plantation, tree quality and planting time, construction, planting base, drainage, sunshine conditions, maintenance, and microclimate. The data related to landscaping construction defects are scattered or fragmented by companies and years, but not managed systematically by the defect information management system. Most of the earlier studies associated with tree defects in apartment complexes suggested defect rates after examining tree defects in the completed construction site and proposed fragmentary and subjective conclusions about the causes of defects observed in trees with high defect rates. It is proposed to continue to conduct studies on the establishment and analysis of systematic databases to identify the exact causes of tree defects and measures to improve, and the need to accumulate systematic data in the construction process where many defects arises. This study was conducted to reduce the defects of trees planted in apartment complexes. Methods: Main factors related to tree defects were subdivided based on the results of literature review and a defect investigation at the completion site, and tree history management items were selected and subdivided during the construction stage. Results: The criteria for the preparation of subdivided items were obtained, and the tree history management checklist was written for the site under actual construction and a systematic database was established. Items that are categorized based to the causes of defects include the location of nurseries, date, tree quality, site conditions, planting techniques, microclimates, and maintenance. Conclusion: This study suggested tree history management items based on the tree defects that can be identified at the construction stage and applied them to the selected study site, which differentiates this study from earlier studies. It will be necessary to conduct a comprehensive and objective time series analysis on tree defects that occur over time by continuously monitoring and collecting data after construction.