• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.261-262
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• 2023

Drone is a suitable equipment for capturing images of cracks at construction sites based on its efficient mobility and high-resolution image acquisition capabilities. In this study, drone was used to acquire indoor construction sites framework images and deep learning technology was applied to detect cracks and measure width, and size. Finally, the usability of the process was verified based on the indoor crack monitoring system.

• Journal of Korean Association for Spatial Structures
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• v.22 no.2
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• pp.19-27
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• 2022

Visual inspection methods have limitations, such as reflecting the subjective opinions of workers. Moreover, additional equipment is required when inspecting the high-rise buildings because the height is limited during the inspection. Various methods have been studied to detect concrete cracks due to the disadvantage of existing visual inspection. In this study, a crack detection technology was proposed, and the technology was objectively and accurately through AI. In this study, an efficient method was proposed that automatically detects concrete cracks by using a Convolutional Neural Network(CNN) with the Orthomosaic image, modeled with the help of UAV. The concrete cracks were predicted by three different CNN models: AlexNet, ResNet50, and ResNeXt. The models were verified by accuracy, recall, and F1 Score. The ResNeXt model had the high performance among the three models. Also, this study confirmed the reliability of the model designed by applying it to the experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.467-471
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• 1997

AGV is very proper equipment for Port Automation. AGV must have Obstacle Detection System(ODS) for port automation. Obstacle Detection System must have some functions. It must be able to classify some specified object from background data. And it must be able to track classified objects. Finally, ODS must determine its next action for safe cruise whether it must do emergency stop or it must speed down or it must change it track. For these functions, ODS can have many different structure. In this paper, we will propose one structure among some possible own which is under construction.

• Convergence Security Journal
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• v.21 no.2
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• pp.11-18
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• 2021

To protect tangible and intangible assets, most of the companies are conducting information protection monitoring by using various security equipment in the IT service network. As the security equipment that needs to be protected increases in the process of upgrading and expanding the service network, it is difficult to monitor the possible exposure to the attack for the entire service network. As a countermeasure to this, various studies have been conducted to detect external attacks and illegal communication of equipment, but studies on effective monitoring of the open service ports and construction of illegal communication monitoring system for large-scale service networks are insufficient. In this study, we propose a framework that can monitor information leakage and illegal communication attempts in a wide range of service networks without large-scale investment by analyzing 'Netflow statistical information' of backbone network equipment, which is the gateway to the entire data flow of the IT service network. By using machine learning algorithms to the Netfllow data, we could obtain the high classification accuracy of 94% in identifying whether the Telnet service port of operating equipment is open or not, and we could track the illegal communication of the damaged equipment by using the illegal communication history of the damaged equipment.

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

• 유공압시스템학회:학술대회논문집
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• 2010.06a
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• pp.56-61
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• 2010

Simulator is a development equipment which enables the ECU to operate in normal mode by simulating the interface signal between ECU and mechanical system electrically. Embedded simulator means simulation function is embedded in ECU firmware, hence the electrical signal interface is replaced by the substitution of information at system program level. This paper explains the development of embedded transmission simulator for the verification of TCU firmware function which covers shifting control and on-board diagnosis. The embedded simulation program is executed in TCU processor along with the TCU firmware and it provides TCU firmware with not only the speed information those are appropriate both in driving and shifting conditions, but also the fault detection signals. Experimental results show that the validity of embedded simulator and its usefulness to the TCU firmware development and verification.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.373-376
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• 2007

The construction industry is an inevitable part of modem development. Now-a-days, the construction industry experiencing several issues related with the maintenance of productivity, quality and labor. Hence there is an immediate requirement for the development of technologies enabling the automated construction equipment. The new technologies should also assure the sufficient safety and efficiency. In the present investigation, an attempts have been made for the development of object sensing algorithm and safety control system for intelligent excavating system. we have analyzed some elemental technologies for sensing objects and also proposed a technology for safety control system as well. The proposed technology will highly influence the safe working performance of construction industry in the positive sense.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.178-191
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• 2020

Purpose: This paper proposes a performance evaluation method for state-of-the-art facility inspection/diagnostic equipment through a trend survey of equipment and standardization systems of US, Japan, and Korea. This paper also suggests the priority of developing a performance evaluation method through expert interviews and surveys. Method: In this study, report for the last 5 years of FMS, state-of-the-art equipment of facility maintenance companies/safety diagnosis specialist agencies and papers/research reports/patents of NTIS were analyzed to identify recent trends of facility inspection/diagnostic equipment usages. standardization system of US, Japan, and Korea were analyzed to figure out a suitable form of a performance evaluation method for the domestic situation. And expert interview and survey were conducted to identify the priority of developing a performance evaluation method. Result: The performance evaluation method must be developed by the shape that only evaluates performance, regardless of types of equipment, on inspection item level for creative technology development. The priority of developing the performance evaluation method was identified as crack detection of concrete for durability evaluation and displacement/deformation/fatigue detection of concrete and steel for stability evaluation. Conclusion: The performance evaluation method will be developed firstly for the crack detection of concrete for durability evaluation and displacement/deformation/fatigue detection of concrete/steel for stability evaluation. In order to promote creative technology development, the performance evaluation method should be developed in a form that provides standardized specimens or testbeds and can be applied regardless of types of technologies.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.39-52
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• 2021

Purpose: Recently, due to increasing usage of high-tech equipment for facility inspection, the need of verifying high-tech equipment is being emphasized. Therefore, the purpose of this paper is to develop performance evaluation methodology of tunnel scanners that inspect tunnel facilities. Method: This paper describes literature reviews regarding the performance evaluation methodology of high-tech based equipment for facility inspection. Based on these investigations and expert advisory meetings, this paper suggests a performance evaluation methodology of tunnel scanner. Result: First evaluation indicator states minimum performance standards of tunnel scanners. Second evaluation indicator is related to tunnel scanner quality. Conclusion: The performance evaluation methodology can provide reliable equipment performance catalogues, helping users to make a proper selection of equipment. Also, developers of equipment can get authorized verification of performances, preventing poor maintenance of facilities.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.359-366
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• 2021

In this study, It was developed an monitoring cracks system based on image processing techniques in order to measure cracks, which are major damages in concrete, and to convert them into a database. The crack monitoring system consists of crack image captured equipment and a crack detection and analysis software. This system provides objective and quantitative data by replacing the conventional visual inspection. The crack detection algorithm w as verified through an indoor test using virtual cracks, and the amount of crack detection and crack width change was monitored by applying it to the self-healing repair mortar construction site. In the case of the crack width detected through image analysis, the maximum difference from the actual crack width was 0.0334mm. It was possible to detect microcracks of 0.1mm or less, and the effect of crack healing over time of the self-healing repair mortar was confirmed trough the field test.