• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.544-547
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• 2008

In 1990, Korea building contractors were indifferent maintenance management cause focus on completion of construction before construction collapsed. Currently, structures monitoring systems are restrictive on large structures. Structures monitoring systems are limited many old and small structures in the whole nation. Recently, we make efforts application Ubiquitous technology as like sensor, sensor network system, and wireless communication system in construction. This paper applies bridge management system using Ubiquitous skill which is real-time monitoring report offering system.

• Steel and Composite Structures
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• 제49권6호
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• pp.701-711
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• 2023

In order to fully reflect variation characteristics of composite concrete dam health state, the monitoring data is applied to diagnose composite concrete dam health state. Composite concrete dam lesion development to wreckage is a precursor, and its health status can be judged. The monitoring data are generally non-linear and unsteady time series, which contain chaotic information that cannot be characterized. Thus, it could generate huge influence for the construction of monitoring models and the formulation of corresponding health diagnostic indicators. This multi-scale diagnosis process is from point to whole. Chaotic characteristics are often contained in the monitoring data. If chaotic characteristics could be extracted for reflecting concrete dam health state and the corresponding diagnostic indicators will be formulated, the theory and method of diagnosing concrete dam health state can be huge improved. Therefore, the chaotic characteristics of monitoring data are considered. And, the extracting method of the chaotic components is studied from monitoring data based on fuzzy dynamic cross-correlation factor method. Finally, a method is proposed for formulating composite concrete dam health state indicators. This method can effectively distinguish chaotic systems from deterministic systems and reflect the health state of concrete dam in service.

• 한국터널공학회:학술대회논문집
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• 한국터널공학회 2005년도 학술발표회 논문집
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• pp.189-201
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• 2005

Brittle failure has been detected in over-stressed rock mass during the construction of oil storage cavern. The main characteristics of stress induced brittle failure of the site are introduced. Various evaluation and measures are sought to stabilize the over-stressed rock mass. The major results from numerical analysis of the cavern are presented, and from current microseismic monitoring to detect hazard from brittle failure are presented.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.662-663
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• 2015

Despite the improvement of productivity and cost, the operating of such equipments yet has been recognized as a 3D business which is a low wage and poor working environment business field. Accordingly, the number of such operators has been decreasing by time. Especially, construction equipment demands higher controlling skills and occasionally involved in critical accidents. Therefore, this study aims to suggest a conceptual design for an construction equipment Around View Monitoring system that visually assists the operator for more efficient operating. It is expected that the application of such technology for a construction equipment highly improves the productivity and work quality, moreover, prevents disastrous accidents that occur to labors.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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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.

• 한국재난정보학회 논문집
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• 제17권1호
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• pp.53-59
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• 2021

연구목적 및 방법: 본 논문은 지반구조물 계측센서의 내구연한 기준에 대한 분석적 연구로 국내 건설공사 발주기관의 건설 계측센서에 대한 내구연한 기준과 조달청의 건설계측 및 건설기계 관련 내용연수 기준을 분석하였다. 연구결과: 지반구조물에 설치되기 전 조달청에서 물품 자체로 구매하는 경사계와 변형률계 등의 내구연한 기준은 8년에서 10년을 제시하고 있다. 결론: 국내외 댐에 설치된 각종 계측센서의 신뢰성 비교를 통한 실제적인 내구연한 분석과 터널에 설치된 유지관리 계측센서의 경과연수에 대한 손망실율 등을 종합 검토한 결과 구조물이나 지반에 설치된 국내 간극수압계 및 토압계 등의 매립식 계측센서의 적정 내구연한은 5년에서 8년이 합리적인 것으로 판단된다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 가을학술발표대회논문집
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• pp.165-166
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• 2023

Construction inspection and monitoring are key activities in construction projects. Automation of inspection tasks improves the limitations and inefficiencies of manual construction inspections, enabling systematic and consistent construction inspections. In this paper, an RTSP (Real-Time Streaming Protocol) system is used to remotely manage and supervise the construction site without having to visit the construction site by deploying a robot on site on behalf of four construction stakeholders (owner, supervisor, constructor, and designer). I would like to propose. The proposed system can contribute to identifying and monitoring the process process and work results at the construction site in real time.

• Structural Monitoring and Maintenance
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• 제2권4호
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• pp.357-382
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• 2015

This paper provides an overview of the use of different Distributed Optical Fiber Sensor systems (DOFSs) to perform Structural Health Monitoring (SHM) in the specific case of civil engineering structures. Nowadays, there are several methods available for extracting distributed measurements from optical fiber, and their use have to be according with the aims of the SHM performance. The continuous-in-space data is the common advantage of the different DOFSs over other conventional health monitoring systems and, depending on the particular characteristics of each DOFS, a global and/or local health structural evaluation is possible with different accuracy. Firstly, the fundamentals of different DOFSs and their principal advantages and disadvantages are presented. Then, laboratory and field tests using different DOFSs systems to measure strain in structural elements and civil structures are presented and discussed. Finally, based on the current applications, conclusions and future trends of DOFSs in SHM in civil structures are proposed.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 봄 학술논문 발표대회
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• pp.255-256
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• 2021

The performance measurement of construction projects has traditionally been evaluated as a prerequisite for successful project completion. Considering this importance, the UK and the US are operating quantitative performance measurement systems for construction projects. However, in the case of Korea, there is a limit to the use of existing methods due to the limitation of data collection. Recently, in consideration of the domestic situation, research is being conducted to measure the quantitative performance of a project by using big data including progress and project attribute information. Therefore, this study aims to present the design direction of a performance monitoring system using Quality Function Deployment.

• Smart Structures and Systems
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• 제20권2호
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• pp.163-173
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• 2017

Structural health monitoring (SHM) of civil infrastructure using fiber Bragg grating sensor networks (FBGSNs) has received significant public attention in recent years. However, there is currently little research on the health-monitoring technology of high-piled wharfs in coastal ports using the fiber Bragg grating (FBG) sensor technique. The benefits of FBG sensors are their small size, light weight, lack of conductivity, resistance corrosion, multiplexing ability and immunity to electromagnetic interference. Based on the properties of high-piled wharfs in coastal ports and servicing seawater environment and the benefits of FBG sensors, the SHM system for a high-piled wharf in the Tianjin Port of China is devised and deployed partly using the FBG sensor technique. In addition, the health-monitoring parameters are proposed. The system can monitor the structural mechanical properties and durability, which provides a state-of-the-art mean to monitor the health conditions of the wharf and display the monitored data with the BIM technique. In total, 289 FBG stain sensors, 87 FBG temperature sensors, 20 FBG obliquity sensors, 16 FBG pressure sensors, 8 FBG acceleration sensors and 4 anode ladders are installed in the components of the back platform and front platform. After the installation of some components in the wharf construction site, the good signal that each sensor measures demonstrates the suitability of the sensor setup methods, and it is proper for the full-scale, continuous, autonomous SHM deployment for the high-piled wharf in the costal port. The South 27# Wharf SHM system constitutes the largest deployment of FBG sensors for wharf structures in costal ports to date. This deployment demonstrates the strong potential of FBGSNs to monitor the health of large-scale coastal wharf structures. This study can provide a reference to the long-term health-monitoring system deployment for high-piled wharf structures in coastal ports.