• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.1139-1146
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• 2009

Collapse of cut slope includes many uncertainties in view of the reason and time. So, in the past, risky cut slopes have been dealt after they've been collapsed through post-management measures. But recently, advanced disaster prevention system is required, and as a part of that RTMS(Real-Time Monitoring System) was developed. In this study, stability of risky cut slope was evaluated by site investigation. To grasp deformation behavior characteristics of slope, numerical analysis based on FEM was performed and using results of that, specific standards for installation of Real-Time Monitoring System were suggested.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1216-1223
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• 2008

Displacement control of earth retaining wall is recognized as the most important item for insuring the stability of ground in urban deep excavation site near by major structure such as subway etc. The field monitoring system is classified by two types as manual system and automatic system. The application case of latter type of field monitoring is increased because real time measurement is possible in automatic system and that is correspondent with the recent constructional trend. Though the automatic monitoring system is more useful and advanced than manual monitoring system, accuracy of the system is not verified sufficiently. It was examined that the reliance of automatic monitoring system in this paper through the comparison of monitoring result obtained three urban excavation site in which the each type of monitoring system was executed concurrently. Result of the examination is that the two types of monitoring system is generally alike in view of monitoring result, so the engineering reliance of automatic system was confirmed in case site. This task was researched in restricted case site, it is expected more precise analysis from security of more data monitored and progressive study.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1259-1267
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• 2008

One of the most important item for insuring the stability of ground in urban deep excavation site near by major structure such as subway is displacement control of earth retaining wall. The field monitoring system is classified by two types as manual system and automatic system. The application case of latter type of field monitoring is increased because real time measurement is possible in automatic system and that is correspondent with the recent constructional trend. Though the automatic monitoring system is more useful and advanced than manual monitoring system, accuracy of the system is not verified sufficiently. It was examined that the reliance of automatic monitoring system in this paper through the comparison of monitoring result obtained one of deep urban excavation site in which the each type of monitoring system was executed concurrently. Result of the examination is that the two types of monitoring system is generally alike in view of monitoring result, so the engineering reliance of automatic system was confirmed in case site. This study was researched in restricted one case site, so it is expected more precise analysis from security of more data monitored and progressive study.

• Journal of KIBIM
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• v.11 no.2
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• pp.24-32
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• 2021

Recently, starting with smart construction research, interest in technology that automates construction site management using artificial intelligence technology is increasing. In order to automate construction site management, it is necessary to recognize objects such as construction equipment or workers, and automatically analyze the relationship between them. For example, if the relationship between workers and construction equipment at a construction site can be known, various use cases of site management such as work productivity, equipment operation status monitoring, and safety management can be implemented. This study derives a real-time object detection platform architecture that is required when performing construction site management using deep learning technology, which has recently been increasingly used. To this end, deep learning models that support real-time object detection are investigated and analyzed. Based on this, a deep learning model development process required for real-time construction site object detection is defined. Based on the defined process, a prototype that learns and detects construction site objects is developed, and then platform development considerations and architecture are derived from the results.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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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.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.57-65
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• 2012

PURPOSES : Efficiency Improvement of a public road construction project management work using the development of a real-time remote site monitoring system METHODS : In this study, we developed the remote site monitoring system using a web camera for road construction projects in the RCMA(Regional Construction Management Administration). We can be monitored a construction progress and a weak point of the situation in real time using this. To achieve this, we tested about 10 road construction projects ordered by RCMA. Then, we verified a applicability for the site monitoring system in future. RESULTS : Take advantage of the remote site monitoring system consists of the Construction CALS System, one of the business systems used in the part of the MLTM(Ministry of Land, Transport and Maritime Affairs) institution-agencies. Was configured to be served through the "Construction CALS System" of "Construction Management System(Contractors)" and the "Construction CALS Portal System". Through this, Benefit analysis through a pilot application of the 10 road construction sites and developing considerations and "Guide for visual information processing equipment installation-operating in construction sites"are presented. CONCLUSIONS : Through the establishment of remote site monitoring system can improve the efficiency of construction management services. In addition, Various disasters and calamities, accidents and illegal construction will be prevented in advance is expected. This is expected to further improve the quality of the facilities.

• 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.

• Smart Structures and Systems
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• v.21 no.2
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• pp.139-149
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• 2018

Understanding the current status of a construction project is necessary to achieve successful on-site management. Real-time information delivery is a major concern for construction industry practitioners in order to expedite decisions and discussions. We propose the use of a first personal view (FPV) system of a quadcopter drone as a tool for monitoring on-site status and communicating between construction participants. The most important function of the drone FPV system is its ability to visually monitor construction site situations in real time. An on-site management system process is developed, verified, and applied to several construction work tasks after determining factors that affect efficient construction management. The proposed system is expected to assist the construction manager in achieving high efficiency.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.781-788
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• 2003

It is an essential process to predict behaviors of ground and structure to seek economical efficiency and stability on the given environment. Predictions are conducted through analysis process of ground and structure. For these analyses, exact and quick acquisition of measuring data is required. But we face many difficulties in data acquisition stages due to the conditions of construction site. Therefore development of a powerful and effective monitoring system that can manage the integration of database and the implementation of measuring process in real time is strongly desired. This article shows an actual example of application of internet based monitoring system compared with the conventional monitoring system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.269-272
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• 2004

The target of this paper is the development of Web-based monitoring & control system which is for effective and economic management of mold manufacturing process. This system has three module; G-code Control, Monitoring Module and Result analysis module. Also, as the environment of development is based on internet, this system which is possible to the remote site management of manufacturing process works on Web. To be possible to control the manufacturing monitoring by client, each module is made ActiveX control and is based on socket communication. This system makes the foundation which is possible to manage the mold manufacturing process efficiently from remote site by matching real-time monitoring with manufacturing process in factory using G-code control and displaying the result of manufacturing using Ch-CGI.