• International conference on construction engineering and project management
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• 2022.06a
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• pp.136-144
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• 2022

Construction sites are characterized by dangerous situations and environments that cause fatal accidents. Potential risk detection needs to be improved by continuously monitoring site conditions. However, the current labor-intensive inspection practice has many limitations in monitoring dangerous conditions at construction sites. Computer vision technology that can quickly analyze and collect site conditions from images has been in the spotlight as a solution. Nonetheless, inspection results obtained via computer vision are still stored and managed in centralized systems vulnerable to tampering with information by the central node. Blockchain has been used as a reliable and efficient decentralized information management system. Despite its potential, only limited research has been conducted integrating computer vision and blockchain. Therefore, to solve the current safety management problems, the authors propose a framework for construction site inspection that integrates object detection and blockchain network, enabling efficient and reliable remote inspection. Object detection is applied to enable the automatic analysis of site safety conditions. As a result, the workload of safety managers can be reduced with inspection results stored and distributed reliably through the blockchain network. In addition, errors or forgery in the inspection process can be automatically prevented and verified through a smart contract. As site safety conditions are reliably shared with project participants, project participants can remotely inspect site conditions and make safety-related decisions in trust.

• 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.

• Korean Journal of Computational Design and Engineering
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• v.5 no.1
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• pp.33-41
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• 2000

A monitoring and control system, as a broker to connect work-fields with higher departs, gives a great effect on capacity and reliability of a manufacturing system. However, it is very difficult to construct an integrated monitoring control system in a shop with diverse equipment. This paper proposes a CORBA based scheme to construct an integrated system for monitoring and control of equipment in a machining shop. The system is developed by applying the object oriented technology. Thus, its design and maintenance are not only early but it can cope with variation of production situation flexibly. Finally, we introduce a prototype using a milling machine, a robot, PLC's, etc.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.1237-1244
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• 2006

This research discussed about method for basis construction of sea jacket construction. Several access ways of method for foundation construction of sea jacket construction are used. Accompany many efforts of design and build process to overcome the form of construction work and application equipment, special quality of construction and restriction and so on of sea environment in the case of pile foundation. Therefore, great many factor of sea condition, construction special quality, base condition, construction time, equipment composition, worker composition etc. shows other work form in spot at sea jacket construction process.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.841-844
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• 2005

Computer vision technology can be used to interpret the images captured by web cameras installed on construction sites to automatically quantify the results. This information can be used for quality control, productivity measurement and to direct construction. Steel frame construction is particularly well suited for automatic monitoring as all structural members can be viewed from a small number of camera locations, and three-dimensional computer models of steel structures are frequently available in a standard electronic format. A system is being developed that interprets the 3-D model and directs a camera to look for individual members as regular intervals to determine when each is in place and report the results. Results from a simple lab-scale system are presented along with preliminary full-scale development.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.354-356
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• 2015

As domestic recession has had an adverse impact on many Korean companies in Korea, financial soundness has become a critical issues. It is essential to identify financial risk factors to prevent workout as well as to improve the financial condition of domestic construction companies. Therefore, this study derived important management indicators and the financial ratios that belong to each indicator through a comparative analysis between healthy companies and workout companies with financial statement. As a consequence, key financial ratios are derived into 3 of 25 ratios; Equity Ratio in stability indicator, Total Asset Turnover Ratio in activity indicator, and Labor Equipment Ratio in productivity indicator. So, Korean construction firms are required close monitoring these critical financial ratios indicating variation between construction companies which have opposing statuses in finance in order to keep sound financial condition and increase productivity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.623-629
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• 2012

During the construction of crossing engineering one of the important measures to ensure the safety of subway operation is the implementation of deformation surveying to the existing subway tunnel. Guangzhou new subway line 2 engineering which crosses the existing tunnel is taken as the background. How to achieve intelligent and automatic deformation surveying forecast during the subway tunnel construction process is studied. Because large amount of surveying data exists in the subway construction, deformation analysis is difficult and prediction has low accuracy, a subway intelligent deformation prediction model based on the PBIL and support vector machine is proposed. The PBIL algorithm is used to optimize the exact key parameters combination of support vector machine though probability analysis and thereby the predictive ability of the model deformation is greatly improved. Through applications on the Guangzhou subway across deformation surveying deformation engineering the prediction method's predictive ability has high accuracy and the method has high practicality. It can support effective solution to the implementation of the comprehensive and accurate surveying and early warning under subway operation conditions with the environmental interference and complex deformation.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.39-51
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• 2017

Recently, looking at construction sites with either large or small scale, accidents like collision, fall, etc. occur often. These accidents lead to not only damage of human lives but also serious economic loss. In case of large scale constructions sites, safety management systems are used to reduce industrial accidents. However in construction sites with small scale, those systems cannot be applied due to problems such as lack of compatability and high installation expense. In this case, just by putting on safety gears can also reduce industrial accidents. Therefore, in this paper, a safety management systems that can be used at both large and small scale construction sites is proposed. This safety management system consists of a smart module, a repeater and a gateway, and a monitoring system. The smart module, which is detachable, is attached to a safety helmet. This module transfers the current status of the user to the monitoring system through the repeater and the gateway. The repeater transfers the data received from the smart module to the gateway, and the gateway sends the data from the repeater to the monitoring system. The monitoring system shows the user status to the safety supervisor by displaying the data - temperature, height, intensity of illumination, images - received from the smart module. The safety supervisor can monitor the user status in real-time and take immediate action in case of emergency through this monitoring system.

• Journal of Drive and Control
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• v.18 no.1
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• pp.24-30
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• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.3
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• pp.87-95
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• 2021

The Doam Lake Watershed is one of Gangwon-do's non-point source management areas. This area has a lot of snowfall in winter, and it is expected that there will be a lot of soil erosion in early spring due to snow melting. In this study, snow melting was monitored in the Doam Lake watershed from February to 3, 2020. It was conducted to analyze the water quality changes by calculating the concentration of non-point source pollution caused by snowmelt, and to compare the concentration of water quality during snowmelt event with rainfall and non-rainfall event. As a result of water quality analysis, Event Mean Concentration (EMC) at the first monitoring was SS 33.9 mg/L, TP 0.13 mg/L, TN 4.33 mg/L, BOD 1.35 mg/L, TOC 1.84 mg/L. At the second monitoring, EMC were SS 81.3 mg/L, TP 0.15 mg/L, TN 3.12 mg/L, BOD 1.32 mg/L, TOC 3.46 mg/L. In parameter except SS, it showed good water quality. It is necessary to establish management measures through continuous monitoring.