• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.927-932
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• 2000

Recently, construction vibration has caused annoyance for a number of dwellers in nearby construction field and that induced from operating of large construction equipment, has become a very serious issue in our living environment. But, construction vibration standard of our living environment. But construction vibration standard of our country is efficient. Especially, directly blow method(diesel piling method, oil pressure method, etc) has caused much problems of highly impactive vibration. Construction works, in order to solve these problem, will be used SIP(Soilcement Injected Precast Pile) method of low vibration equipment. In this point, this study attempts to survey on the characteristics of piling vibration by SIP method for various earth conditions in construction field. And this study intends to get the basic data to establish a standard about construction vibration.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.91-92
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• 2022

The construction industry is highly dependent on human resources and changes the degree of completion of construction work depending on the level of performance of engineers. As women's social advancement has recently expanded, the construction industry is also experiencing a large influx. Therefore, it can be seen that not only male engineers' ability to carry out work but also female engineers' ability to carry out work is important. Therefore, this study investigated the actual work conditions and work performance capabilities of female engineers and presented them as basic data for the construction of work capability improvement measures.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.27-50
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• 2009

This paper describes an adaptive management approach for predicting, monitoring, and controlling ground movements associated with excavations in urban areas. Successful use of monitoring data to update performance predictions of supported excavations depends equally on reasonable numerical simulations of performance, the type of monitoring data used as observations, and the optimization techniques used to minimize the difference between predictions and observed performance. This paper summarizes each of these factors and emphasizes their inter-dependence. Numerical considerations are described, including the initial stress and boundary conditions, the importance of reasonable representation of the construction process, and factors affecting the selection of the constitutive model. Monitoring data that can be used in conjunction with current numerical capabilities are discussed, including laser scanning and webcams for developing an accurate record of construction activities, and automated and remote instrumentations to measure movements. Self-updating numerical models that have been successfully used to compute anticipated ground movements, update predictions of field observations and to learn from field observations are summarized. Applications of these techniques from case studies are presented to illustrate the capabilities of this approach.

• 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.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.329-333
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• 2008

As construction projects become getting bigger and complicated, the importance of resource management in construction sites is to be emphasized all the more than ever, but the reality is now gone far away leaving data filing and management dependent on the hands of in-field managers, which gives rise to a variety of problems such as decreased productivity. The manually-dependent data management makes it hard to acquire data and information needed for projects both quickly and correctly with abundant cost and endeavor by accumulating the related data, and efficient project management, being exemplified by such practical applications as Bar-code, RFID(Radio Frequency Identification), GPS(Global Positioning System), PDA(Personal Digital Assistants), USN(Ubiquitous Sensor Network) and DAT(Data Acquisition Technology). In this context literature survey is made theoretically, taken into account 14 classification of construction works, 31 types of work classification in CIS, Masterformat as follows;

• International conference on construction engineering and project management
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• 2020.12a
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• pp.443-452
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• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.290-293
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• 2003

The field organization management in construction industry is very important factor improvement and cost reduction. But, until now, evaluation methods on the existing field organization did not make ready and endeavor of organization betterment was insufficient in construction industry. The purpose of this study to provide basic data for reasonable selection and evaluation of the field manager through analyzing operation status of the existing field organization in apartment and office building project by interview and questionnaire on the 22 construction companies. This study presented optimal proposal on the selection and evalution of field manager for productivity improvement and cost reduction by means of efficient construction progress in apartment and dffice building project.

• Tunnel and Underground Space
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• v.8 no.2
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• pp.139-145
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• 1998

The reliable estimation of the system parameters and the accurate prediction of the system behavior are important to design underground structures safely and economically. Especially, the elastic modulus and the in-situ stresses are very important parameters in predicting the behavior of the underground structure. Therefore, the back analysis using the field measurement data is developed to determine accurately the elastic modulus and the in-situ stresses of the underground structural system in this study. A back analysis using the combined finite and boundary element is developed. It can consider the far field boundary condition and is efficient in computation. In this study, a back analysis is performed to predict behaviors of underground structures for the real construction site. The comparison between the results of the back analysis with field measurement data and the obtained material properties from the field test shows good agreement for the real construction site.

• Smart Media Journal
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• v.9 no.2
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• pp.99-109
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• 2020

This paper proposes a platform construction plan for the use of spectrum big data, collects and analyzes the big data in the radio wave field, establishes a linkage plan, and presents a support system scheme for linking and using the spectrum and public sector big data. It presented a plan to build a big data platform in connection with the spectrum public sector. In a situation where there is a lack of a support system for systematic analysis and utilization of big data in the field of radio waves, by establishing a platform construction plan for the use of big data by radio-related industries, the preemptive response to realize the 4th Industrial Revolution and the status and state of the domestic radio field. The company intends to contribute to enhancing the convenience of users of the big data platform in the public sector by securing the innovation growth engine of the company and contributing to the fair competition of the radio wave industry and the improvement of service quality. In addition, it intends to contribute to raising the social awareness of the value of spectrum management data utilization and establishing a collaboration system that uses spectrum big data through joint use of the platform.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.253-254
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• 2021

In the field of construction, research on smart construction technology is being actively pursued as a measure to increase productivity and efficiency. The technology that links 3D scanning and BIM of smart construction technology is in the limelight as a technology for checking the state of buildings in the field of architecture. It is thought that these techniques will be of great help in solving problems when the amount of inspection targets is large, such as confirmation of the rebar arrangement intervals, and therefore a large number of human resources are required. Therefore, in this study, we would like to apply 3D scanning to rebar construction to confirm whether the rebar arrangement can be confirmed according to the design drawing. In the study, the wall rebar of the rebar placed at the actual construction site was directly scanned to extract data, and the rebar placing status was confirmed through type analysis. As a result of analyzing the reinforcing bar arrangement state based on the data obtained by 3D scanning, it was found that the technology can be utilized.