• The Journal of Engineering Geology
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• v.32 no.2
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• pp.221-239
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• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• Journal of KIBIM
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• v.9 no.4
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• pp.10-20
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• 2019

As a result, the areas of knowledge that received the highest score in a positive impact were areas of risk management, while those that received the highest score in a negative impact were items of software management. In addition, each project was rated according to the score obtained. The distribution of grades by project was 71% for projects above middle grade and 29% for projects below middle grade. These results show that interest in BIM technology is increasing compared to the past, actual field application and research are actively being conducted, and that real construction sites also enjoy significant positive effects in terms of project management through BIM. In addition, the company is using BIM by applying advanced digital technologies such as AI technology, laser scanning technology and drone technology in line with the era of the fourth industrial revolution. Such a steady progress in future research on BIM technology development will reduce the number of low-grade projects and many middle-grade projects are expected to be upgraded to higher-level ones.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.381-382
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• 2023

Frequent accidents occur when workers at construction sites leave the safety zone, and particularly in the past 5 years, 9 fatal accidents occurred at the Korea Railroad Corporation due to train accidents on other tracks during track work. With the Severe Accident Punishment Act taking effect in January 2022, it is a priority to secure a safe work environment for workers at industrial (construction) sites. Therefore, there is a need to manage workers' departure from the safety zone (construction zone) and to facilitate communication within the construction zone. In this study, a mobile edge computing CCTV system is proposed that uses geofencing to determine whether workers are working in the danger zone, which can judge and respond in real-time to the ever-changing field environment. The proposed system is mobile and flexible, rather than server-based fixed CCTV. However, since it is designed mainly based on images, it has limitations in recognition rate depending on the environment such as distance, viewing angle, and illumination. As a way to compensate for this, it is required to develop more reliable equipment by combining technologies such as LiDAR and Radar.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.1
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• pp.11-19
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• 2019

Recently, with the development of the fourth industrial revolution that has been achieved through the fusion of information and communication technology (ICT), the technologies of AI, IOT, BIG-DATA, it is increasing utilization rate by industry and research and development of application technologies are being actively carried out. Especially, in the case of unmanned aerial vehicles, the construction market is expected to be one of the most commercialized areas in the world for the next decade. However, research on utilization of unmanned aerial vehicles in the construction field in Korea is insufficient. In this study, We have developed a quantitative building inspection method using the unmanned aerial vehicle and presented the protocol for it. The proposed protocol was verified by applying it to existing old buildings, and defect information could be quantified by calculating length, width, and area for each defect. Through this technical research, the final goal is to contribute to the development of safety diagnosis technology using unmanned aerial vehicle and risk assessment technology of buildings in case of disaster such as earthquake.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.95-103
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• 2023

With the increasing number of aging buildings across Korea, emerging maintenance technologies have surged. One such technology is the non-contact detection of concrete cracks via thermal images. This study aims to develop a technique that can accurately predict the depth of a crack by analyzing the temperature difference between the crack part and the normal part in the thermal image of the concrete. The research obtained temperature data through thermal imaging experiments and constructed a big data set including outdoor variables such as air temperature, illumination, and humidity that can influence temperature differences. Based on the collected data, the team designed an algorithm for learning and predicting the crack depth using machine learning. Initially, standardized crack specimens were used in experiments, and the big data was updated by specimens similar to actual cracks. Finally, a crack depth prediction technology was implemented using five regression analysis algorithms for approximately 24,000 data points. To confirm the practicality of the development technique, crack simulators with various shapes were added to the study.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.95-103
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• 2022

Recently, the fourth industrial revolution has a great influence on the development of many industries as well as the construction industry. Various technologies related to the industrial revolution 4.0, such as AI and big data, have gained much attention. However, little has been known about the importance and preparedness of stakeholders of the construction industry in Korea for the industry 4.0 technologies so far. This study revealed how the stakeholders perceive and prepare for industry 4.0 using a survey. In addition, collaboration potential score for each technology was calculated to find technologies with high potential for collaboration. Result is that the importance of the technologies was evaluated high in overall, but the preparedness and implementation in university education or business was evaluated low. Technologies with high potential for industry-university collaboration are AI/big data and 3D printing/3D scanning. This study can contribute to the training of industry 4.0 experts and improving preparedness, which would enable the innovation and application of industry 4.0 technologies in the construction industry.

• International Journal of High-Rise Buildings
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• v.12 no.4
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• pp.287-297
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• 2023

This paper briefly discusses current issues in wind engineering, including the enhancement of aerodynamic database and AI-assisted design, aerodynamic characteristics of tall buildings with atypical building shapes, application of computation fluid dynamics to wind engineering, evaluation of aerodynamic force coefficients based on a probabilistic method, estimation of tornadic wind speed (JEF scale) and effect of the Ekman Spiral on tall buildings.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.533-535
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• 2021

The differences between this study and previous studies are as follows. First, by building a cloud-based system using IoT technology, the system was built to monitor the status of buildings in real time from anywhere with an internet connection. Second, a model for predicting the future was developed using artificial intelligence (LSTM) and statistical (ARIMA) methods for the measured time series sensor data, and the effectiveness of the proposed prediction model was experimentally verified using a scaled-down building model. Third, a method to analyze the condition of a building more three-dimensionally by visualizing the structural deformation of a building by convergence of multiple sensor data was proposed, and the effectiveness of the proposed method was demonstrated through the case of an actual earthquake-damaged building.

• Journal of the Korea Institute of Building Construction
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• v.12 no.6
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• pp.664-673
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• 2012

Determining the layout of temporary facilities that support construction activities at a site is an important planning activity, as layout can significantly affect cost, quality of work, safety, and other aspects of the project. The construction site layout problem involves difficult combinatorial optimization. Recently, various artificial intelligence(AI)-based algorithms have been applied to solving many complex optimization problems, including neural networks(NN), genetic algorithms(GA), and swarm intelligence(SI) which relates to the collective behavior of social systems such as honey bees and birds. This study proposes a site facility layout optimization algorithm based on self-organizing maps(SOM). Computational experiments are carried out to justify the efficiency of the proposed method and compare it with particle swarm optimization(PSO). The results show that the proposed algorithm can be efficiently employed to solve the problem of site layout.

• Journal of the Korea Institute of Building Construction
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• v.7 no.3
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• pp.91-98
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• 2007

Recently a construction industry introduces information that brings about many advantages in the early planning phase, design phase and construction phase. Especially it replaces 2D, 3D systems(usually using explanation of drawing information) ai 4D CAD(offering a sort of 4D-having relation of construction schedule and 3D drawing information). Nevertheless a 4D has these benefits, it has limits which are not only usually using 3D modeling but also limit of making full use of practical affairs because of a lack of connecting varietals of progress of work. To solve these uppermost limits, this research is presenting unified systems to use in risk management which are efficient management of space and non-space information, space analysis, making full use of data base, introducing GIS system of easy interaction.