• Journal of KIBIM
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• v.8 no.3
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• pp.1-11
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• 2018

Gentrification is appearing in various areas. Especially commercial gentrification, the value of property is rising and it means the change of commercial sphere in revitalizing the underdeveloped commercial. In this study, Identify the process of increasing the franchise rate, which is changing gradually in commercial areas. We analyze prior studies on gentrification and franchise. Identify changing of land use distribution in Samcheong-dong area and analyze franchise change process. As a result of analyzing the changing of land use in Samcheong-dong area, the number of houses and other uses has continued to decrease. In the case of franchises, it increased sharply and in the case of general commercial, it steadily decreased. Looking at analyzing the franchise change process in Samcheong-dong area, In the franchise change process, there is very little change in land use from residential and other uses to general commercial. Representative spaces that show the process of franchise change are around the three-way streets, around the community service center and around the police station.

• Journal of KIBIM
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• v.9 no.1
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• pp.42-51
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• 2019

Maintenance of aging structures has attracted societal attention. Maintenance of the aging structure can be efficiently performed with a digital twin. In order to maintain the structure based on the digital twin, it is required to accurately detect the damage of the structure. Meanwhile, deep learning-based damage detection approaches have shown good performance for detecting damage of structures. However, in order to develop such deep learning-based damage detection approaches, it is necessary to use a large number of data before and after damage, but there is a problem that the amount of data before and after the damage is unbalanced in reality. In order to solve this problem, this study proposed a method based on Generative adversarial network, one of Generative Model, for generating acceleration data usually used for damage detection approaches. As results, it is confirmed that the acceleration data generated by the GAN has a very similar pattern to the acceleration generated by the simulation with structural analysis software. These results show that not only the pattern of the macroscopic data but also the frequency domain of the acceleration data can be reproduced. Therefore, these findings show that the GAN model can analyze complex acceleration data on its own, and it is thought that this data can help training of the deep learning-based damage detection approaches.

• Journal of KIBIM
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• v.9 no.3
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• pp.1-7
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• 2019

Digital twin technology has been actively developed to monitor and assess the current state of actual structures. The digital twin changes the traditional observation method performed in the field to the real-time observation and detection system using virtual online model. Thus, this study designed a digital twin model for a beam and examined the feasibility of the digital twin for bridges. To reflect the current state of the bridge, model updating was performed according to the field test data to construct an analysis model. Based on the constructed bridge analysis model, the relationship between strain and displacement was used to represent a virtual model that behaves in the same way as the actual structure. The strain and displacement relationship was expressed as a matrix derived using an approximate analytical theory. Then, displacements can be obtained using the measured data obtained from strain sensors installed on the bridge. The coordinates of the obtained displacements are used to construct a virtual digital model for the bridge. For verification, a beam was fabricated and tested to evaluate the digital twin model constructed in this study. The displacements obtained from the strain and displacement relationship agrees well with the actual displacements of the beam. In addition, the displacements obtained from the virtual model was visualized at the locations of the strain sensor.

• Journal of KIBIM
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• v.11 no.3
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• pp.75-90
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• 2021

A smart home system improves the elderly's quality of life by monitoring and analyzing their movements and health conditions with better health-care and social support services. Therefore, there has been an effort to adopt a smart home system for the independently living elderly. However, to the best of our knowledge, no study has investigated the usability of a smart home system on actual independently living elderly housing in long-term settings. Thus, this study aims to demonstrate the usability of a smart home system on independently living elders in living lab conditions. The BLE smart band and the BLE receiver were chosen for the smart home system to monitor the movement of the participants in their homes as well as to monitor the heart rates, step counts, sleep index. Nine independent living elderly from the senior welfare center in Kimjae participated in this living lab demonstration experiment for ten months. This demonstration experiment confirmed the effectiveness of low-cost and easily adoptable IoT-based BLE sensor sets on independent living elders and discussed the troubles and limitations of the experiment. By grasping the pros and cons of IoT-based BLE sensor sets, this study seeks to improve the accessibility and usability of smart home systems for the elderly population in independent living arrangements.

• Journal of KIBIM
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• v.8 no.4
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• pp.72-79
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• 2018

Rapid developments around the world have resulted in urban expansion, habitat destruction, habitat fragmentation, and pollution problems, which are the main reasons for the decline in biological diversity. The United Nations warns that many animals and plants will die out in the near future if this continues. This study was performed to propose a map of eco-corridor suitability analysis of Korean water deer(Hydropotes Inermis) to enhance biodiversity in Chuncheon city. Eight factors affecting habitat suitability were elevation, aspect, slope, forest type, distance to the road, distance to the stream, land use and green connectivity. Previous study analysis on the mobility behaviour of the Korean water deer(Hydropotes Inermis) produced a habitat suitability map by determining the threshold and assigning a value between 0 and 1 depending on the habitat suitability using the fuzzy function. A method of analysis was proposed for a number of eco-corridor through comparative analysis of the data from the produced habitat suitability map and the road-kill point. The previous studies were focused on Backdudaegan region and national parks except for urban cities. The potential habitat map of Korean water deer could be helpful as a way to prevent habitat disconnection and increase species diversity in urban areas.

• Journal of KIBIM
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• v.10 no.3
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• pp.54-62
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• 2020

There is growing consensus among planners and policymakers that brownfield remediation has positive impacts on neighborhoods in terms of housing prices, public health, and environmental quality. However, there is a limited understanding of how brownfield redevelopments spatially affect neighborhood housing turnover and stability. This paper addresses the spatial impacts of brownfield redevelopments on neighboring housing turnover in Cuyahoga County, Ohio. This study examines housing turnover before and after the remediation of brownfield sites countywide and in housing submarkets stratified by household income. Based on housing sales data between 1996 and 2007, the extended Cox Hazard model with the difference-in-difference approach is employed to clarify the causal relationships between brownfield redevelopments and neighboring housing turnover. Additionally, along with the results of the previous study examining impacts of brownfield remediation on nearby housing prices, this paper estimates the change of neighborhood stability due to brownfield redevelopments based on both attributes of housing prices and turnovers.

• Journal of KIBIM
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• v.10 no.4
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• pp.11-21
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• 2020

With increasing interest and research on smart cities, there is also an increasing number of studies on urban facilities that can be built within smart cities. According to these studies, smart cities' urban facilities are likely to become high value-added industries. However, the concept of smart city is not clear because it involves various fields. Therefore, in this study, the definition of Next-Generation(N.G) Smart City Facilities with Digital Twin and Digital Chain is carried out through a multidisciplinary approach. Based on this, Next-Generation Smart City Facilities will be divided into High Value-Added Products and Big Data Platforms. Subsequently, the definition of the Digital Chain containing the data flow of the entire process built through the construction of the Digital Twin proceeds. The definitions derived are applied to the Next-Generation Noise Barrier Tunnel to ensure that data is exchanged at the Digital Twin stage, and to review the proposed configuration of the Digital Chain and Data Flow in this study. The platform definition and Digital Chain of Next-Generation Smart City Facilities proposed in this study suggest that it can affect not only the aspects of data management that are currently in the spotlight, but also the manufacturing industry as a whole.

• Journal of KIBIM
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• v.11 no.1
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• pp.31-38
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• 2021

The design principles of new urbanism (NU) have been adopted for new towns-in town projects for inner city neighborhoods in Seoul, Korea Since 2000. Here, ten NU principles were matched to four urban design categories: streets, land use, housing and buildings, and public open spaces. These elements were analyzed for Eunpyung New Town project. Through the case, the applications and implications NU principles are explored. The principles of connectivity, quality architecture and urban design, increased density, green transportation, sustainability, and quality of life were positively and successively adopted for streets, land use, housing and buildings, and public open spaces. The principles of mixed-use and diversity and traditional neighborhood structure were only partially applied in land use, housing and buildings, and public open spaces. It should be note that the walkability principle is intended not for job-housing proximity, but for pedestrian-friendly street design.

• Journal of KIBIM
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• v.9 no.4
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• pp.75-83
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• 2019

Recent data development has made it possible to analyze each individual's daily commuting by using transportation card transaction. This research utilizes about 1 million observations from the subway line no.7 of Seoul metropolitan transportation data. By using such a massive dataset, the authors try to identify daily travel behavior of morning commute and its possible relationship between subway usage and socio-economic factors. There are 4 main types of users and their travel behavior, and top 15 stations with the most users for arrival and departure are selected. Accordingly, 15 stations have distinctive characteristics including population density and the number of businesses around stations. To identify this fact, the 4 most populated stations are selected and their socio-economic factors are examined. According to the analysis, the most departure stations are generally surrounded by hihgly populated residential areas, whereas the most arrival stations are stood within the job concentrated districts.

• Journal of KIBIM
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• v.10 no.2
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• pp.21-28
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• 2020

As the number of aging bridges increases, more studies are being conducted on developing effective and reliable methods for the assessment and maintenance of bridges. With the advancement in new sensing systems and data learning techniques through AI technology, there is growing interests in how to evaluate bridges using these advanced techniques. This paper presents a CNN(Convolution Neural Network) deep learning based technique for evaluating the damage existence and for estimating the damage location in PSC bridges using static strain data. Simulation studies were conducted to investigate the proposed method with error analysis. Damage was simulated as the reduction in the stiffness of a finite element. A data learning model was constructed by applying the CNN technique as a type of deep learning. The damage status and its location were estimated using data set built through simulation. It was assumed that the strain gauges were installed in a regular interval under the PSC bridge girders. In order to increase the accuracy in evaluating damage, the squared error between the intact and measured strains are computed and applied for training the data model. Considering the damage occurring near the supports, the results of error analysis were compared according to whether strain data near the supports were included.