• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.53-54
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• 2023

Because irregular shaped buildings are designed with various three-dimensional curves, the difficulty of design and construction is very high, and more construction drawings are needed to reduce construction errors. General 2D drawings may have limitations in conveying the information necessary for construction. By utilizing BIM, it is possible to three-dimensionally design parts that are not expressed on 2D drawings and additional structurall components required for the construction of the curved exterior finishing materials. This study examines the necessity of BIM at the construction stage, its performance through it, and how it can be linked to smart construction technology through construction BIM being applied to the new construction site of Sejong-Pocheon Line Cheoin Rest Area.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.14-15
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• 2018

Logistics facilities are characterized by wide spans and high flooring, most of which are constructed with PC (Precast Concrete) methods to meet a wide range of commercial and industrial needs. However, the PC structure is a pin joint design, and the construction cost is increased due to the restrictions caused by the installation process, and the construction period is lengthened. In order to solve the above problem, SMART Frame, which is a structural system similar to the steel frame structure, was developed by embedding a steel frame at both ends of the PC. The purpose of this study is to analyze the erection time reduction effect of steel connected precast concrete components (SMART frames) for long span and heavy loaded logistics buildings compared to existing PC frames. For this study, a logistics building constructed with pin joint PC components is selected as a case. The result is compared with the existing PC frame to confirm the erection time reduction effect.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.6
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• pp.471-474
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• 2020

In recent years, the challenge of higher energy efficiency has emerged as urban buildings have become taller, and the area of window glasses has increased. To address the problem of energy efficiency in buildings, research on smart windows is being actively conducted. In this study, an accelerated experiment for thermal stability was conducted to fabricate a liquid crystal cell applicable to external windows. It was confirmed from the study that the function is maintained even in a high-temperature external environment through the change in transmittance by voltage. Compared with the initial transmittance, after the passage of time, the smart window cell to which the sealant was applied showed a small change in transmittance of 1~2%. This result confirmed the thermal stability of the liquid crystal-based smart window.

• Smart Structures and Systems
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• v.11 no.5
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• pp.435-451
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• 2013

High-rise buildings are a common feature of urban cities around the world. These flexible structures frequently exhibit large vibration due to strong winds and earthquakes. Structural control has been employed as an effective means to mitigate excessive responses; however, structural control mechanisms that can be used in tall buildings are limited primarily to mass and liquid dampers. An attractive alternative can be found in outrigger damping systems, where the bending deformation of the building is transformed into shear deformation across dampers placed between the outrigger and the perimeter columns. The outrigger system provides additional damping that can reduce structural responses, such as the floor displacements and accelerations. This paper investigates the potential of using smart dampers, specifically magnetorheological (MR) fluid dampers, in the outrigger system. First, a high-rise building is modeled to portray the St. Francis Shangri-La Place in Philippines. The optimal performance of the outrigger damping system for mitigation of seismic responses in terms of damper size and location also is subsequently evaluated. The efficacy of the semi-active damped outrigger system is finally verified through numerical simulation.

• Wind and Structures
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• v.36 no.4
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• pp.237-247
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• 2023

The emergence of high-rise buildings has necessitated frequent structural health monitoring and maintenance for safety reasons. Wind causes damage and structural changes on tall structures; thus, safe structures should be designed. The pressure developed on tall buildings has been utilized in previous research studies to assess the impacts of wind on structures. The wind tunnel test is a primary research method commonly used to quantify the aerodynamic characteristics of high-rise buildings. Wind pressure is measured by placing pressure sensor taps at different locations on tall buildings, and the collected data are used for analysis. However, sensors may malfunction and produce erroneous data; these data losses make it difficult to analyze aerodynamic properties. Therefore, it is essential to generate missing data relative to the original data obtained from neighboring pressure sensor taps at various intervals. This study proposes a deep learning-based, deep convolutional generative adversarial network (DCGAN) to restore missing data associated with faulty pressure sensors installed on high-rise buildings. The performance of the proposed DCGAN is validated by using a standard imputation model known as the generative adversarial imputation network (GAIN). The average mean-square error (AMSE) and average R-squared (ARSE) are used as performance metrics. The calculated ARSE values by DCGAN on the building model's front, backside, left, and right sides are 0.970, 0.972, 0.984 and 0.978, respectively. The AMSE produced by DCGAN on four sides of the building model is 0.008, 0.010, 0.015 and 0.014. The average standard deviation of the actual measures of the pressure sensors on four sides of the model were 0.1738, 0.1758, 0.2234 and 0.2278. The average standard deviation of the pressure values generated by the proposed DCGAN imputation model was closer to that of the measured actual with values of 0.1736,0.1746,0.2191, and 0.2239 on four sides, respectively. In comparison, the standard deviation of the values predicted by GAIN are 0.1726,0.1735,0.2161, and 0.2209, which is far from actual values. The results demonstrate that DCGAN model fits better for data imputation than the GAIN model with improved accuracy and fewer error rates. Additionally, the DCGAN is utilized to estimate the wind pressure in regions of buildings where no pressure sensor taps are available; the model yielded greater prediction accuracy than GAIN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5904-5927
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• 2019

Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.37-46
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• 2006

In this study, the efficacy of the newly developed smart passive control system to improve seismic performance of base isolated building structures is numerically verified. The smart passive control system consists of a magnetorheological (MR) damper and an electromagnetic induction (EMI) part. The damping characteristics of an MR damper can be controlled by the current generated in an EMI part according to the Faraday's law of electromagnetic induction. An EMI part consisting of a permanent magnet and a solenoid coil could substitute a control system including sensors, a controller and an external power supply in a conventional smart control system. The benchmark control problem for a base isolated building presented by the american society of civil engineers is considered for numerical simulation. The control performance of the smart passive control system is compared to that of the conventional smart control system using MR dampers. It is demonstrated from the numerical simulation results that the smart passive control system is useful to improve the seismic performance of base isolated buildings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.664-671
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• 2020

A Smart Building, one that uses automated processes to control its operations, refers in this study to one that uses both Internet of Things (IoT) devices and cloud services software. Cloud service providers (e.g. Amazon, Google, and Microsoft) have recently providedIoT cloud platform application services on IoT devices. According to Postscapes, there are now 152 IoT cloud platforms. Choosing one for a smart building is challenging. We selected Microsoft Azure IoT Hub and Amazon's AWS (Amazon Web Services) IoT. The two platforms were evaluated and selected from a smart building perspective. Each prototype was evaluated on two different IoTplatforms, assuming a typical smart building scenario. The selection was based on information and experience gained from developing the prototype system using the IoT cloud platform. The assessment made in this evaluation may be used to select an IoTcloud platform for smart buildings in the future.

• Electronics and Telecommunications Trends
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• v.34 no.5
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• pp.36-47
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• 2019

Smart window technology has become a major component of smart buildings, leading to energy savings and enhanced functionality. Smart windows work like curtains or blind screens, blocking external light sources. Smart window components employ electrochromic or photochromic materials that can selectively block sunlight when electricity is applied. The installation of low-E glass and building-integrated photovoltaics (BIPV) is being encouraged in accordance with the policy on saving building energy. To incorporate BIPV into smart windows, the transparency and colors of transparent photovoltaics must be optimized. The power sources required to operate these smart windows take advantage of the transparent color of the solar cells, which also facilitates aesthetics. Self-powered smart windows that combine electrochromic or photochromic screens with transparent solar cells suggest a promising convergent technology.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.143-153
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• 2021

Recently, by applying the 4th industrial revolution technologies such as A.I., IoT, and big data to general residential infrastructure, various application services of residential-based are provided to residents through linkage and utilization between technologies. Accordingly, smart housing system is increasing as advanced living spaces that can improve the quality of life and convenience of residents. Such a smart housing is expected to be an item that can create new demands and markets in the construction industry since it provides a new paradigm that combines construction technology and IT by combining IT technology with existing construction industry. Based on this, it is expected that it will be possible to gradually develop large-scale markets such as smart buildings and smart cities. In this paper, therefore, we propose an artificial intelligence multiplex smart housing system as an intelligent platform that can autonomously manage and control the size of places and spaces, used for various purposes based on smart housing technology by using artificial intelligence systems.