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Prof. Dongjun Suh
Department of Convergence & Fusion System Engineering, Kyungpook National University, Sangju 37224, Korea

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0 Machine Learning
0 AI
0 Smart control
0 Energy ICT

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Journal article
Published: 04 August 2021 in Sustainable Energy Technologies and Assessments
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Because of the unavailability of standard renewable power generation capacity and the ambiguous sales methods for each building type, there has been indiscriminate installation of renewable energy sources to increase the mandatory installation rate of renewable energy. Importantly, campus buildings are high energy-consuming buildings that have considerable energy-saving potential. Herein, we present a model that maximizes the total life cycle cost (LCC) of a building using energy simulation programs (EnergyPlus & DesignBuilder) by considering various costs and efficiencies depending on the capacity and efficiency of the photovoltaic (PV) and ground-source heat pumps (GSHP) systems and optimization analysis using heuristic solution and multi-objective genetic algorithm. Based on economic factors, a Korean campus residential building was used as a case study, and the expense of the optimization models of seven applicable scenarios were analyzed. Each scenario is a method for selling renewable energy power, and it is possible to determine the building type and the effect of the sales method by analyzing the results of these scenarios. This method could be used to develop installation guidelines for integration of renewable energy systems into newly built buildings and provide the basis for decision-making by studying retrofitting of existing buildings to enhance energy efficiency.

ACS Style

Minjeong Sim; Dongjun Suh. A heuristic solution and multi-objective optimization model for life-cycle cost analysis of solar PV/GSHP system: A case study of campus residential building in Korea. Sustainable Energy Technologies and Assessments 2021, 47, 101490 .

AMA Style

Minjeong Sim, Dongjun Suh. A heuristic solution and multi-objective optimization model for life-cycle cost analysis of solar PV/GSHP system: A case study of campus residential building in Korea. Sustainable Energy Technologies and Assessments. 2021; 47 ():101490.

Chicago/Turabian Style

Minjeong Sim; Dongjun Suh. 2021. "A heuristic solution and multi-objective optimization model for life-cycle cost analysis of solar PV/GSHP system: A case study of campus residential building in Korea." Sustainable Energy Technologies and Assessments 47, no. : 101490.

Journal article
Published: 03 August 2021 in Sustainability
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Renewable energy systems are an alternative to existing systems to achieve energy savings and carbon dioxide emission reduction. Subsequently, preventing the reckless installation of renewable energy systems and formulating appropriate energy policies, including sales strategies, is critical. Thus, this study aimed to achieve energy reduction through optimal selection of the capacity and lifetime of solar thermal (ST) and ground source heat pump (GSHP) systems that can reduce the thermal energy of buildings including the most widely used photovoltaic (PV) systems. Additionally, this study explored decision-making for optimal PV, ST, and GSHP installation considering economic and environmental factors such as energy sales strategy and electricity price according to energy policies. Therefore, an optimization model based on multi-objective particle swarm optimization was proposed to maximize lifecycle cost and energy savings based on the target energy savings according to PV capacity. Furthermore, the proposed model was verified through a case study on campus buildings in Korea: PV 60 kW and ST 32 m2 GSHP10 kW with a lifetime of 50 years were found to be the optimal combination and capacity. The proposed model guarantees economic optimization, is scalable, and can be used as a decision-making model to install renewable energy systems in buildings worldwide.

ACS Style

Minjeong Sim; Dongjun Suh; Marc-Oliver Otto. Multi-Objective Particle Swarm Optimization-Based Decision Support Model for Integrating Renewable Energy Systems in a Korean Campus Building. Sustainability 2021, 13, 8660 .

AMA Style

Minjeong Sim, Dongjun Suh, Marc-Oliver Otto. Multi-Objective Particle Swarm Optimization-Based Decision Support Model for Integrating Renewable Energy Systems in a Korean Campus Building. Sustainability. 2021; 13 (15):8660.

Chicago/Turabian Style

Minjeong Sim; Dongjun Suh; Marc-Oliver Otto. 2021. "Multi-Objective Particle Swarm Optimization-Based Decision Support Model for Integrating Renewable Energy Systems in a Korean Campus Building." Sustainability 13, no. 15: 8660.

Journal article
Published: 02 July 2021 in Remote Sensing
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Currently, the world is actively responding to climate change problems. There is significant research interest in renewable energy generation, with focused attention on solar photovoltaic (PV) generation. Therefore, this study developed an accurate and precise solar PV generation prediction model for several solar PV power plants in various regions of South Korea to establish stable supply-and-demand power grid systems. To reflect the spatial and temporal characteristics of solar PV generation, data extracted from satellite images and numerical text data were combined and used. Experiments were conducted on solar PV power plants in Incheon, Busan, and Yeongam, and various machine learning algorithms were applied, including the SARIMAX, which is a traditional statistical time-series analysis method. Furthermore, for developing a precise solar PV generation prediction model, the SARIMAX-LSTM model was applied using a stacking ensemble technique that created one prediction model by combining the advantages of several prediction models. Consequently, an advanced multisite hybrid spatio-temporal solar PV generation prediction model with superior performance was proposed using information that could not be learned in the existing single-site solar PV generation prediction model.

ACS Style

Bowoo Kim; Dongjun Suh; Marc-Oliver Otto; Jeung-Soo Huh. A Novel Hybrid Spatio-Temporal Forecasting of Multisite Solar Photovoltaic Generation. Remote Sensing 2021, 13, 2605 .

AMA Style

Bowoo Kim, Dongjun Suh, Marc-Oliver Otto, Jeung-Soo Huh. A Novel Hybrid Spatio-Temporal Forecasting of Multisite Solar Photovoltaic Generation. Remote Sensing. 2021; 13 (13):2605.

Chicago/Turabian Style

Bowoo Kim; Dongjun Suh; Marc-Oliver Otto; Jeung-Soo Huh. 2021. "A Novel Hybrid Spatio-Temporal Forecasting of Multisite Solar Photovoltaic Generation." Remote Sensing 13, no. 13: 2605.

Journal article
Published: 12 November 2020 in Remote Sensing
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Precise and accurate prediction of solar photovoltaic (PV) generation plays a major role in developing plans for the supply and demand of power grid systems. Most previous studies on the prediction of solar PV generation employed only weather data composed of numerical text data. The numerical text weather data can reflect temporal factors, however, they cannot consider the movement features related to the wind direction of the spatial characteristics, which include the amount of both clouds and particulate matter (PM) among other weather features. This study aims developing a hybrid spatio-temporal prediction model by combining general weather data and data extracted from satellite images having spatial characteristics. A model for hourly prediction of solar PV generation is proposed using data collected from a solar PV power plant in Incheon, South Korea. To evaluate the performance of the prediction model, we compared and performed ARIMAX analysis, which is a traditional statistical time-series analysis method, and SVR, ANN, and DNN, which are based on machine learning algorithms. The models that reflect the temporal and spatial characteristics exhibited better performance than those using only the general weather numerical data or the satellite image data.

ACS Style

Bowoo Kim; Dongjun Suh. A Hybrid Spatio-Temporal Prediction Model for Solar Photovoltaic Generation Using Numerical Weather Data and Satellite Images. Remote Sensing 2020, 12, 3706 .

AMA Style

Bowoo Kim, Dongjun Suh. A Hybrid Spatio-Temporal Prediction Model for Solar Photovoltaic Generation Using Numerical Weather Data and Satellite Images. Remote Sensing. 2020; 12 (22):3706.

Chicago/Turabian Style

Bowoo Kim; Dongjun Suh. 2020. "A Hybrid Spatio-Temporal Prediction Model for Solar Photovoltaic Generation Using Numerical Weather Data and Satellite Images." Remote Sensing 12, no. 22: 3706.

Journal article
Published: 11 November 2020 in Energies
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Note: In lieu of an abstract, this is an excerpt from the first page.Article

ACS Style

Junhwa Hwang; Dongjun Suh; Marc-Oliver Otto. Forecasting Electricity Consumption in Commercial Buildings Using a Machine Learning Approach. Energies 2020, 13, 5885 .

AMA Style

Junhwa Hwang, Dongjun Suh, Marc-Oliver Otto. Forecasting Electricity Consumption in Commercial Buildings Using a Machine Learning Approach. Energies. 2020; 13 (22):5885.

Chicago/Turabian Style

Junhwa Hwang; Dongjun Suh; Marc-Oliver Otto. 2020. "Forecasting Electricity Consumption in Commercial Buildings Using a Machine Learning Approach." Energies 13, no. 22: 5885.

Conference paper
Published: 30 June 2020 in Transactions on Petri Nets and Other Models of Concurrency XV
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This study introduces a design of building inventory for risk analysis using open data in Korea. Recently, disasters of various sizes and types are occurring globally. Risk analysis tools are used to estimate the losses due to disasters. However, there is a limitation in the application of disaster statistical data in Korea because these data are based on the country where the tool is produced. To improve the accuracy of loss assessment, it is necessary to utilize data in consideration of each country’s environment. However, the data opened at the national level are distributed among various organizations. Thus, considerable time is required to build infrastructure. Therefore, we collect the open data distributed among various institutions and ensure data compatibility and interoperability through the standardization of the data in various formats. In addition to a disaster analysis system, a design method for a database system that can support various analysis systems through the data is proposed considering scalability.

ACS Style

Su-Seong Chai; Dongjun Suh. A Design of Building Inventory for Risk Analysis Using Open Data. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 5 -9.

AMA Style

Su-Seong Chai, Dongjun Suh. A Design of Building Inventory for Risk Analysis Using Open Data. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():5-9.

Chicago/Turabian Style

Su-Seong Chai; Dongjun Suh. 2020. "A Design of Building Inventory for Risk Analysis Using Open Data." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 5-9.

Journal article
Published: 21 December 2019 in Information
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To cope with natural disasters and their impact, various types of risk assessment tools have been developed to assess hazards from a scientific point of view as well as the socioeconomic impacts of a hazardous event. Because most of the assessment tools have been developed using local and regional characteristics, there are limitations when applying special cases consisting of various disaster-related datasets in Korea. In this paper, we collected open data scattered among various institutions and guaranteed data interoperability through a standardization process considering various formats. In addition, this study presents a scalable design method and implementation of a database system which can be easily employed in Korean loss estimation due to natural hazards. The proposed database system will be of great help in predicting the disaster scale and degree of damage, in supporting decision-making to minimize damage, and could serve as a data platform of disaster risk reduction and prevention.

ACS Style

Su-Seong Chai; Dongjun Suh. Design and Implementation of a Multi-Disaster Risk Assessment Database System in South Korea. Information 2019, 11, 8 .

AMA Style

Su-Seong Chai, Dongjun Suh. Design and Implementation of a Multi-Disaster Risk Assessment Database System in South Korea. Information. 2019; 11 (1):8.

Chicago/Turabian Style

Su-Seong Chai; Dongjun Suh. 2019. "Design and Implementation of a Multi-Disaster Risk Assessment Database System in South Korea." Information 11, no. 1: 8.

Journal article
Published: 24 August 2018 in Sensors
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A hybrid particle swarm optimization (PSO), able to overcome the large-scale nonlinearity or heavily correlation in the data fusion model of multiple sensing information, is proposed in this paper. In recent smart convergence technology, multiple similar and/or dissimilar sensors are widely used to support precisely sensing information from different perspectives, and these are integrated with data fusion algorithms to get synergistic effects. However, the construction of the data fusion model is not trivial because of difficulties to meet under the restricted conditions of a multi-sensor system such as its limited options for deploying sensors and nonlinear characteristics, or correlation errors of multiple sensors. This paper presents a hybrid PSO to facilitate the construction of robust data fusion model based on neural network while ensuring the balance between exploration and exploitation. The performance of the proposed model was evaluated by benchmarks composed of representative datasets. The well-optimized data fusion model is expected to provide an enhancement in the synergistic accuracy.

ACS Style

Hyunseok Kim; Dongjun Suh. Hybrid Particle Swarm Optimization for Multi-Sensor Data Fusion. Sensors 2018, 18, 2792 .

AMA Style

Hyunseok Kim, Dongjun Suh. Hybrid Particle Swarm Optimization for Multi-Sensor Data Fusion. Sensors. 2018; 18 (9):2792.

Chicago/Turabian Style

Hyunseok Kim; Dongjun Suh. 2018. "Hybrid Particle Swarm Optimization for Multi-Sensor Data Fusion." Sensors 18, no. 9: 2792.

Journal article
Published: 29 October 2014 in Energies
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This research presents an evaluative energy model for estimating the energy efficiency of the design choices of architects and engineers in the early design phase. We analyze the effects of various parameters with different characteristics in various combinations for building energy consumption. With this analysis, we build a database that identifies a set of heuristic rules for energy-efficient building design to facilitate the design of sustainable apartment housing. Perturbation studies are based on a sensitivity analysis used to identify the thermal influence of the input design parameters on various simulation outputs and compare the results to a reference case. Energy sensitivity weight factors are obtained from an extensive sensitivity study using building energy simulations. The results of the energy sensitivity study summarized in a set of heuristic rules for evaluating architectural features are estimated through case studies of Korean apartment buildings. This study offers valuable guidelines for developing energy-efficient residential housing in Korea and will help architects in considering appropriate design schemes and provide a ready reference to generalized test cases for both architects and engineers so that they can zero in on a set of effective design solutions.

ACS Style

Dongjun Suh; Seongju Chang. A Heuristic Rule-Based Passive Design Decision Model for Reducing Heating Energy Consumption of Korean Apartment Buildings. Energies 2014, 7, 6897 -6929.

AMA Style

Dongjun Suh, Seongju Chang. A Heuristic Rule-Based Passive Design Decision Model for Reducing Heating Energy Consumption of Korean Apartment Buildings. Energies. 2014; 7 (11):6897-6929.

Chicago/Turabian Style

Dongjun Suh; Seongju Chang. 2014. "A Heuristic Rule-Based Passive Design Decision Model for Reducing Heating Energy Consumption of Korean Apartment Buildings." Energies 7, no. 11: 6897-6929.

Journal article
Published: 04 June 2013 in Wireless Personal Communications
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Context-awareness is associated with the concept of machines being able to both recognize and react to the surrounding environment, which has accelerated multimedia computing technology to provide user-oriented intelligent services. The goal of this research focuses on the modeling of video quality measurement in seamless video service delivery process considering the mobility patterns of users. Mobility supporting schemes providing seamless multimedia services are classified into host mobility and user mobility. The former refers to a host-level handoff while the latter indicates a user-level handoff. In host-level handoff, the decisive factors affecting the quality of video contents consumption are the total distance between hosts, the distance to resume streaming while the user is in mobility mode as well as the screen size of the end host. The influential parameters affecting the degree of video quality and seamlessness are evaluated by a subjective quality assessment and then a perceived video quality model was developed, accordingly. In addition, the optimal video delivery switching point to enable user mobility based video service is studied through the quality analysis of host mobility services at varying distances among the hosts. Experimental results show that the proposed quality model has high correlation with assessed quality and is useful to enable an adequate seamless mobility for multimedia service delivery.

ACS Style

Dongjun Suh; Jinsul Kim; Seongju Chang. Perceived Quality Measurement Model Supporting Full Session Mobility in Multimedia Service Delivery. Wireless Personal Communications 2013, 73, 233 -242.

AMA Style

Dongjun Suh, Jinsul Kim, Seongju Chang. Perceived Quality Measurement Model Supporting Full Session Mobility in Multimedia Service Delivery. Wireless Personal Communications. 2013; 73 (2):233-242.

Chicago/Turabian Style

Dongjun Suh; Jinsul Kim; Seongju Chang. 2013. "Perceived Quality Measurement Model Supporting Full Session Mobility in Multimedia Service Delivery." Wireless Personal Communications 73, no. 2: 233-242.

Conference paper
Published: 01 June 2013 in 2013 International Conference on Information Science and Applications (ICISA)
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A prototype of smart space consisting of network-enabled and intelligence-equipped building components is proposed in this paper. These smart building blocks could be integrated through a Swarm Intelligence Middleware Platform (SIMP) in which simple rules and local interactions are concurrently performed by taking the inspiration from the self-organized behaviors of social animals, and this would allow the formation of collective behavior for various applications of smart space. This paper shows the process of creating a smart space plus representative user scenarios based on the collaboration of these smart building components coordinated through SIMP.

ACS Style

Hyunseok Kim; Dongjun Suh; Seongteak Jang; Jinsul Kim; Seongju Chang. UbiSpace: Prototypical Smart Space Built upon Swarm Intelligence Middleware Platform. 2013 International Conference on Information Science and Applications (ICISA) 2013, 1 -4.

AMA Style

Hyunseok Kim, Dongjun Suh, Seongteak Jang, Jinsul Kim, Seongju Chang. UbiSpace: Prototypical Smart Space Built upon Swarm Intelligence Middleware Platform. 2013 International Conference on Information Science and Applications (ICISA). 2013; ():1-4.

Chicago/Turabian Style

Hyunseok Kim; Dongjun Suh; Seongteak Jang; Jinsul Kim; Seongju Chang. 2013. "UbiSpace: Prototypical Smart Space Built upon Swarm Intelligence Middleware Platform." 2013 International Conference on Information Science and Applications (ICISA) , no. : 1-4.

Journal article
Published: 13 November 2012 in Energies
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This paper proposes and develops a residential energy and resource consumption estimation model in the context of multi-family residential housing in Korea using a multi-layer perceptron (MLP) neural network. Eight indicators are introduced which affect the energy and water resource usage characteristics of Korean residential complexes. The proposed model precisely estimated the electricity, gas energy and water consumption for each examined residential complex. In terms of validation, the results showed the highest level of agreement with actually collected datasets. The model shows promising prospects in providing necessary estimations, not only for optimally scaling and sizing energy- and water-related infrastructures, but also to promote reliable energy and resource savings through greenhouse gas (GHG) reduction planning in multi-family housing complexes. The model could also be of use in framing guidelines for the better planning of national or regional energy and resource policies and for forming a foundation of decision-making with definite references regarding the facility management of each apartment complex to enhance the energy and resource use efficiency at these locations.

ACS Style

Dongjun Suh; Seongju Chang. An Energy and Water Resource Demand Estimation Model for Multi-Family Housing Complexes in Korea. Energies 2012, 5, 4497 -4516.

AMA Style

Dongjun Suh, Seongju Chang. An Energy and Water Resource Demand Estimation Model for Multi-Family Housing Complexes in Korea. Energies. 2012; 5 (11):4497-4516.

Chicago/Turabian Style

Dongjun Suh; Seongju Chang. 2012. "An Energy and Water Resource Demand Estimation Model for Multi-Family Housing Complexes in Korea." Energies 5, no. 11: 4497-4516.

Conference paper
Published: 01 May 2011 in 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)
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Convergence between construction and Information Technology (IT) can facilitate network-enabled building materials that can be used to manifest a built-in digital ecosystem capable of coping with various environmental changes. It is difficult, however, to mix IT components into a building material. Therefore, this research first proposes a network-enabled smart block equipped with various sensing, cognition and actuation capabilities that would cope with various environmental and user requirement changes in addition to maintaining high durability and easy assembly and reconfiguration. Based on the precedent research on Smart Architectural Surface, the developed blocks can also perceive dynamic environmental status and propagates sensed information to the neighboring blocks. Using ecosystem of such smart blocks, we tried to establish UbiWall system which can satisfy diverse interactive multimedia services such as sensor enabled interactive tiled display wall, multi-modal and multifunctional interaction system and autonomous services either localized or globalized depending on the users' interactions with the smart blocks. Ultimately, the developed system can be evolved onto a digital ecosystem which could accommodate a variety of services by strongly coupling a value chain between smart blocks and the users.

ACS Style

Hyunseok Kim; Seongteak Jang; Dongjun Suh; Seongju Chang. UbiWall as a reconfigurable ecosystem of smart blocks. 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011) 2011, 95 -100.

AMA Style

Hyunseok Kim, Seongteak Jang, Dongjun Suh, Seongju Chang. UbiWall as a reconfigurable ecosystem of smart blocks. 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011). 2011; ():95-100.

Chicago/Turabian Style

Hyunseok Kim; Seongteak Jang; Dongjun Suh; Seongju Chang. 2011. "UbiWall as a reconfigurable ecosystem of smart blocks." 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011) , no. : 95-100.

Conference paper
Published: 01 August 2010 in 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics
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Ubi-floor is designed as an interactive floor system which allows user to interact with a floor based smart environment. Concerning context aware floor system, previous researches typically dealt with simple ideas of using gate pattern recognition supported by piezoelectric sensing devices or personal identification mediated by body weight estimation that cannot fully support position dependent context-awareness not to mention interactive interfaces based on it. This paper describes the design and implementation of an interactive floor system that is capable of dealing with various context aware multimedia applications such as visual displays, floor based games, navigation through geographical maps and recording or playing video memo triggered by the menu selections through foot step tracking interface. In addition, this pilot system is recognized as a highly scalable modular prototype of an innovative digital floor system applicable to diversified ubiquitous environments. Furthermore, the system is likely to provide highly enhanced usability of a smart floor system largely affected by various applications that could be adopted. Our further study will include the integration of this ubi-floor platform with various applications in the domain of ubiquitous computing.

ACS Style

Seongju Chang; Sungil Ham; SeungBum Kim; Dongjun Suh; Hyunseok Kim. Ubi-Floor: Design and Pilot Implementation of an Interactive Floor System. 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics 2010, 2, 290 -293.

AMA Style

Seongju Chang, Sungil Ham, SeungBum Kim, Dongjun Suh, Hyunseok Kim. Ubi-Floor: Design and Pilot Implementation of an Interactive Floor System. 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics. 2010; 2 ():290-293.

Chicago/Turabian Style

Seongju Chang; Sungil Ham; SeungBum Kim; Dongjun Suh; Hyunseok Kim. 2010. "Ubi-Floor: Design and Pilot Implementation of an Interactive Floor System." 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics 2, no. : 290-293.