• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.428-431
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• 2009

기존의 첨단주택은 IT 차원에서 접근되어 에너지 절약을 위한 기술은 시도하지 않았고 에너지 환경관리 기술이 미흡하였다. 본 논문에서는 실제 사용자 생활 패턴을 파악하여 에너지 소모를 얼마나 줄일 수 있는지 테스트 하였다. 복도, 출입구 그리고 현재 근무 중인 테이블에 조도 센서와 인체 감지 센서를 설치하였는데 조도 센서와 인체감지 센서는 하나의 그룹을 이루며 생활패턴을 파악하고 조도 값에 따라 실내등을 소등할 수 있도록 한다. 모든 센서 노드는 스타 토폴로지(one-hop) 형태로 연결되며 데이터는 USN 브릿지에 있는 베이스노드로 수집되고 이더넷을 통해 서버로 전달하면 DB에 저장된다. 그러므로 실시간으로 실내 환경 데이터를 수집하여 실내 환경 통합 감시 및 모니터링이 가능하고 에너지 소모를 줄일 수 있다.

• Convergence Security Journal
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• v.22 no.1
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• pp.55-60
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• 2022

This study is to analyze trends and relational structures in the energy sector related to renewable energy. For this reason, in this study, we focused on big data including SNS data. SNS utilizes the Instagram platform to collect renewable energy hash tags and use them as a word embedding method for big data analysis and social network analysis, and based on the results derived from this research, it will be used for the development of the renewable energy industry. It is expected that it can be utilized.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.933-937
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• 2009

This paper proposes a dynamic timeout scheduling for energy efficient and accurate aggregation by analyzing the single hop delay in wireless sensor networks based on IEEE 802.15.4. The proposed scheme dynamically configures the timeout value depending on both the number of nodes sharing a channel and the type of wireless media, with considering the results of delay analysis of the single hop delay. The timeout of proposed scheme is much smaller than the maximum single hop delay which is used as the timeout of traditional data aggregation schemes. Therefore the proposed scheme considerably reduces the energy consumption of idle monitoring for waiting messages. Also, the proposed scheme maintains the data accuracy by guaranteeing the reception ratio required by the sensor network applications. Extensive simulation has revealed that proposed scheme enhances energy consumption by 30% with maintaining data accuracy, as compared with the TAG data aggregation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.79-85
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• 2009

A sink node and its neighbor nodes spend more energy than other nodes since a stationary sink node collects data from wireless sensor networks(WSNs). For larger WSNs, the unbalanced energy of nodes causes the operation of WSNs to stop rapidly. This paper proposes a data gathering method by adapting the mobile sink to prolong the life time of large WSNs. After partitioning a network into several clusters, a mobile sink visits each cluster and collects data from it. An efficient algorithm is proposed to improve the energy efficiency by delivering the message from the mobile sink to the cluster head as well as to reduce the data gathering delay, which is the disadvantage of the mobile sink. Also, The algorithm is analyzed for the energy consumption and the data gathering delay. The validity of the ananlysis result is confirmed by the simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.514-517
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• 2017

In solar photovoltaic systems, power generation is greatly affected by the weather conditions, so it is essential to predict solar energy for stable load operation. Therefore, data on weather conditions are needed as inputs to machine learning algorithms for solar energy prediction. In this paper, we use 15 kinds of weather data such as the precipitation accumulated during the 3 hours of the surface, upward and downward longwave radiation average, upward and downward shortwave radiation average, the temperature during the past 3 hours at 2 m above from the ground and temperature from the ground surface as input data to the algorithm. We analyzed the statistical characteristics and correlations of weather data and extracted the downward and upward shortwave radiation averages as a major elements of a feature vector with high correlation of 70% or more with solar energy.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.271-276
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• 2014

The life-time and performance of a wireless sensor network is closely related to energy-efficiency of sensor nodes. In this paper, to increase energy-efficiency, each sensor node operates in one of three operational modes which are normal, power-saving, and inactive. In normal mode sensor nodes sense and transmit data with normal period, whereas sensor nodes in power-saving mode have three-times longer period. In inactive mode, sensor nodes do not sense and transmit any data, which makes the energy consumption to be minimized. Plus, the proposed algorithm can avoid unnecessary energy consumption by preventing transmitting duplicate sensed data. We implemented and simulated the proposed algorithm using Tiny OS based ZigbeX platfom and NS-2, respectively. Performance evaluation results show that the proposed algorithm can prolong sensor networks' lifespan by efficiently reducing energy consumption and its standard deviation of all sensor nodes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.35-40
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• 2011

In this paper, we compare and analyze data aggregation methods based on event area in wireless sensor networks. Data aggregation methods consist of two methods: the direct transmission method and the aggregation node method. The direct aggregation method has some problems that are data redundancy and increasing network traffic as all nodes transmit own data to neighbor nodes regardless of same data. On the other hand the aggregation node method which aggregate neighbor's data can prevent the data redundancy and reduce the data. This method is based on location of nodes. This means that the aggregation node can be selected the nearest node from a sink or the centered node of event area. So, we describe the benefits of data aggregation methods that make up for the weak points of direct data dissemination of sensor nodes. We measure energy consumption of the existing ways on data aggregation selection by increasing event area. To achieve this, we calculated the distance between an event node and the aggregation node and the distance between the aggregation node and a sink node. And we defined the equations for distance. Using these equations with energy model for sensor networks, we could find the energy consumption of each method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.765-767
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• 2016

Building Energy commissioning is a process in which verifying and making the document during entire lifetime including planning, design, construction, test run of equipment, and maintenance to minimize the operational problems of building energy efficiency. The general commissioning is replacing the equipment or reconstructing the skin to achieve the performance for the design. This process is expensive and has the disadvantage of taking a long payback period by one operation. In this paper, we studied the monitoring-based commissioning (MBCx) to increase the energy efficiency of buildings through analyzing energy use data. MBCx is modeling a building energy, comparing the real energy use with it, detecting the cause of falling the efficiency, and running the optimal operation regularly.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.219-220
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• 2022

최근 항로표지는 기본 업무를 위한 등명기의 구동과 해상 환경 정보 수집 및 데이터 전송 기능들의 확장을 통해 다양한 임무를 수행하기 위한 스마트 장비로써 진화하고 있다. 그래서 항로표지를 운영하기 위한 전력량의 요구가 높아지고 있고, 동작 구동 시간을 확보하기 위해 다양한 해상 에너지원을 통해 발전하는 시스템을 고려하고 있다. 하지만 전원 공급 및 교체가 쉽지 않은 해상 환경에서 태양광, 파력 등의 한정적인 에너지원의 활용은 지속적인 스마트 항로표지의 동작에 한계가 존재한다. 그래서 해양 환경 상황에서도 한정된 에너지원을 활용하여 에너지 수집을 하고 이를 활용하여 다양한 환경 센싱, 정보 연산, 데이터 처리, 무선 정보 전송 등의 시스템에 안정적으로 전력을 공급할 수 있는 방안이 필요하다. 본 논문에서는 해상 환경 적응 에너지 수집, 백업 전력운영, 항로표지 출력 에너지 재사용, 분산 전력관리 등을 포함한 차세대 스마트 항로표지 전원 시스템 구성 방안에 대해서 제안한다.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.33-44
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• 2005

Recently, the weather has been influenced by the environmental pollution and the oil price has been risen because of the lack of resources. So, the weather and energy are influencing on not only enterprises or nations, but also individual daily life and economic activities very much. Because of these reasons, there are so many researches about management of solar radiation needed to develope solar energy as alternative energy. And many researchers are also interested in identifying the area according to changing characteristics of climate data. However, the researches have not developed how to apply the cluster analysis, retrieval and analytical results according to the characteristics of the area through data mining. In this paper, we design a data model of the data for storing and managing the climate data tested in twenty cities in the domestic area. And we provide the information according to the characteristics of the area after clustering the domestic climate data, using k-means clustering algorithm. And we suggest the way how to apply the department store and amusement park as an applied weather marketing. The proposed system is useful for constructing the database about the weather marketing and for providing the elements and analysis information.