• 한국정밀공학회지
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• 제32권4호
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• pp.339-344
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• 2015

Machine tools are one of the energy-intensive equipment used in the manufacturing industry. The importance of energy has increased and the machine tools are required to be energy-efficient. The servo systems of the machine tool consume electrical power to rotate a spindle and to feed a tool during machining. Servo system consumes a lot of energy when the machine tool is operated. The energy consumption pattern of each axis needs to be investigated in order to optimize the machining process with regard to energy cost. In this paper, an energy monitoring system is developed considering various measuring points of servo system in order to grasp the energy consumption pattern of each axis.

• 한국CDE학회논문집
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• 제18권6호
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• pp.451-460
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• 2013

This paper presents the necessary elements and data flow in developing a monitoring system of energy usage for apartment houses with a Smart TV. Energy consumption data in each home are collected and analyzed in the HUB station by way of measuring instruments. And the amount of energy usage, such as electricity, gas, hot water, heating, water and other utilities are displayed through the Smart TV application. Energy consumption Database in the HUB station are processed and displayed in the browser of a Smart TV through XML, JAVASCRIPT and Flash. Smart TV users can get the energy consumption status through the energy consumption analysis display of the Smart TV application and improve the energy efficiency by comparing the usage patterns with neighboring houses. And the application display energy usage information, consumption ranking, rates to user as well. Furthermore, usage of last month or year can be compared to help to reduce the energy usage. The proposed system can provide the information about the amount of energy use to be reduced and the warning on the waste of energy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2676-2689
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• 2013

Due to increased consumption of energy in the building environment, the building energy management systems (BEMS) solution has been developed to achieve energy saving and efficiency. However, because of the shortage of building energy management specialists and incompatibility among the energy management systems of different vendors, the BEMS solution can only be applied to limited buildings individually. To solve these problems, we propose a building cluster based remote energy monitoring and management (EMM) system and its functionalities and roles of each sub-system to simultaneously manage the energy problems of several buildings. We also introduce a novel energy demand forecasting algorithm by using past energy consumption data. Extensive performance evaluation study shows that the proposed regression based energy demand forecasting model is well fitted to the actual energy consumption model, and it also outperforms the artificial neural network (ANN) based forecasting model.

• KIEAE Journal
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• 제13권2호
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• pp.39-46
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• 2013

Recently, the field of construction is putting a variety of effort into reducing CO2, since global warming is being accelerated due to climate changes and the increase of greenhouse gas. For reduction of CO2 in the field of construction, it is required to make plans to cut down heating energy of buildings and especially, it is urgently needed to cut down energy of residential buildings in rural area where occupies the majority of consumption of petroleum-based energy sources. Therefore, this research compared and analyzed the actual energy consumption, by evaluating energy performance of a detached house applying passive house design components for reduction of energy. As the result, energy consumption showed remarkable differences, according to the operation of a heat recovery ventilation unit which is one of passive house design components, and building energy consumption displayed remarkable differences, too, depending on the difference of airtightness performance during building energy simulation conducted in process of design. Based on these results, the importance of airtightness performance of passive house was verified. The result of the actual measurement of energy consumption demonstrated that LNG was most economical amongst several heat resources yielded, on the basis of LPG source energy consumption measured within a certain period of time, and it was followed by kerosene. LPG was analyzed to have a low economic efficiency, when used for heating.

• 소프트웨어공학소사이어티 논문지
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• 제26권3호
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• pp.53-62
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• 2013

스마트 디바이스의 보급과 함께 컨텍스트 인지 애플리케이션에 대한 수요가 증가하는 추세이다. 하지만, 센서를 통한 컨텍스트의 수집은 추가적인 배터리 소비가 요구된다. 이것은 제한된 배터리 수명을 가진 모바일 디바이스에서 다수의 컨텍스트 인지 애플리케이션을 구동하는데 큰 제약사항이 된다. 그러므로 에너지 효율적인 컨텍스트 모니터링 기법이 요구된다. 본 논문에서는 안드로이드 디바이스에서 가능한 네 가지 컨텍스트 모니터링 기법을 제시하고, 각 기법 간의 에너지 소모량을 분석하여 적합한 적용 지침을 제안한다. 본 논문에서 제안된 기법을 컨텍스트 모니터링 애플리케이션에 적용하면 컨텍스트 모니터링에 소비되는 에너지 소모량을 효과적으로 감소시킬 수 있다. 제안된 기법을 검증하기 위해 적용하여 사용자 행동 인지 애플리케이션을 개발하여 각 기법에 대한 에너지 소모량을 정량적으로 비교한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.896-899
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• 2016

데이터센터를 안정적이고 효율적으로 운영하기 위해서는 서버관리와 전력관리가 중요하다. 본 논문에서는 데이터센터의 서버관리 인터페이스와 전력관리 모듈을 이용하여 에너지 사용량을 모니터링 및 시각화하고, 서버의 온도와 각 장치의 작동상태, 전원상태와 같은 서버 모니터링 정보를 제공하여 데이터센터의 에너지소비분석에 도움을 주는 웹 기반 애플리케이션에 대한 소개와 구현방법을 제안한다. 이 애플리케이션은 서버관리표준 인터페이스인 IPMI 뿐만 아니라 제조사의 독자적인 서버관리기술을 사용하여 이기종 서버에 대한 통합 모니터링이 가능하며, 모니터링 대상서버 시스템에 별도의 에이전트 설치가 필요하지 않으므로 모니터링에 따라 시스템에 발생할 수 있는 부하가 거의 없고, 실시간으로 에너지 소비량과 모니터링 정보를 제공하기 때문에 데이터센터의 에너지소비패턴분석과 서버관리에 효과적으로 사용할 수 있다.

• 인간식물환경학회지
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• 제22권2호
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• pp.219-229
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• 2019

This study was carried out to verify the accuracy of fitness tracking devices in monitoring heart rate and energy consumption and to contribute to the development of a forest exercise program that can recommend the intensity and amount of forest exercises based on personal health-related data and provide monitoring and feedback on forest exercises. Among several commercially available wearable devices, Fitbit was selected for the research, as it provides Open API and data collected by Fitbit can be utilized by third parties to develop programs. Fitbit provides users with various information collected during forest exercises including exercise time and distance, heart rate, energy consumption, as well as the altitude and slope of forests collected by GPS. However, in order to verify the usability of the heart rate and energy consumption data collected by Fitbit in forest, the accuracy of heart rate and energy consumption were verified by comparing the data collected by Fitbit and reference. In this study, 13 middle-aged women were participated, and it was found that the heart rate measured by Fitbit showed a very low error rate and high correlation with that measured by the reference. The energy consumption measured by Fitbit was not significantly different from that measured in the reference, but the error rate was slightly higher. However, there was high correlation between the results measured by Fibit and the reference, therefore, it can be concluded that Fitbit can be utilized in developing actual forest exercise programs.

• 디지털융복합연구
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• 제14권9호
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• pp.309-315
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• 2016

무선 모바일 네트워크 환경에서 노드 이동성은 에너지 소모를 가중화시킨다. 본 논문에서는 노드 이동성으로 인한 에너지 소모를 줄이고, 클러스터 멤버 노드의 수명 주기를 연장시키기 위하여 클러스터 기반의 노드 관리 알고리즘 (CNMA: Cluster-based Node Management Algorithm)을 제안한다. 제안된 CNMA 알고리즘은 클러스터 내에서 클러스터 헤더 노드와 멤버 노드들의 이동성을 추적하고 이들의 관계를 주기적으로 모니터링함으로써 에너지 잔량을 분석한다. 그리고 노드들의 상태 전이 과정을 분석하여 클러스터링 분할과 병합을 수행한다. 본 연구의 목적은 노드 이동성으로 발생된 에너지 소모를 최소화하기 위한 것이다. 시뮬레이션 결과를 통하여 제안된 알고리즘이 이동성으로 인한 에너지 소모를 효율적으로 제어할 수 있음을 보이며, 에너지 수명 주기가 향상됨을 보인다.

• ETRI Journal
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• 제33권6호
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• pp.857-863
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• 2011

Due to uncertainties in target motion and randomness of deployed sensor nodes, the problem of imbalance of energy consumption arises from sensor scheduling. This paper presents an energy-efficient adaptive sensor scheduling for a target monitoring algorithm in a local monitoring region of wireless sensor networks. Owing to excessive scheduling of an individual node, one node with a high value generated by a decision function is preferentially selected as a tasking node to balance the local energy consumption of a dynamic clustering, and the node with the highest value is chosen as the cluster head. Others with lower ones are in reserve. In addition, an optimization problem is derived to satisfy the problem of sensor scheduling subject to the joint detection probability for tasking sensors. Particles of the target in particle filter algorithm are resampled for a higher tracking accuracy. Simulation results show this algorithm can improve the required tracking accuracy, and nodes are efficiently scheduled. Hence, there is a 41.67% savings in energy consumption.

• 전기전자학회논문지
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• 제13권3호
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• pp.39-46
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• 2009

무선 센서 네트워크는 무선 네트워크 기능이 있는 소형 장치로 구성된다. 실제 현장에서 센서 네트워크의 응용 영역을 증가시키기 위해서는 에너지 소모를 최소화 하는 것이 가장 큰 문제이다. 그러므로 센서 네트워크의 평가를 위해서 정확한 에너지 모델이 필요하다. 본 논문에서는 센서 네트워크의 전력 소모를 분석한다. 전력 소모 모델을 개발하기 위해서 TelosB를 기반으로 하는 상용 제품인 Kmote의 전력 특성을 측정한다. 제안한 모델로부터 PIR 센서를 이용하는 인체 감지 응용에서 건전지를 사용하는 센서 노드는 약 6.9개월의 수명을 예상할 수 있다. 이러한 결과를 바탕으로 독거노인 모니터링 시스템에 적용 가능함을 확인하였다.