• International journal of advanced smart convergence
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• v.5 no.1
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• pp.1-7
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• 2016

Recently, introduced a cloud computing technology to the IT industry, smart phones, it has become possible connection between mobility terminal such as a tablet PC. For dissemination and popularization of movable wireless terminal, the same operation have focused on a viable mobile cloud in various terminal. Also, it evolved Wireless Sensor Network(WSN) technology, utilizing a Body Sensor Network(BSN), which research is underway to build large Ubiquitous Sensor Network(USN). BSN is based on large-scale sensor networks, it integrates the state information of the patient's body, it has been the need to build a managed system. Also, by transferring the acquired sensor information to HIS(Hospital Information System), there is a need to frequently monitor the condition of the patient. Therefore, In this paper, possible sensor information exchange between terminals in a mobile cloud environment, by integrating the data obtained by the body sensor HIS and interoperable data DBaaS (DataBase as a Service) it will provide a base of mBodyCloud System. Therefore, to provide an integrated protocol to include the sensor data to a standard HL7(Health Level7) medical information data.

• KIEAE Journal
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• v.14 no.6
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• pp.23-29
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• 2014

It is essential to investigate the structure and the main characteristics of BSN (Bio-Sensor Network) platform in built smart healthcare environment while designing healthy housing facilities. For this study, WSN (Wireless Sensor Network) data transmission technologies have been employed with medical sensors, and optimal medical devices would provide various Web 2.0 services by connecting to the WiBro network. The BSN platform normally recognizes in surroundings of WBAN (Wireless Body Area Network) or WPAN (Wireless Personal Area Network), and it is possible to manage sensor nodes by utilizing SOAP (Simple Object Access Protocol) and REST (REpresentational State Transfer). In addition, the feature of SNMP (Simple Network Management Protocol) for mobile gateway is also included for being adapted to huge network structure. Finally, BSN platform will play a role as important clues for developing personal WSN service models for smart healthy housing properties.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.82-88
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• 2017

The data generated by the BSN sensor attached to the human body is mostly mobile. Accordingly, in a mobile cloud environment that processes BSN data, the service should not be fixed in a specific area but be able to support it according to the move. The mobile device must be able to process, filter and transmit the collected BSN data. The cloud server must be able to collect the data processed by the mobile device and provide it as a service. And the transfer of data requires standardized transfer between each device. In this paper, we propose a data delivery method through standard schema when mobile device processes data and provides service in cloud system and a data processing method according to the movement of the mobile device.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• Smart Structures and Systems
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• v.21 no.2
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• pp.225-234
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• 2018

E-Health allows you to supersede the central patient wireless healthcare system. Wireless Body Sensor Network (WBSN) is the first phase of the e-Health system. In this paper, we aim to understand e-Health architecture and configuration, and attempt to minimize energy consumption and latency in transmission routing protocols during restrictive latency in data delivery of WBSN phase. The goal is to concentrate on polling protocol to improve and optimize the routing time interval and schedule communication to reduce energy utilization. In this research, two types of network models routing protocols are proposed - elemental and clustering. The elemental model improves efficiency by using a polling protocol, and the clustering model is the extension of the elemental model that Destruct Supervised Decision Tree (DSDT) algorithm has been proposed to solve the time interval conflict transmission. The simulation study verifies that the proposed models deliver better performance than the existing BSN protocol for WBSN.

• Journal of the Korean Solar Energy Society
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• v.28 no.6
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• pp.58-63
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• 2008

It is essential to investigate the structure and the main characteristic of Home USN (Ubiquitous Sensor Network) technologies in built ubiquitous environment while designing bio-sensors. For this study, Thermistor elements and Thermopile black body have been selected to implement ubiquitous technologies for bio-sensors and wireless network such as WiBro has been used to transfer sensing data to the BSN (Bio-Sensor Network) gateway. It is certain that efficiency of ubiquitous space design is improved if main components of each specific sensor network are analyzed precisely in digital way and corresponding communication modules are prepared accordingly. Ubiquitous technology, in conclusion, has to be applied not only with systematical mechanism or electronic setting but in human-centered atmosphere as well, keeping with deep consideration for bio-housing service factors in eco-friendly surrounding.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.8-15
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• 2016

Studies have been made for the wireless sensor network protocols by a number of researchers to date. In particular, the studies as to the hierarchical protocol LEACH algorithm was concentrated. Various studies have been derived for the performance of the protocol is based on the LEACH protocol have been made. Improved algorithms have been proposed continuously. On the other hand, The performance comparison and evaluation of the improved algorithm is insufficient. Therefore, we compared the performance for the ML-LEACH (Multi Hop-Layered) and DL-LEACH (Dual Hop-Layered) been derived mainly LEACH. scalability, energy consumption, CH elected, network lifetime were selected as a Performance evaluation items.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.66-72
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• 2016

In this paper, we proposed the clustering algorithm using fuzzy inference system for improving adaptability the cluster head selection of TEEN. The stochastic selection method cannot guarantee available of cluster head. Furthermore, because the formation of clusters is not optimized, the network lifetime is impeded. To improve this problem, we propose the algorithm that gathers attributes of sensor node to evaluate probability to be cluster head.

• Information and Communications Magazine
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• v.25 no.2
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• pp.18-25
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• 2008

지능형 센서, 마이크로전자공학 및 집적회로, SoC (system-on-chip) 설계와 저전력 무선통신의 급속한 발달로 소형 지능형 센서노드의 개발을 촉진하여 왔다. 이러한 센서 노드는 인체센서네트워크(Body Sensor Network;BSN)의 개발에 초석이 되며, 향후 이 분야의 급속한 발전을 기대하게 된다. 초 저전력 RF 기술의 발전은 침투식 및 비침투식 장치들이 원격 단말과 데이터 전송을가능케 하며, 환자를 장기간 모니터링하여 의료 전문가에게 실시간으로 피드백 함으로써 건강관리 시스템의 일대 혁신을 일으키고 있다. 본 기고에서는 이식형 의료 장치들간의 무선통신 방법과 BSN 분야에서의 최근 기술적 발전동향에 주안점을 두어, 인체 내장형 및 인체 부착형 통신 네트워크 구조를 파악한 후, 이들 분야에서 미해결 쟁점과 난제에 관하여 분석하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.131-140
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• 2009

A key challenge for Wireless Body Area Network (WBAN) is to maximize the network lifetime with power-efficient and flexible duty cycling techniques on energy-constraint sensor nodes. In this paper, we propose a novel power-efficient MAC protocol for WBAN that accommodates normal, emergency, and on-demand traffic in a reliable manner. This protocol supports two wakeup mechanisms, a traffic-based wakeup mechanism, which accommodates normal traffic by exploiting the node's traffic patterns, and a wakeup radio mechanism, which accommodates emergency and on-demand traffic by using a wakeup radio. It can be seen that the proposed protocol not only improves the lifetime of WBAN but also provides a reliable method to handle sporadic events. Simulation results show that the proposed protocol outperforms WiseMAC in terms of low-power consumption and delay.