• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.357-360
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• 2008

Vital sign monitoring system using IEEE 502.IS.4 based wireless sensor network(WSN) is designed and developed on mobile environment and sensor node platform. WSN and CDMA are integrated to create a wide coverage to support various environments like inside and outside. We developed query processor to use selective any devices(ECG, Blood pressure and sugar module) and control of the self-organizing network of sensor nodes in a wireless sensor network. Vital sign from wireless medical any devices are analysed in cell phone first for real time signal analyses and the abnormal vital signs are sent and save to hospital server for detail signal processing. wireless signal traffic in wireless sensor network environment or data communication inside the cell phone is reduced.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.405-406
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• 2012

A sensor network is composed of a large number of sensor nodes which have sensing, computation and wireless communication capabilities. The sensor node sends such collected data, usually via radio transmitter, to a command center (sink) either directly or through a data concentration center (a gateway). These sensor networks can be used for various application areas such as health, military, home network, managing inventory, monitoring disaster areas and so on. Moreover, owing to the rapid growth of mobile technology, high-performance smartphones are widespread and in increasing cases are utilized as a terminal device. In this paper, we propose a home management system using smartphone and sensor networks.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.136-146
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• 2006

In Wireless Sensor Network(WSN) a sensor node transfers sensing data to the base-node through multi-hop because of the limited transmission range. Also because of the limited energy of the sensor node, the sensor nodes are required to consume their energy evenly to prolong the lifetime of the network. LMPR is a routing protocol for WSN, LMPR configures the network autonomously based on level which is the depth from the base-node, and distributes the transmission and computation load of the network to each sensor node. This paper implements LMPR on TinyOS and experiments on the performance of LMPR in WSN. As the result, the average of the received rate of LMPR is 91.39% and LMPR distributes the load of the transmission and computation about 4.6 times compare to the shortest cost routing protocol. We expect LMPR evenly distributes the transmission and computation load of the network to each node, and the lifetime of the network will be longer than it used to be.

• Convergence Security Journal
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• v.20 no.3
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• pp.13-20
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• 2020

Recently, the need of researches and developments about WSN(Wireless Sensor Network) technologies, which can be applied to services that require continuous monitoring or services to specific areas where accesses are limited, has gradually increased due to their expansion of application areas and the improvement of the efficiency. Especially, in the defense field, researches on the latest IT technologies including sensor network areas are actively conducted as an alternative to avoid the risk factors that can be occurred when personnel are put in, such as boundary and surveillance reconnaissance and to utilize personnel efficiently. In this paper, we analyze the conditions for increasing the life span of sensing nodes that make up sensor network by applying clustering and location-based techniques and derived the factors for extending the life span of them. The derived factors include CH(Cluster Head) election scheme and optimal path selection from CH to BS(Base Station). We proposed final scheme using derived factors and verified it through simulation experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.163-168
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• 2008

Navigation system based on indoor location estimation is one of the core technologies in mobile robot systems. Wireless sensor network has great potential in the indoor location estimation due to its characteristics such as low power consumption, low cost, and simplicity. In this paper we present an algorithm to estimate the indoor location of mobile robot based on wireless sensor network and fuzzy modeling. ZigBee-based sensor network usually uses RSSI(Received Signal Strength Indication) values to measure the distance between two sensor nodes, which are affected by signal distortion, reflection, channel fading, and path loss. Therefore we need a proper correction method to obtain accurate distance information with RSSI. We develop the fuzzy distance models based on RSSI values and an efficient algorithm to estimate the robot location which applies to the navigation algorithm incorporating the time-varying data of environmental conditions which are received from the wireless sensor network.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.284-294
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• 2008

In this paper, we describe an implementation of small mobile robot that can be used at research and application of mobile sensor networking. This robot that will constitute the sensor network, as a platform of multi-robot system for each to be used as sensor node, has to satisfy restrictions in many aspects in order to perform sensing, communication protocol, and application algorithms. First, the platform must be designed with a robust structure and low power consumption since its maintenance after deployment is difficult. Second, it must have flexibility and modularity to be used effectively in any structure so that it can be used in various applications. Third, it must support the technique of wireless network for ubiquitous computing environment. At last, to let many nodes be scattered, it must be cost-effective and small. Considering the above restrictions of the mobile platform for sensor network, we designed and implemented robots control the current of actuator by using additional circuit for power efficiency. And we chose MSP430 as MCU, CC2420 as RF transceiver, and etc, that have the strength in the aspect of power. For flexibility and modularity, the platform has expansion ports. The results of experiments are described to show that this robot can act as sensor node by RF communication process with Zigbee standard protocol, execute the navigation process with simple obstacle avoidance and the moving action with RSSI(Received Signal Strength Indicator), operate at low-power, and be made with approx. $100.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7B
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• pp.649-658
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• 2009

Due to limited size and limited battery lifetime of sensor node, one has to address the power saving issue in wireless sensor network. The existing power saving algorithm based on data reuse was proposed for the cluster structured wireless sensor network. We state the problem of existing power saving algorithm and propose new power saving algorithm for tree structured wireless sensor network. The proposed algorithm reduces power consumption by buffering the sensed data at the selected relay node for its data lifetime. The optimum buffering node is selected so that the power saving gain is maximized and at the same time, power consumption among sensor nodes are equally distributed in the network. With computer simulations, it is shown that the proposed algorithm outperforms the conventional algorithm in terms of power saving gain.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1B
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• pp.48-57
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• 2008

Wireless sensor networks are composed of a lot of sensor nodes and they are used to monitor environments. Since many studies on wireless sensor networks have considered a stationary sink node, they cannot provide fully ubiquitous applications based on a mobile sink node. In those applications, routing paths for a mobile sink node should be updated while a sink node moves in order to deliver sensor data without data loss. In this paper, we propose a method to continuously update routing paths for a mobile sink node which can be extended on hierarchical multi-hop routing protocols in wireless sensor networks. The efficiency of the proposed scheme has been validated through comparing existing method using a location based routing protocol by extensive computer simulation.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1071-1075
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• 2010

Because a sensor node in wireless sensor networks(WSNs) has limited resources, such as battery capacity and memory, data aggregation techniques have been studied to manage the limited resources efficiently. Because sensor network uses wireless communication, a data can be disclosed by attacker. Thus, the study on data protection schemes for data aggregation is essential in WSNs. But the existing data aggregation methods require both a large number of computation and communication, in case of network construction and data aggregation processing. To solve the problem, we propose a data protection scheme based on Hilbert-curve for data aggregation. Our scheme can minimizes communications among neighboring sensor nodes by using tree-based routing. Moreover, it can protect the data from attacker by doing encryption through a Hilbert-curve technique based on a private seed, Finally, we show that our scheme outperforms the existing methods in terms of message transmission and average sensor node lifetime.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.886-889
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• 2010

Power consumption measurement in sensor network is difficult to proceed by survey in real field. Thus, through simulation, the power consumption is estimated and replacement time of nodes are decided. A simulation tool simulates various facts such as power consumption, packet transmission traffic, network topology and etc. In this paper, it suggests sensor node power model to simulate power consumption which has large importance among simulation facts in sensor network. This model omits calculating expressions that the data originally surveyed can substitute with, according to power consumption property of each functions in sensor node in order to minimize calculations in simulation. In this case accuracy of power consumption estimation will be reduced, but can simulate it faster due to reduced calculation. Suggested model is fitted to analyze power consumption difference between two or more sensor network algorithms with rapid simulation speed rather than accurate simulation.