• Journal of Korea Multimedia Society
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• v.17 no.6
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• pp.687-696
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• 2014

An integrated ship area network has functionality of remote control and autonomous management of various sensors and instruments embedded or boarded in a ship. For such environment, an wireless bridge is essential to transmit control and/or managing information to sensors or instruments from a central integrated ship area network station. In this paper, one of reliable schemes of WiMedia based wireless bridge using relay cooperative transmission using WiMedia distributed MAC protocol is proposed to increase a communication reliability between cluster headers, irrespective of channel variation. Simulation results show that the proposed wireless bridge using relay cooperative transmission scheme increases communication reliability.

• Journal of electromagnetic engineering and science
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• v.15 no.2
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• pp.104-110
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• 2015

As civil infrastructures continue to deteriorate, the demand for structural health monitoring (SHM) has increased. Despite its outstanding capability for damage identification, many conventional SHM techniques are restricted to huge structures because of their wired system for data and power transmission. Although wireless data transmission using radio-frequency techniques has emerged vis-$\grave{a}$-vis wireless sensors in SHM, the power supply issue is still unsolved. Normal batteries cannot support civil infrastructure for no longer than a few decades. In this study, we develop a magnetic resonance-based wireless power transmission system, and its performance is validated in three different mediums: air, unreinforced concrete, and reinforced concrete. The effect of concrete and steel rebars is analyzed.

• Smart Structures and Systems
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• v.30 no.6
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• pp.583-599
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• 2022

In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.307-312
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• 2007

Wireless Sensor Network(WSN) is considered as a core technology necessary for Ubiquitous computing, with its numerous possible applications in many practical areas, is being researched and studied actively by many around the world. WSN utilizes wireless sensors spatially placed to gather information regarding temperature, light condition, motion and change in speed of the objects within their surrounding environment. This paper implements an environmental information monitoring and indexing system based on spatial indexing technique by constructing a WSN system. This Multi-Query Indexing Technique coupled with wireless sensors provides an output based on the pre-defined built-in data index and new input from the sensors. If environment data is occured, system have to perform a proper action after collecting and analyzing this data. This is the purpose of implementing environment data monitoring system. We constructed environmental application using TinyOS and built tested with MICAz sensor bords. We designed and implemented a monitoring system which detects and multi-indexing process environmental data from distributed sensors.

• Smart Structures and Systems
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• v.6 no.3
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.125-129
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• 2023

Age of Information (AoI) has been introduced in wireless networked control systems (WNCSs) to guarantee timely status updates. In addition, as the edge computing (EC) architecture has been deployed in NCS, EC close to sensors can be exploited to collect status updates from sensors and provide control decisions to actuators. However, when lots of sensors simultaneously deliver status updates, EC can be overloaded, which cannot satisfy the AoI requirement. To mitigate this problem, this paper uses actuators with computing capability that can directly receive the status updates from sensors and determine the control decision without the help of EC. To analyze the AoI of the actuation update via EC or directly using actuators, this paper developed an analytic model based on timing diagrams. Extensive simulation results are included to verify the analytic model and to show the AoI with various settings.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.264-266
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• 2005

Recently, on-line diagnosis methods through wired and wireless networks are widely adopted in the diagnosis of industrial Electric Facilities, such as generators, transformers and motors. Also smart sensors which includes sensors, signal conditioning circuits and micro-controller in one board are widely studied in the field of condition monitoring. This paper suggests an self-powered system suitable for condition-monitoring smart sensors, which uses parasitic vibrations of the facilities as energy source. First, vibration-driven noise patterns of the electric facilities are presented. And then, an electromagnetic generator which uses mechanical mass-spring vibration resonance are suggested and designed. Finally energy consumption of the presented smart sensor, which consists of MEMS vibration sensors, signal conditioning circuits, a low-power consumption micro-controller, and a ZIGBEE wireless tranceiver, are presented. The usefulness and limits of the presented electromagnetic generators in the field of electric facility monitoring are also suggested.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.164-172
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• 2013

We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.846-856
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• 2016

Wireless sensor networks (WSNs) are widely applied in monitoring and control of environment parameters. It is sometimes necessary to disseminate data through wireless links after they are deployed in order to adjust configuration parameters of sensors or distribute management commands and queries to sensors. Several approaches have been proposed recently for data dissemination in WSNs. However, none of these approaches achieves both high efficiency and low complexity simultaneously. To address this problem, cluster-tree based network architecture, which divides a WSN into hierarchies and clusters is proposed. Upon this architecture, data is delivered from base station to all sensors in clusters hierarchy by hierarchy. In each cluster, father broadcasts data to all his children with instantly decodable network coding (IDNC), and a novel scheme targeting to maximize total transmission gain (MTTG) is proposed. This scheme employs a new packet scheduling algorithm to select IDNC packets, which uses weight status feedback matrix (WSFM) directly. Analysis and simulation results indicate that the transmission efficiency approximate to the best existing approach maximum weight clique, but with much lower computational overhead. Hence, the energy efficiency achieves both in data transmission and processing.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.111-117
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• 2019

We investigated the variations in the magnetic-field distribution and power transmission efficiency, resulting from changes in the relative positions of the transmitting and receiving coils, for electromagnetic-induction-type wireless power transmission using an elliptical receive coil. Results of simulations using a high-frequency structure simulator were compared to actual measurement results. The simulations showed that the transmission efficiency could be maintained relatively stable even if the alignment between the transmitting and receiving coils was changed to some extent. When the centre of the receiving coil was perfectly aligned with the centre of the transmitting coil, the transmission efficiency was the maximum; however, the degree of decrease in the transmission efficiency was small even if the centre of the receiving coil moved by ± 10mm from the centre of the transmitting coil. Therefore, it is expected that the performance of the wireless power transmission system will not be degraded significantly even if perfect alignment is not maintained. The results suggested a standardized application method of wireless transmission in the utilization of wireless power for implantable sensors.