• Smart Structures and Systems
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• v.6 no.5_6
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• pp.749-765
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• 2010

There are on-going efforts to utilize guided waves for structural damage detection. Active sensing devices such as lead zirconate titanate (PZT) have been widely used for guided wave generation and sensing. In addition, there has been increasing interest in adopting wireless sensing to structural health monitoring (SHM) applications. One of major challenges in wireless SHM is to secure power necessary to operate the wireless sensors. However, because active sensing devices demand relatively high electric power compared to conventional passive sensors such as accelerometers and strain gauges, existing battery technologies may not be suitable for long-term operation of the active sensing devices. To tackle this problem, a new wireless power transmission paradigm has been developed in this study. The proposed technique wirelessly transmits power necessary for PZT-based guided wave generation using laser and optoelectronic devices. First, a desired waveform is generated and the intensity of the laser source is modulated accordingly using an electro-optic modulator (EOM). Next, the modulated laser is wirelessly transmitted to a photodiode connected to a PZT. Then, the photodiode converts the transmitted light into an electric signal and excites the PZT to generate guided waves on the structure where the PZT is attached to. Finally, the corresponding response from the sensing PZT is measured. The feasibility of the proposed method for wireless guided wave generation has been experimentally demonstrated.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.2
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• pp.79-86
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• 2016

In wireless sensor networks, increasing the sensing rate of each node to improve the data accuracy usually incurs a decrease of network lifetime. In this study, an energy-adaptive data compression scheme is proposed to efficiently control the sensing rate in an energy-harvesting wireless sensor network (WSN). In the proposed scheme, by utilizing the surplus energy effectively for the data compression, each node can increase the sensing rate without any rise of blackout time. Simulation result verifies that the proposed scheme gathers more amount of sensory data per unit time with lower number of blackout nodes than the other compression schemes for WSN.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.162-171
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• 2014

Spectrum sensing is a key technical challenge for cognitive radio (CR). It is well known that multicycle cyclostationarity (MC) detection is a powerful method for spectrum sensing. However, a conventional MC detector is difficult to implement because of its high computational complexity. This paper considers reducing computational complexity by simplifying the test statistic of a conventional MC detector. On the basis of this simplification process, an improved MC detector is proposed. Compared with the conventional detector, the proposed detector has low-computational complexity and high-accuracy sensing performance. Subsequently, the sensing performance is further investigated for the cases of Rayleigh, Nakagami-m, Rician, and Rayleigh fading and lognormal shadowing channels. Furthermore, square-law combining (SLC) is introduced to improve the detection capability in fading and shadowing environments. The corresponding closed-form expressions of average detection probability are derived for each case by the moment generation function (MGF) and contour integral approaches. Finally, illustrative and analytical results show the efficiency and reliability of the proposed detector and the improvement in sensing performance by SLC in multipath fading and lognormal shadowing environments.

• Smart Structures and Systems
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• v.18 no.5
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• pp.885-909
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• 2016

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.

• Smart Structures and Systems
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• v.8 no.1
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• pp.139-155
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• 2011

Polymeric thin-film assemblies whose bulk electrical conductivity and mechanical performance have been enhanced by single-walled carbon nanotubes are proposed for measuring strain and corrosion activity in metallic structural systems. Similar to the dermatological system found in animals, the proposed self-sensing thin-film assembly supports spatial strain and pH sensing via localized changes in electrical conductivity. Specifically, electrical impedance tomography (EIT) is used to create detailed mappings of film conductivity over its complete surface area using electrical measurements taken at the film boundary. While EIT is a powerful means of mapping the sensing skin's spatial response, it requires a data acquisition system capable of taking electrical impedance measurements on a large number of electrodes. A low-cost wireless impedance analyzer is proposed to fully automate EIT data acquisition. The key attribute of the device is a flexible sinusoidal waveform generator capable of generating regulated current signals with frequencies from near-DC to 20 MHz. Furthermore, a multiplexed sensing interface offers 32 addressable channels from which voltage measurements can be made. A wireless interface is included to eliminate the cumbersome wiring often required for data acquisition in a structure. The functionality of the wireless impedance analyzer is illustrated on an experimental setup with the system used for automated acquisition of electrical impedance measurements taken on the boundary of a bio-inspired sensing skin recently proposed for structural health monitoring.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.3
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• pp.285-292
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• 2015

This paper presents a wireless ground reaction force (GRF) sensing system for ambulatory GRF recording. The system is largely divided into three parts: force sensing modules based on optical sensor, outsole type frame, and embedded system for wireless communication. The force sensing module has advantages of the low height, robustness to the moment interference, and stable response in long term use. In simulation study, the strain and stress properties were examined to satisfy the requirements of the GRF sensing system. Four sensing modules were mounted on the toe, ball, and heel of foot shaped frame, respectively. The GRF signals were extracted using Micrpcontroller unit and transferred to the smart phone via Bluetooth communication. We measured the GRF during the normal walking for the validation of the continuous recording capability. The recorded GRF was comparable to the off the shelf stationary force plate.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.2
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• pp.95-101
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• 2012

In order to supply emotion service depending on user's emotional change in a mobile environment, various researches have been carried. This paper discusses a protocol for wireless charging and an embedded platform of the mobile emotional sensing device which supports that. Wireless charging process relieves user's vexatious task to charge the emotional sensing device. To support wireless charging, there are one basestation and several mobile devices. Basestation coordinates and controls the devices over wireless communication, as well as supplies energy. For 1:N communication we defines the network whose superframe is classified into four categories: a network join superframe, a charging request superframe, a charging superframe and an inactive superframe. Physical layer provides how to supply energy to the devices and communicate physically. Mobile device is equipped with energy charged circuits, which correspond with the defined energy supplying method, as well as bidirectional communication circuits. Mobile device monitors and analyzes its own battery status, and is able to send a request packet to basestation. Therefore, it can be charged before its battery is exhausted without user's perception.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.113-119
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• 2010

Wireless ad hoc network composed of low power devices has been operated in ISM bands. However, with the growing proliferation of wireless services, these bands are increasingly getting congested. In order to relieve the spectrum scarcity and inefficient spectrum utilization, ad ho cognitive radio was proposed. In this paper we propose the efficient spectrum sensing method to reduce power consumption and detect white space in ad hoc cognitive radio system. The wireless channel between a licensed user and CR systems is modeled as Gaussian channel, the distance between a licensed user and CR systems is assumed differently. Also, the wireless channel among CR systems is assumed as the perfect channel and the distance among CR systems is assumed close distance. CR systems sense the spectrum of the licensed user by using a energy detection method. From the simulation results, spectrum sensing performance of combining sensing result of CR systems with high received energy shows higher than combining sensing result of all CR systems and we can refer to the proposed sensing method in order to perform effective spectrum sensing with low power consumption.

• Smart Structures and Systems
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• v.4 no.6
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• pp.759-777
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• 2008

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1555-1570
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• 2016

For monitoring forest fires, a real-time system to prevent fires in wider areas should be supported consistently. However, there has still been a lack of the support for real-time system related to forest fire monitoring. In addition, the 'real-time' processing in a forest fire detection system can lead to excessive consumption of energy. To solve these problems, the intelligent data acquisition of sensing nodes is required, and the maximum energy savings as well as rapid and accurate detection by flame sensors need to be done. In this regard, this paper proposes a node built-in filter algorithm for intelligent data collection of sensing nodes for the rapid detection of forest fires with focus on reducing the power consumption of the remote sensing nodes and providing efficient wireless sensor network-based forest environment monitoring in terms of data transmission, network stability and data acquisition. The experimental result showed that battery life can be extended through the intelligent sampling of remote sensing nodes, and the average accuracy of the measurement of flame detection based on the distance is 44%.