• Journal of KIISE:Databases
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• v.37 no.6
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• pp.324-332
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• 2010

The majority of event detection in real-time embedded sensor network systems is based on data fusion that uses noisy sensor data collected from complicated real-world environments. Current research has produced several excellent low-level mechanisms to collect sensor data and perform aggregation. However, solutions that enable these systems to provide real-time data processing using readings from heterogeneous sensors and subsequently detect complex events of interest in real-time fashion need further research. We are developing real-time event detection approaches which allow light-weight data fusion and do not require significant computing resources. Underlying the event detection framework is a collection of real-time monitoring and fusion mechanisms that are invoked upon the arrival of sensor data. The combination of these mechanisms and the framework has the potential to significantly improve the timeliness and reduce the resource requirements of embedded sensor networks. In addition to that, we discuss about a privacy that is foundation technique for trusted embedded sensor network system and explain anonymization technique to ensure privacy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3965-3982
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• 2015

Event detection is one of the key issues in many wireless sensor network (WSN) applications. The uncertainties that are derived from the instability of sensor node, measurement noise and incomplete sampling would influence the performance of event detection to a large degree. Many of the present researches described the sensor readings with crisp values, which cannot adequately handle the uncertainties inhered in the imprecise sensor readings. In this paper, a fault-tolerant event detection algorithm is proposed based on Dempster-Shafer (D-S) theory (also called evidence theory). Instead of crisp values, all possible states of the event are represented by the Basic Probability Assignment (BPA) functions, with which the output of each sensor node are characterized as weighted evidences. The combination rule was subsequently applied on each sensor node to fuse the evidences gathered from the neighboring nodes to make the final decision on whether the event occurs. Simulation results show that even 20% nodes are faulty, the accuracy of the proposed algorithm is around 80% for event region detection. Moreover, 97% of the error readings have been corrected, and an improved detection capability at the boundary of the event region is gained by 75%. The proposed algorithm can enhance the detection accuracy of the event region even in high error-rate environment, which reflects good reliability and robustness. The proposed algorithm is also applicable to boundary detection as it performs well at the boundary of the event.

• Korean Journal of Optics and Photonics
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• v.26 no.2
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• pp.83-87
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• 2015

This study was focused on developing an optical sensor that monitors ultraviolet (UV) light. Recently, we proposed and demonstrated a novel, highly sensitive UV sensor based on a fiber Bragg grating (FBG). To ensure that the incident UV light is focused on the FBG surface, the sensor was coated with an azobenzene polymer material that acts as a UV-induced stretchable functional material, in combination with a cylindrical focal lens. In this study we have improved the sensitivity of the sensor by employing a cylindrical focal mirror as a curved reflector, to refocus the UV light passing through the FBG. We considered the performance of several different types of reflectors and chose the optimal radius of curvature for the reflector. Compared to the UV sensor without an auxiliary device, the sensitivity of the FBG sensor with a focal lens and a curved reflector was 15 times as high.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.4
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• pp.160-167
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• 2007

In this paper, we presented the development results of high speed wavefront sensor which is used in diagnosing the beam quality of He-Ne laser for adaptive optics system. The beam quality information of laser in AO system is necessarily required for diagnosing the optical components or correcting the distorted wavefront afterward. According to system requirements, normally, it is requested that there are high precision of measurement and real time processing speed. The developed wavefront sensor in this paper achieved maximum 30Hz of measurement rate and ${\lambda}/20(\;{@}\;{\lambda}=0.6328{\mu}m)$ of measurement precision in RMS. We also applied the developed into an experimental adaptive system and verified the performance of it by correcting the aberrated wavefront with a rate of 30Hz and $\lambda$/20 precision using the combination of the developed and PID control algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.689-694
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• 2016

The objective of this study is to identify the requirements for a energy metering device and develop a real-time energy metering device for measuring energy (electricity) consumption of the electric railway vehicle during its operation. The study also evaluated the performance of the AC voltage sensor, current sensor, and data meter for the device and performed EMC tests such as surge and EFT (Burst). The performance tests showed that the percent errors of the AC voltage sensor and current sensor were ${\leq}0.1%$, and ${\leq}0.5%$ under 10~127V, and 10~250A, respectively. The result of surge and EFT (Burst) tests also indicated that the device had no malfunction in any wave (combination and ring waves) under the treat level with 2kV. The result of the field test also confirmed that the device had no malfunction in data metering.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.23-29
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• 2012

Injured peoples usually care their body at medical institutions. But if they need some more rehabilitation to the affected area thus exist. These medical institutions according to the scale there are significant differences in rehabilitation programs, most of the small-scale rehabilitation program for medical doctors and patients to be progression of the conversation is an issue. In this paper, in a small medical facility rehabilitation to assist in the accuracy and reliability, physical contact and force sensors that can measure a combination of substitution and the tactile sensor and tactile sensor alternative with a similar function is proposed. Perceptron neural networks by applying the contact evaluation according to the algorithm to determine the pattern is applied.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.5
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• pp.591-603
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• 2014

In this paper, we have described the characteristics of the Underwater Distributed Sensor Network (UDSN) and proposed the conceptual design guideline by an effectiveness analysis. To perform the effectiveness analysis, we defined an battlefield environment, and then analyzed principal components which compose the UDSN to find out simulation parameters and system constraints. We have chosen a measure of effectiveness based on a target trajectory, which could enhance intuitive understanding about current status, and performed various simulations to reveal critical design parameters in terms of sensor node types, arrangement, cost and combination of detection information.

• Proceedings of the IEEK Conference
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• summer
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• pp.237-243
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• 2004

A multichannel smart sound sensor capable to detect and identify sound events in noisy conditions is presented in this paper. Sound information extraction is a complex task and the main difficulty consists is the extraction of high­level information from an one-dimensional signal. The input of smart sound sensor is composed of data collected by 5 microphones and its output data is sent through a network. For a real time working purpose, the sound analysis is divided in three steps: sound event detection for each sound channel, fusion between simultaneously events and sound identification. The event detection module find impulsive signals in the noise and extracts them from the signal flow. Our smart sensor must be capable to identify impulsive signals but also speech presence too, in a noisy environment. The classification module is launched in a parallel task on the channel chosen by data fusion process. It looks to identify the event sound between seven predefined sound classes and uses a Gaussian Mixture Model (GMM) method. Mel Frequency Cepstral Coefficients are used in combination with new ones like zero crossing rate, centroid and roll-off point. This smart sound sensor is a part of a medical telemonitoring project with the aim of detecting serious accidents.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.352-361
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• 2018

This paper proposes a sensing system of the Halbach array permanent magnet spherical motor(PMSM). The rotor position can be obtained by solving three rotation angles, which revolves around 3 reference axes of the stator. With the development of 3-D hall sensor, the position identification problem of the Halbach array PMSM based on rotor magnetic field is studied in this paper. A nonlinear and serious coupling relationship between the rotation angles and the measured magnetic flux density is established on the basis of the rotation transformation theory and the magnetic field model. In order to get rid of the influence on position detection caused by the harmonics of rotor magnetic field and the stator coil magnetic field, a sensor location combination scheme is proposed. In order to solve the nonlinear equation fast and accurately, a new position solution algorithm which combines the merits of gradient projection and particle swarm optimization(PSO) is presented. Then the rotation angles are obtained and the rotor position is identified. The validity of the sensing system is verified through the simulation.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.427-433
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• 2019

This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.