• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.770-775
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• 2009

Along with the advance of USN technology in a human-oriented informatization society these days, society is quickly changing into a ubiquitous computing society in which information even between objects can be organically combined and utilized. In order to successfully build such a ubiquitous computing society, it is indispensable to have core USN technologies such as USN sensor nodes, sensor networks, USN middleware, and USN applied services that efficiently manage sensing information collected from sensor nodes, and support the abstraction function for the composition of sensor networks. In order to process the transmission event of sensing values that are generated from various USN terminal devices, this study designs a process that performs the abstraction of data for the efficient process of diverse sensing values transferred from USN and RFID terminal devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.757-770
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• 2020

We propose a hand gesture recognition method that is compatible with a head-up display (HUD) including small processing resource. For fast link adaptation with HUD, it is necessary to rapidly process gesture recognition and send the minimum amount of driver hand gesture data from the wearable device. Therefore, we use a method that recognizes each hand gesture with an inertial measurement unit (IMU) sensor based on revised correlation matching. The method of gesture recognition is executed by calculating the correlation between every axis of the acquired data set. By classifying pre-defined gesture values and actions, the proposed method enables rapid recognition. Furthermore, we evaluate the performance of the algorithm, which can be implanted within wearable bands, requiring a minimal process load. The experimental results evaluated the feasibility and effectiveness of our decomposed correlation matching method. Furthermore, we tested the proposed algorithm to confirm the effectiveness of the system using pre-defined gestures of specific motions with a wearable platform device. The experimental results validated the feasibility and effectiveness of the proposed hand gesture recognition system. Despite being based on a very simple concept, the proposed algorithm showed good performance in recognition accuracy.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.658-664
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• 2013

In this paper, we present a case study of vibration suppression based on the application of active damping to the small boring process of a boring bar with diameter below ${\Phi}12$. The proposed active damping system consists of an acceleration sensor for real-time monitoring of the vibration signal, a driver for phase control in a computer program, and piezoelectric actuators for damping. In this system, the vibration signals are detected by the acceleration sensor and sent to the computer as an input. The phase shift parameter of the natural frequency of the input signal is sent to the data acquisition board in the computer and calculated by the phase control program. This study confirmed the effectiveness of this damping system, and it opens up the possibility of the development of active damping systems for small boring processes.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.501-512
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• 2018

Radio frequency identification (RFID) sensor tag provides several advantages including battery-less operation and low cost, which are suitable for long-term monitoring. This paper presents a self-powered RFID temperature sensor tag for online temperature monitoring in substation. The proposed sensor tag is used to measure and process the temperature of high voltage equipments in substation, and then wireless deliver the data. The proposed temperature sensor employs a novel phased-locked loop (PLL)-based architecture and can convert the temperature sensor in frequency domain without a reference clock, which can significantly improve the temperature accuracy. A two-stage rectifier adopts a series of auxiliary floating rectifier to boost its gate voltage for higher power conversion efficiency. The sensor tag chip was fabricated in TSMC $0.18{\mu}m$ 1P6M CMOS process. The measurement results show that the proposed temperature sensor tag achieve a resolution of $0.15^{\circ}C$/LSB and a temperature error of $-0.6/0.7^{\circ}C$ within the range from $-30^{\circ}C$ to $70^{\circ}C$. The proposed sensor tag achieves maximum communication distance of 11.8 m.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.10
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• pp.949-955
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• 2007

This paper proposes an efficient localization algorithm in the RFID sensor space for the precise localization of a mobile robot. The RFID sensor space consists of embedded sensors and a mobile robot. The embedded sensors, that is tags are holding the absolute position data and provide them to the robot which carries a reader and requests the absolute position fur localization. The reader, it is called as antenna usually, gets several tag data at the same time within its readable range. It takes time to read all the tags and to process the data to estimate the position, which is a major factor to deteriorate the localization accuracy. In this paper, an efficient algorithm to estimate the position and orientation of the mobile robot as quickly as possible has been proposed. Along with the algorithm, a new allocation of the tags in the RFID sensor space is also proposed to improve the localization accuracy. The proposed algorithms are demonstrated and verified through the real experiments.

• 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.

• International Journal of Naval Architecture and Ocean Engineering
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• v.2 no.3
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• pp.171-176
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• 2010

This paper proposes the application of sensor technology to assemble ship blocks efficiently. A sensor-based monitoring system is designed and implemented to improve shipbuilding productivity by reducing the labor cost for the adjustment of adequate positioning between ship blocks during pre-erection or erection stage. For the real-time remote monitoring of relative distances between two ship blocks, sensor nodes are applied to measure the distances between corresponding target points on the blocks. Highly precise positioning data can be transferred to a monitoring server via wireless network, and analyzed to support the decision making which needs to determine the next construction process; further adjustment or seam welding between the ship blocks. The developed system is expected to put to practical use, and increase the productivity during ship blocks assembly.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.99-101
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• 2006

Auto-Cross Correlated time series (ACTS) model was constructed by using the backpropagation neural network. The performance of ACTS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 3%. By integrating ACTS model into equipment software, process quality can be more stringently monitored while improving device throughput.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.102-104
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• 2006

Auto-Correlated time series (ATS) model was constructed by using the backpropagation neural network. The performance of ATS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 4%. By integrating ATS model into equipment software, process quality can be more stringently monitored while improving device throughput.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.183-186
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• 2012

To process continuous queries on a sensor network, it is required to transfer query predicates and build a query index on each sensor node. However, if we transfer query predicates to all sensor nodes, it makes the number of messages for query predicates increase. In this paper, we propose the scheme to construct the tree based relationship structure using data region of the sensor node and select the target nodes to transfer query predicates. we also implement the tree based relationship structure and measure the number of messages for sending predicates.