• 한국공작기계학회논문집
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• 제15권3호
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• pp.73-81
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• 2006

This paper describes our primary study for a new method of recognizing materials, which is need for precision work system. This is a study of dynamic characteristics of smart sensors, new method$(R_{SAI})$ has the sensing ability of distinguishing materials. Experiment and analysis are executed for finding the proper dynamic sensing condition. First, we developed advanced smart sensor. We made smart sensors for experiment. The type of smart sensor is HH type. The smart sensor was developed for recognition of material. Second, we develop new estimation methods that have a sensing ability of distinguish materials. Dynamic characteristics of sensor are evaluated through new recognition index$(R_{SAI})$ that ratio of sensing ability index. Distinguish of object is executed with $R_{SAI}$ method relatively. We can use the $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object (auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.

• 한국정밀공학회지
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• 제19권1호
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• pp.48-55
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• 2002

This paper deals with the sensing ability of the smart sensor that has the sensing ability to distinguish materials according to the input condition changing. This is a study of dynamic characteristics of sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. Experiments and analysis were executed to estimate ability to recognize objects according to the input condition. First, we developed the advanced smart sensor. Second, we developed the new method, which has the capability sensing of different materials. Dynamic characteristics of the smart sensor were evaluated relatively through a new $R_{SAI}$ method. According to frequency changing, influence of the smart sensor are evaluated through a new recognition index ($R_{SAI}$) that ratio of sensing ability index. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safely diagnosis of structure, etc.

• 통합자연과학논문집
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• 제8권1호
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• pp.67-74
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• 2015

Sensing characteristics for porous smart particle based on DBR smart particles were reported. Optically encoded porous silicon smart particles were successfully fabricated from the free-standing porous silicon thin films using ultrasono-method. DBR PSi was prepared by an electrochemical etch of heavily doped $p^{++}$-type silicon wafer. DBR PSi was prepared by using a periodic pseudo-square wave current. The surface-modified DBR PSi was prepared by either thermal oxidation or thermal hydrosilylation. Free-standing DBR PSi films were generated by lift-off from the silicon wafer substrate using an electropolishing current. Free-standing DBR PSi films were ultrasonicated to create DBR-structured porous smart particles. Three different surface-modified DBR smart particles have been prepared and used for sensing volatile organic vapors. For different types of surface-modified DBR smart particles, the shift of reflectivity mainly depends on the vapor pressure of analyte even though the surfaces of DBR smart particles are different. However huge difference in the shift of reflectivity depending on the different types of surface-modified DBR smart particles was obtained when the vapor pressures are quite similar which demonstrate a possible sensing application to specify the volatile organic vapors.

• 복식
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• 제65권1호
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• pp.118-135
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• 2015

In recent years, smart clothing had been developed in order to better detect and monitor physical movement of the patient, so that such activities such as location identification and biometric recognition could be done. However, most of the sensing devices of smart clothing were limited to smart sensing sports clothing and the designs did not consider the physical characteristics and the behavior of the wearer. Therefore, this study aimed to create an open protection system by developing a wearable sensing device for health monitoring and location information. For this purpose, this study developed eleven types of wearable sensing design that could be commercially sold and worn by people who needed their biological information to be constantly monitored. The study conducted four tests in order to develop three types of sensing devices for various sensing wears. The purpose of this study was to expand the user rang of smart sensing wears, and provide a foundation for the development of distinctive wearable sensing devices reflecting the user. Furthermore, contribute to the design for the person subject to protection.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2379-2384
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• 2005

We propose a novel method for object recognition using the smart tag system with a stereo vision on a pan-tilt mechanism. We developed a smart tag which included IRED device. The smart tag is attached onto the object. We also developed a stereo vision system which pans and tilts for the object image to be the centered on each whole image view. A Stereo vision system on the pan-tilt mechanism can map the position of IRED to the robot coordinate system by using pan-tilt angles. And then, to map the size and pose of the object for the robot to coordinate the system, we used a simple model-based vision algorithm. To increase the possibility of tag-based object recognition, we implemented our approach by using as easy and simple techniques as possible.

• 한국인터넷방송통신학회논문지
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• 제13권3호
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• pp.33-38
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• 2013

스마트폰에 탑재된 다양한 종류의 센서들을 활용하여 사용자의 상태나 사회활동 및 주변 환경을 모니터링하는 스마트폰 센싱 시스템에서 특정 지역의 데이터가 손실되는 문제는 피할 수 없다. 다수의 사용자를 대상으로 사전에 정의해 놓은 조건이 만족할 때 센서로부터 측정된 값을 서버로 전송하는 기회기반 센싱 기법에서는 이러한 데이터 손실 문제가 더 심화된다. 본 논문에서는 수집된 데이터의 품질 저하 문제를 해결하기 위해 스마트폰 센싱의 특성을 고려한 손실 데이터 추정 모델을 제안한다. 제안된 추정 모델에서는 데이터의 시공간적 상관관계를 고려할 뿐만 아니라 신뢰도가 높은 데이터를 제공하는 참여자의 우선순위를 높임으로써 향상된 추정 값을 도출하도록 설계하였다. 또한 실험결과를 통해 본 논문에서 제안한 기법이 기존의 기법들에 비해 높은 신뢰도를 보이는 것을 알 수 있었다.

• International journal of advanced smart convergence
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• 제10권3호
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• pp.33-40
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• 2021

Recently, wearable computers equipped with various biosensors such as smart watches, smart bands, and smart patches that support daily health management of users as well as patients have been released. Users of wearable computers such as smart watches face various difficulties in performing biometric information processes such as data sensing, collection, transmission, real-time analysis, and feedback in a weak wireless and mobile biometric information service environment. In particular, the biometric information collection interface is an important basic process that determines the quality and performance of the entire biometric information service. So far, research has focused on sensing hardware and logic. This study intensively considers the interface method for effectively sensing and collecting raw biometric information. In particular, the process of collecting biometric information is designed and analyzed from the perspective of periodicity. Therefore, we propose an efficient and stable periodic collection method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권9호
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• pp.2213-2231
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• 2013

Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.23-26
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• 2000

This paper descrtbcs our prlmary study for a new mncthod of recogninng materials. which is need for precision work system. This IS a study of dynarnlc characteristics of sensor. new melhod ($R_{SAI}$) has thc sensing ability of distinguishing materials. Experiment and annlysis are executed for proper dynamic scnslng condition. First. we developed advanced smart sensor Second, we develop new methods that have a sensing ability of distinguish matarialsAccording to frequency changing. mtluence of smart sensor are evaluated through new recognition Index ($R_{SAI}$) that ratioof sensing ability index. Disungush of object is cxucuted wllh RsA, method relalivcly according to liequency changing. Wecan use the RsAl for finding materids. Applfciltionr of thls method are linding abnormal condition of obicct (automanufacturing).keling ofobject (medlcal product). tobolics, safety diagnosis of structure, etc

• Journal of Communications and Networks
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• 제14권6호
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• pp.614-618
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• 2012

Smart grid is widely considered to be a next generation power grid, which will be integrated with information feedback communications.However, smart grid communication technologies are subject to inefficient spectrum allocation problems. Cognitive radio networks can solve the problemof spectrumscarcity by opening the under-utilized licensed bands to secondary users. In this paper, adaptive cognitive radio spectrum sensing and sharing algorithms are developed for smart grid environments. Simulation results are presented to demonstrate the effectiveness of the proposed scheme in comparison with other existing schemes.