• 통합자연과학논문집
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• 제9권3호
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• pp.199-205
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• 2016

In this paper, we established ZIGBEE home network and combined smart-grid and u-Healthcare system. We assisted for amount of electricity management of household by interlocking home devices of wireless sensor, PLC modem, DCU and realized smart grid and u-Healthcare at the same time by verifying body heat, pulse, blood pressure change and proceeded living body signal by using SVM algorithm and variety of ZIGBEE network channel and enabled it to check real-time through IHD which is developed by user interface. In addition, we minimized the rate of energy consumption of each sensor node when living body signal is processed and realized Query Processor which is able to optimize accuracy and speed of query. We were able to check the result that is accuracy of classification 0.848 which is less accounting for average 17.9% of storage more than the real input data by using Mjoin, multiple query process and SVM algorithm.

• 제어로봇시스템학회논문지
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• 제12권9호
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• pp.905-911
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• 2006

Smart homes are expected to offer various intelligent services by recognizing the residents' life pattern, health, and feeling. One of the key issues for realizing the smart home is how to detect the locations of residents. Currently, the research effort is focused on two approaches: terminal-based and non-terminal-based method. The terminal-based method employs a type of device that should be carried by the resident while the non-terminal-based method has no such device. This paper presents a novel non-terminal-based approach using an array of pyroelectric infrared sensors (PIRs) that can detect residents. The feasibility of the system is evaluated experimentally on a test bed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.281-283
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• 2009

This paper presents the smart fan which is operated by a small conventional motor and an ultrasonic sensor. The smart fan generates cool wind with regulated speed of wing by the distance between the user and the fan. In this research, an 8-bit microcontroller (ATmega128) and an ultrasonic sensor (NT-TS601) are utilized for the system control and sensing information. In order to obtain the speed information from the encoderless DC motor, a stroboscope is used, which provides the voltage variation by the motor speed. The proposed smart fan makes the user feel cool, convenient and safe at a low cost.

• International Journal of Computer Science & Network Security
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• 제21권2호
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• International journal of advanced smart convergence
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• 제11권3호
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• pp.72-78
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• 2022

The aim of this research is to improve the effectiveness of digital media advertising because current advertisements -in digital signage - indiscriminately appeals to the general public rather than to a specific target. In order to deliver efficient and customized advertisement information, an IoT human body detection sensor mounted on digital signage detected human faces and then classified them firstly by gender. The digital signage here is a smart digital signage that can analyze facial signals, discriminate them based on patterns, and apply the extracted data by displaying the corresponding information to the user. In addition, by identifying the customer's location approaching the smart digital signage and displaying the optimized content information for the customer's location through an algorithm, the digital signage can dramatize the advertisement Thus, this is a study meant forimproving information efficiency while reducing noise and driving power waste generated from unnecessary digital information reproduction.

• 한국인터넷방송통신학회논문지
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• 제9권5호
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• pp.65-71
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• 2009

유비쿼터스 센서 네트워크 기술은 새로운 컴퓨팅 패러다임인 유비쿼터스 컴퓨팅의 핵심 분야로서, 무선 센서 네트워크를 이용한 상황정보 모니터링 시스템에 적합한 기술이다. 이 기술을 모니터링 시스템에 적용하면 열악한 환경에 간편하고 저렴한 비용으로 실시간으로 발생된 상황데이터를 수집 및 분석하여 즉각적인 상황대처와 사용자가 원하는 환경의 조건을 효율적으로 수행할 수 있다. 한편, 센서 네트워크 미들웨어는 에너지 사용에 제약을 가지는 센서 네트워크의 요구사항과 다양한 서비스 제공을 위한 서비스 확장성을 고려하여 센서 네트워크와 응용 서비스가 상호 분리되어 각각의 기능을 수행하고 제어 및 모니터링이 쉽도록 설계되어야 한다. 본 논문에서는 스마트 홈에서 프로파일과 표준화된 관리 프로토콜을 사용하여 무선 센서 네트워크를 영역기반으로 관리하는 프로토콜을 제안한다. 제안된 시스템은 수집될 데이터의 양이 적고 지속적인 모니터링이 불필요하고 일정한 간격으로 특정 지역에서 발생되는 상황을 감지하는 작업에서 기존 유선 통신을 이용한 상황감시보다는 효율적이다.

• 스마트미디어저널
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• 제12권10호
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• pp.55-62
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• 2023

농업 및 축산업 분야에서 혁신과 변화가 빠르게 진행되고 있으며, 스마트 축사와 같은 새로운 기술의 도입이 이루어지고 다양한 센서의 활용으로 장비 제어가 가능한 데이터들이 수집되고 있다. 그러나 축사 운영에는 다양한 어려운 과제들이 존재하며, 이러한 문제들을 해결하기 위하여 가상센서 기술이 필요하게 되었다. 본 논문에서는 축사에 사용되는 다양한 데이터 항목과 센서 데이터 유형을 정의하고 타 분야에서 가상센서를 활용한 사례를 연구하며 최종 스마트 축사를 위한 가상센서 시스템을 구현하고 설계하였다. 최종적으로 구현된 시스템에 대한 평가 및 성능 지표 분석을 위한 MBE와 EVRMSE를 활용하였으며, 가상센서를 활용하여 데이터 수집 및 관리를 진행한 결과 실물센서와의 데이터 값 차이가 뚜렷하지 않아 만족스러운 결과를 보였다. 스마트 축사에서 가상센서 시스템을 활용하면 축사 운영 및 가축 건강 상태 모니터링 등 다양한 부분에서 혁신과 효율성 향상을 기대할 수 있을 것으로 기대한다. 이 논문은 스마트 축사 분야에서 가상 센서 기술을 활용하여 데이터 수집 및 관리의 혁신적인 방법을 제안하고, 그 성능을 검증하는데 있어서 중요한 결과를 도출한 연구이며, 향후 연구과제로 가상 센서를 활용한 디지털 축사의 연결 등을 탐색하고자 한다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.136-141
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• 2007

This paper introduces an artificial neuron which is a nano composite continuous sensor. The continuous nano sensor is fabricated as a thin and narrow polymer film sensor that is made of carbon nanotubes composites with a PMMA or a silicone matrix. The sensor can be embedded onto a structure like a neuron in a human body and it can detect deteriorations of the structure. The electrochemical impedance and dynamic strain response of the neuron change due to deterioration of the structure where the sensor is located. A network of the long nano sensor can form a structural neural system to provide large area coverage and an assurance of the operational health of a structure without the need for actuators and complex wave propagation analyses that are used with other methods. The artificial neuron is expected to effectively detect damage in large complex structures including composite helicopter blades and composite aircraft and vehicles.

• 한국항행학회논문지
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• 제18권6호
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• pp.648-652
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• 2014

기존의 IT 산업 환경은 인터넷을 중심으로 하는 멀티미디어 콘텐트 기반이었으나, 최근 센서와 통신 기술을 접목한 유비쿼터스 기술이 부각되고 있으며 이를 USN (ubiquitous sensor network)라 한다. 건강관리 분야는 USN 적용에 매우 적합한 문야의 하나로 여겨지고 있다. 본 논문에서는 USN을 기반으로 영유아의 건강과 안전을 관리하기 위해 스마트 센서를 이용한 baby care 시스템을 제안하였다. 제안된 시스템은 낙상 감지 센서, 울음 감지 센서, 발열 감지 센서와 정보 전달을 위한 블루투스 네트워크로 구성되었다. 구현된 시스템은 시현을 통해 실효성을 확인하였다.

• 한국통신학회논문지
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• 제35권9B호
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.