• Smart Structures and Systems
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• 제3권3호
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• pp.373-384
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• 2007

For structural health monitoring (SHM) of civil infrastructures, displacement is a good descriptor of the structural behavior under all the potential disturbances. However, it is not easy to measure displacement of civil infrastructures, since the conventional sensors need a reference point, and inaccessibility to the reference point is sometimes caused by the geographic conditions, such as a highway or river under a bridge, which makes installation of measuring devices time-consuming and costly, if not impossible. To resolve this issue, a visionbased real-time displacement measurement system using digital image processing techniques is developed. The effectiveness of the proposed system was verified by comparing the load carrying capacities of a steel-plate girder bridge obtained from the conventional sensor and the present system. Further, to simultaneously measure multiple points, a synchronized vision-based system is developed using master/slave system with wireless data communication. For the purpose of verification, the measured displacement by a synchronized vision-based system was compared with the data measured by conventional contact-type sensors, linear variable differential transformers (LVDT) from a laboratory test.

• 한국환경과학회지
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• 제27권11호
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• pp.1155-1167
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• 2018

We developed a small sensor observation system (SSOS) at a relatively low cost to observe the atmospheric boundary layer. The accuracy of the SSOS sensor was compared with that of the automatic weather system (AWS) and meteorological tower at the Korea Meteorological Administration (KMA). Comparisons between SSOS sensors and KMA sensors were carried out by dividing into ground and lower atmosphere. As a result of comparing the raw data of the SSOS sensor with the raw data of AWS and the observation tower by applying the root-mean-square-error to the error, the corresponding values were within the error tolerance range (KMA meteorological reference point: humidity ${\pm}5%$, atmospheric pressure ${\pm}0.5hPa$, temperature ${\pm}0.5^{\circ}C$. In the case of humidity, even if the altitude changed, it tends to be underestimated. In the case of temperature, when the altitude rose to 40 m above the ground, the value changed from underestimation to overestimation. However, it can be confirmed that the errors are within the KMA's permissible range after correction.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.465-467
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• 2015

본 논문에서는 환경센서를 기반으로 한 스마트폰 연동형 듀얼모드 전원 스트립 제어기를 구현한다. 화재현황통계에 따르면 주거시설의 미확인 전기사고화재가 23.4%를 차지하고 있다. 사용자 부주의로 발생하는 이러한 화재사고를 줄이고 인명과 재산을 보호하기 위해서는 사용자의 편의성을 높인 스마트한 전원제어기술이 필요하다. 이를 위해 논문에서 구현한 듀얼모드 전원 스트립 제어기는 온도, 조도, 습도센서와 같은 환경센서로부터 수집된 데이터를 기반으로 사용자의 스마트폰과 연동하여 전원 스트립의 ON-OFF 동작을 두 가지 방식(수동모드/자동모드)으로 제어한다. 수동모드는 사용자가 스마트폰에 표시된 환경센서 데이터를 보고 강제적으로 전원 스트립의 ON-OFF 동작을 제어하고, 자동모드는 사용자가 미리 설정해 둔 임계치(threshold)를 환경센서 데이터가 벗어날 경우 자동으로 전원 스트립의 ON-OFF 동작을 제어한다. 실험실 테스트를 통해 전원 스트립 제어기의 듀얼모드가 성공적으로 동작함을 확인하였다.

• 농촌계획
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• 제25권2호
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• pp.15-21
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• 2019

The agricultural environment is changing and becoming more advanced due to the influence of the 4th Industrial Revolution. From the basic plan of Rural Informatics to the current level of 2nd generation smart farms aimed at improving productivity using Big data, cloud network and more IoT technology. We are continuing to provide support and research and development. However, many problems remain to be solved in order to supply and settle smart farms in Korea. The purpose of this study is to provide a method of collecting and sharing data on farming environment and to help improve the income and productivity of farmers based on collected data. In the case of hog farm, the multiple sensors for environmental data like temperature, humidity and gases and the network environment for connecting the internet were established. The environment sensor was made using the ESP8266 Node MCU board as micro-controller, DHT22 sensor for temperature and humidity, and MQ series sensors for various gases in the hog pens. The network sensor was applied experimentally for one month and the environmental data of the hog farm was stored on a web database. This study is expected to raise the importance of collecting and managing the agricultural and environmental data, for the next generation farmers to understand the smart farm more easily and to try it by themselves.

• Smart Structures and Systems
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• 제29권1호
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Korean Chemical Engineering Research
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• 제49권4호
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• pp.393-399
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• 2011

지난 수십년 동안, 환경오염물질에 대한 광학적 전기화학적 검출 방법에 관한 다양한 연구가 진행되었다. 최근에는 저렴하고, 장치가 불필요한 육안 식별 가능한 환경색센서가 개발되고 있다. 시각적 정성분석은 대상물질에 대한 즉각적인 정보를 제공하여, 실시간 현장 분석이 가능하게 해준다. 또한 정량분석이 가능한 색센서에 대한 관심도 높아지고 있다. 환경색센서는 기상의 VOC, 액상의 중금속 분석용으로 주로 개발되고 있다. 이에 본 총설에서는 다양한 환경색센서의 활용분야를 살펴보고, 기존 색센서의 문제점을 파악한 다음 환경색센서 기술의 발전방향에 관하여 전망하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제15권4호
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• pp.250-260
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• 2023

In this paper, we designed a IoT(Internet of Things) sensor block embedded lightweight house deck structures that can be implemented using Carbon Fiber Reinforced Polymer(CFRP). Deck-Sensor interconnection interface block via IoT connectivity Hub that can mount external environmental sensors such as fire sensors on the Deck body itself was also proposed. Additionally we described the configuration of devices for data acquisition and analysis based on IoT environmental detection sensors that can be commonly installed and used on these deck bodies. On the other hand, received sensing data based monitoring user interface(UI) also developed and used for sensing data analysis for remote monitoring center. Through the implementation of such IoT-based sensor data transmission and collection analysis devices and UI software, this paper confirmed the availability of CFRP based lightweight House deck structure and possibility of CFRP deck-based IoT sensor data networking and analysis functions.

• 대한기계학회논문집A
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• 제41권4호
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• pp.313-319
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• 2017

광섬유 센서는 전자기 간섭에 독립적이고 원거리 계측이 가능하여 다양한 분야에 적용되고 있다. 특히, 광섬유 브래그 격자(FBG) 센서는 다중화, 절대측정이 가능하여 구조 건전성 모니터링(SHM)을 위해 널리 사용되고 있다. 일반적으로, FBG 센서는 에폭시와 같은 접착제를 이용하여 구조물에 직접 부착 및 모듈 제작을 통해 적용한다. 하지만, 에폭시로 부착된 FBG 센서 기반의 장시간 모니터링 과정에서 신호 변화가 발생하여 보정이 요구된다. 이는 계절적 요인으로써 장시간 온도 변화 환경에 노출되어 센서의 접착구조 변형에 의한 결과이며, 센서 접착제의 열경화 과정에 대한 규명이 필요하다. 본 연구에서는, 패키징 방식 4가지 경우의 FBG 센서 시편을 제작하고, 반복 열하중 시험을 수행하였다. 시험 결과, 상온경화 과정에서 미소한 잔류 압축 변형률이 발생하였고, 반복 열하중 초기단계에서 수백 ${\mu}{\varepsilon}$의 압축 변형률이 인가되어 유지되었다. 이를 통해 FBG를 이용한 장시간 SHM을 위해서는 FBG 센서의 신호에 대한 안정화 과정이 필요함을 확인하였다.

• 센서학회지
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• 제6권4호
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• pp.298-306
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• 1997

초음파센서는 저렴성, 단순한 구조, 기계적 강인성, 사용상의 적은 제약 등의 이점 때문에 다양한 응용분야에 적용된다. 그러나 주요 사용 목적으로는 물체의 감지와 거리측정으로 제한된다. 물체의 인식에 초음파센서를 사용하기에는 낮은 분해능을 초래하는 불량한 방향성과 측정오류를 유발하는 반사성의 단점이 있다. 이런 문제를 극복하기 위해 센서의 배열이 사용되어왔다. 즉, 분해능을 개선하기 위해 다양한 센서의 배열형태에서 많은 수의 센서를 사용하거나, 일정 수의 센서를 사용할 경우에는 센서배열을 기계적으로 이동시킨다. 본 논문에서는 센서배열에 단순한 구동 전자회로를 추가하여 센서 시스템의 인식 분해능을 개선하는 실제적인 방범을 제안한다. 구동회로는 송출 구동전압을 다양하게 변화시켜 알려진 센서의 특성에 따라 서로 다른 수신신호의 진폭으로부터 분해능의 개선을 얻는다. 제안된 방법에서는 사용하는 센서의 수를 증가하거나 추가되는 기계적인 구동기를 사용하지 않으며 분해능의 개선을 얻는다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.226-231
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• 2020

In order to maximize the production of landscape plants in optimal condition while coexisting with the environment in terms of precision agriculture, quick and accurate information gathering of the internal environmental elements of the growing container is necessary. This may depend on the accuracy of the positioning of numerous sensors connected to landscape plants cultivating system (LPCS) in containers. Thus, this paper presents a method for estimating the location of the sensors related to cultivation environment connected to LPCS by measuring the received signal strength (RSS) or time of arrival TOA received between oneself and adjacent sensors. The Small sensors connected to the LPCS of container are known for their locations, but the remaining locations must be estimated. For this in the paper, Rao-Cramer limits and maximum likelihood estimators are derived from Gaussian models and lognormal models for TOA and RSS measurements, respectively. As a result, this study suggests that both RSS and TOA range measurements can produce estimates of the exact locations of the cultivation environment sensors within the wireless sensor network related to the LPCS.