Earticle

본 연구에서 사용된 MOS 타입의 가스센서는 저전력, 높은 감도특성과 응답속도 및 소자의 가격이 저렴 하고 전기전도도가 변화하는 특성을 가지고 있다. 따라서 벼에서 발생하는 메탄가스 검출이 가능한 센서 어레이를 설계, 제작하여 시스템과 인터페이스 가능한 장치를 제작하였다. 센서 어레이는 25개로 구성 되어있으며, 어레이 보드로부터 획득한 데이터는 Labview 기반 알고리즘을 이용하여 실시간 측정모니터링 운영 가능한 GUI 시스템 이다. GUI 개발시스템은 8단계의 메탄가스 농도를 측정 가능하여 벼 모종의 성장환경의 개선 및 관리가 가능할 것이다. 향후, 농업 분야에서 메탄 배출에 대한 규제와 배출 저감 대책연구에서 메탄 발생량의 정확한 평가과제로 활용가치가 있을 것으로 사료된다.

In this study, the MOS-type gas sensor used has the characteristics of low power, high sensitivity and response speed, low device price, and changing electrical conductivity. Therefore, a sensor array capable of detecting methane gas generated from rice was designed and manufactured to create a device capable of interface with the system. The sensor array consists of 25 pieces, and the data obtained from the array board is a GUI system that can operate real-time measurement monitoring using Labview-based algorithms. The GUI development system can measure the concentration of methane gas in eight stages, thereby improving and managing the growth environment of rice seedlings. In the future, it is believed that it will be valuable to use as an accurate evaluation task of methane generation in regulations on methane emissions in the agricultural sector and research on emissions reduction measures.

Nowadays, research works into the dynamic and static human activities on Smart spaces abounds. Artificial Intelligence (AI) and low cost non-privacy invasive ambient sensors have made this ubiquitous. This review presents a state-of-the-art analysis, performance evaluation, and future research direction. One of the aims of activity recognition (especially that of humans) systems using thermal sensors and AI is the safety of persons in Smart spaces. In a Smart home, human activity detection systems are put in place to ensure the safety of persons in such an environment. This system should have the ability to monitor issues like fall detection, a common home-related accident. In this work, a review of trends in thermal sensor deployment, an appraisal of the popular datasets, AI algorithms, testbeds, and critical challenges of the recent works was provided to direct the research focus. In addition, a summary of AI models and their performance under various sensor resolutions was presented.

Detection of estrus is an essential factor as a method of successful breeding in the sow. As increasing the adaption of the information and communication technology (ICT) into swine industry, this study focuses on a possibility and quantification of standing time, vulva and body temperature as methods of estrus detection, comparing each time and temperature in estrus and non-estrus period, and analyzing each success rate of new and existing methods. Ultrasonic sensor array and digital infrared thermography were used to evaluate whether new methods such as standing time and number, and vulva and skin temperature can be replaced, or these methods can be quantifiable in estrus period. Ultrasonic sensor array was installed beside the stall and digital infrared thermography was placed in the rear of sow to collect the dates of sow in estrus and non-estrus period. This study showed total standing time, number and number over 10 minutes, and vulva temperature of the sow in estrus period were increased (p < 0.05) compared with those of sow in non-estrus period, respectively. Detection of estrus using standing time and vulva temperature tended (p = 0.06) to increase the success rate when artificial insemination (AI) was performed. In conclusion, standing time and vulva temperature increased when estrus happened. Success rate of AI of sow using these methods showed an increasing trend. Therefore, existing method using the naked eye can be replaced to new method such as vulvar temperature and standing time when detecting the estrus.

The key motivation of this study is for a style of the sensor arrangement to have an effect on the localization performance of mobile robots in case of using sonar sensors. In general robot platforms with sonar sensors, sonar sensors are supposed to be radially arranged on their rotational axis of mobile robots. However, relevant limits to several functions required for their autonomous navigation occur unexpectedly, because a sonar sensor generally has the negative nature of its wide beam width together with the specular reflection. We present a new strategy of the sonar sensor arrangement capable of enhancing the localization performance. Sonar sensors are intended to be arranged nonradially (twistedly expressed in this paper) on their rotational axis. The localization scheme called STARER: Sonar-Twisted ARrangement localizER is based on the extended Kalman filter (EKF) with occupancy grid maps. Experimental results demonstrate the validity and robustness of the proposed method for the localization of mobile robots.

In order to improve the accuracy and reliability of temperature measurements, put forward a kind of high precision non-contact temperature measuring system, which is composed of the quartz temperature sensor array and microprocessors. The sensor used by the system is the quartz tuning fork non-contact temperature sensor based on polymer line, and the polymer line that is highly sensitive to temperature is as the sensitive element, in combination with quartz tuning fork resonator that is not sensitive to the temperature , and they form the high precision temperature sensor together. Compared with the traditional thermometry, set up a new temperature sensor array to measure temperature, which uses the Bayes estimation to fuse the data measured by the temperature sensor array, and calculate the accurate temperature measurements. The experimental results shown that the measurement precision of sensing system is 0.02℃, and the sensitivity is 71.5×10-6/℃within temperature range from 0°C to 100°C.The system has advantages of the high precision, and the good stability, and reliable performance, etc.

MUSIC algorithm has often used to solve the direction of arrival estimation problem to take advantage of the benefits of beamspace operations, such as reduced computation complexity, reduced sensitivity to system errors, good resolution, reduced bias in the estimation. In this paper, a variant of the beamspace MUSIC algorithm is developed, taking advantage of unitary transformations. In general, the beamspace MUSIC algorithm improves direction of arrival estimation by using reduced order characteristic polynomial rooting though Gaussian column reduction. The unitary beamspace MUSIC algorithm reduces the computational complexity of MUSIC algorithm by using real valued forward and backward, while maintaining the original precision. We use forward backward spatial smoothing technique as the preprocessor of beamspace MUSIC algorithm to recover the reduced rank of the covariance matrix due to the coherence of source signals. Through computer simulations show that the combination of spatial smoothing a beamspace MUSIC can achieve good resolution performance.

Coastal surveillance and harbour defence are the most complex and challenging opera- tional issues for modern navy in the current turbulent global political climate. In most of the coastal surveillance and harbour defence systems, long sea-bed arrays consisting of hundreds of pressure sensors are deployed along the coastal belt to capture the low frequency compo- nents emanating from the sub-surface targets. Deployment of these sensor-arrays along with its associated signal conditioning hardware at the ocean-bed is a challenging task. The output of the sensor-array is to be conditioned and then digitized using multi-bit analog to digital converters (ADC). Further, the digitized channel data are required to be send to a base station through a radio frequency link. In this paper, we propose a compressively sampled (CS) architecture of acoustic vector sensor (AVS) array, to estimate the direction of arrival (DoA) of multiple acoustic sources, in a range independent shallow ocean using a one-dimensional search without prior knowledge of the ranges and the depths of the sources. We extend the high resolution angular spectral estimators MUSIC, MVDR and subspace in- tersection method (SIM) to suit the compressively sampled AVS array architecture operating in a shallow ocean environment. This architecture promises a signicant reduction in the number of sensors, analog signal conditioning hardware, data rate or bandwidth, the number of snapshots and the software complexity, leading to easy installation and maintenance.

This paper proposes 128x8 array swipe type fingerprint sensor with a capacitive-sensing technique for image enhancement. The circuit of one pixel includes a pixel level charge-sharing and charge pump to replace an ADC. The circuit also adopts the circuit technique that improves quality of dry finger image captured with capacitive fingerprint sensor LSIs. The proper operation is validated by HSPICE for one-pixel and RTL simulation including logic synthesis for a full chip design on condition of 0.35μm typical CMOS process and 3.3V power. The layout is performed by full custom flow for one-pixel and auto P&R for a full chip. The area of a full chip is 0.161mm2 (9013μm x 1781μm) and the gate count is 303,329. The area of one-pixel is 58 x 58 μm2. Pitch is 60 μm and image resolution is 423dpi.

실내에서의 위치기반 서비스를 위한 실내 위치 인식 기술에 대한 연구가 활발하다. 음향 신호와 TDOA 기술을 기반으로 하는 3차원 위치 인식 시스템에 있어서, 마이크 센서의 개수와 배열 위치에 따라 추정된 위치의 오차 특성이 달라지므로, 본 논문에서는 마이크 센서의 배열과 측정된 거리 차이값의 오차 크기에 따른 추정 위치의 오차를 DOP로 분석하고, 그 추정 위치 오차 패턴과 추정 위치 오차값을 고려하여 최적의 마이크 배열을 결정하는 방법에 대해서 연구하였다.

A study on the indoor positioning system has been active recently for the location based service indoors. In the 3 dimensional positioning system based on the acoustic signal and TDOA technology, the error characteristics of the estimated source position would be changed depending on the number of microphones and the pattern of the microphone array. In this paper, the estimated position error according to the measured distance error between the microphones and the signal source is analyzed, and the optimum microphone array is decided considering the estimated position error patterns and the total amount of the estimated position error.

We present gas sensing performance based on $2{\times}2$ sensor array with four different elements ($TiO_2$, $SnO_2$, $WO_3$ and $In_2O_3$ thin films) fabricated by rf sputter. Each thin film was deposited onto the selected $SiO_2$/Si substrate with Pt interdigitated electrodes (IDEs) of $5{\mu}m$ spacing which were fabricated on a $SiO_2$/Si substrate using photolithography and dry etching. For 5 ppm $NO_2$ and 50 ppm CO, each thin film sensor has a different response to offers the distinguishable response pattern for different gas molecules. Compared with the conventional micro-fabrication technology, $2{\times}2$ sensor array with such remarkable response pattern will be open a new foundation for monolithic integration of high-performance chemoresistive sensors with simplicity in fabrication, low cost, high reliablity, and multifunctional smart sensors for environmental monitoring.

A micromachined fluidic structure for the introduction of liquid samples into a chip-based sensor array composed of individually addressable polymeric microbeads has been developed. The structure consists of a separately attached cover glass, a single silicon chip having micromachined channels and microbead storage cavities, and a glass carver. In our sensor array, transduction occurs via colorimetric and fluorescence changes to receptors and indicator molecules that are covalently attached to termination sites on the polymeric microbeads. Data streams are acquired for each of the individual microbeads using a CCD. One of the key parts of the structure is a passive fluid introduction system driven only by capillary force. The velocity of penetration of a horizontal capillary for the device having a rectangular cross section has been derived, and it is quite similar to the Washburn Equation calculated for a pipe with a circular cross section having uniform radius. The test results show that this system is useful in a ${\mu}$-TAS and biomedical applications.

Nowadays, most major automobile manufacturers are very interested, and actively involved, in developing driver alcohol detection system for safety (DADSS) that serves to prevent driving under the influence. DADSS measures the blood alcohol concentration (BAC) from the driver's breath and limits the ignition of the engine of the vehicle if the BAC exceeds the reference value. In this study, to optimize the sensor array of the DADSS, we selected sensors by using three different methods, configured the sensor arrays, and then compared their performance. The Wilks' lambda, stepwise elimination and filter method (using a principal component) were used as the sensor selection methods [2,3]. We compared the performance of the arrays, by using the selectivity and sensitivity as criteria, and Sammon mapping for the analysis of the cluster type of each gas. The sensor array configured by using the stepwise elimination method exhibited the highest sensitivity and selectivity and yielded the best visual result after Sammon mapping.

Gas-sensor array technology, which has been much utilized in the field of food technology by the name of 'electronic nose' is drawing attention in diagnosing lung cancer based on the analysis of the exhaled human breath. Much understanding has been accomplished about the composition of the volatile organic compounds (VOCs) of the human exhaled breath, in spite of some variations depending on research groups due mainly to lack of the standardization of the sensing procedures. Since VOCs may be produced during the process of cellular metabolism, difference in the cellular metabolism between healthy cells and lung cancer cells are expected to be reflected on the composition variation of the exhaled VOCs. Several studies have attempted to apply the gas-sensor array technology to lung cancer analysis using many different types of sensors including metal oxide, carbon black-polymer composite, surface acoustic wave, and gold nanoparticles. In this mini-review VOC as biomarkers, sensor array technology and application of the array technology for the diagnosis of cancer disease have been described.

A simple array of metal-insulator-metal capacitive elements was proposed for a potential application in humidity sensing platforms. We fabricated meso-scale sensors with different sizes(large-size: $2.7{\times}2.7mm^2$ ; mid-size: $1.5{\times}1.5mm^2$ ; small-size: $0.7{\times}0.7mm^2$) and characterized the performance of each design. Polyimide films were utilized as a humidity-sensitive layer. Capacitance changes of the polyimide layer were measured with respect to water absorption. The device showed sensitivity in the full range of relative humidity (RH) with excellent linearity(correlation coefficient > 0.994). This array structure exhibits unique advantages including easy fabrication process, high batch productivity, and high structural compatibility with various substrate materials. It is anticipated that this device structure will be potentially useful in unique applications including mapping spatial humidity variations over a meso-scale area and implementing flexible humidity sensing element arrays.

1. Introduction 2. Distance measurement using array 3. Linearization of CdS array characteristics 3.1. Crisp linearization of CdS array characteristics 3.2. Fuzzy logic linearization of CdS array characteristics 4. Magnetic Levitation System 4.1. Design of MLS 4.2. Implementation of MLS 4.3. Results of MLS 5. Conclusion