• Proceedings of the KSR Conference
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• 2007.11a
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• pp.989-993
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• 2007

It was intended in this study to seek for the measures to utilize the USN technique, which has high usability due to low price and low power consumption, in air quality monitoring. As a method, the sensors of temperature, humidity, particulate matters (PM10), and carbon dioxide ($CO_2$) were installed in the self-manufactured sensor nodes; the nodes were installed in the waiting rooms and platforms of a subway station and the measurements were collected at real time with use of a computer which micro gateway was built in. Collected data was to be processed by the statistics program installed in the computer; the collected data is to be used in managing the air quality of stations after transmission to the ventilation system of ventilation chambers.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.911-923
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• 2010

In wireless sensor networks (WSNs), cluster based data routing protocols have the advantages of reducing energy consumption and link maintenance cost. Unfortunately, most of clustering protocols have been designed for uniformly distributed sensor networks. However, some urgent situations do not allow thousands of sensor nodes being deployed uniformly. For example, air vehicles or balloons may take the responsibility for deploying sensor nodes hence leading a normally distributed topology. In order to improve energy efficiency in such sensor networks, in this paper, we propose a new cluster formation algorithm named DAEEC (Density Aware Energy-Efficient Clustering). In this algorithm, we define two kinds of clusters: Low Density (LD) clusters and High Density (HD) clusters. They are determined by the number of nodes participated in one cluster. During the data routing period, the HD clusters help the neighbor LD clusters to forward the sensed data to the central base station. Thus, DAEEC can distribute the energy dissipation evenly among all sensor nodes by considering the deployment density to improve network lifetime and average energy savings. Moreover, because the HD clusters are densely deployed they can work in a manner of our former algorithm EEVAR (Energy Efficient Variable Area Routing Protocol) to save energy. According to the performance analysis result, DAEEC outperforms the conventional data routing schemes in terms of energy consumption and network lifetime.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3079-3089
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• 2015

In this paper, a smart constrained application protocol (CoAP)-based gateway with a border router is proposed for home safety services to remotely monitor the trespass, fire, and indoor air quality. The smart CoAP gateway controls a home safety sensor node with a pyroelectric infrared motion sensor, a fire sensor, a humidity and temperature sensor, and a non-dispersive infrared CO2 sensor and gathers sensing data from them. In addition, it can convert physical sensing data into understandable information and perform packet conversion as a border router for seamless connection between a low-power wireless personal area network (6LoWPAN) and the Internet (IPv6). Implementation and laboratory test results verify the feasibility of the smart CoAP gateway which especially can provide about 97.20% data throughput.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.245-249
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• 2021

In this paper, we present novel simulation contents for drone racing and autonomous flight of drone. With Depth camera and SLAM, we conducted mapping 3 dimensional environment through RTAB-map. The 3 dimensional map is represented by point cloud data. After that we recovered this data in Unreal Engine. This recovered raw data reflects real data that includes noise and outlier. Also we built drone racing contents like gate and obstacles for evaluating drone flight in Unreal Engine. Then we implemented both HITL and SITL by using AirSim which offers flight controller and ROS api. Finally we show autonomous flight of drone with ROS and AirSim. Drone can fly in real place and sensor property so drone experiences real flight even in the simulation world. Our simulation framework increases practicality than other common simulation that ignore real environment and sensor.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.392-393
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• 2005

Due to the temporal and spatial simultaneity and the high-frequency repetition, the data set retrieved from the satellite observation is considered to be the most desirable ones for the study of air-sea interaction. With rapidly developing sensor technology, satellite-retrieved data has experienced improvement in the accuracy and the number of parameters. Nevertheless, since it is still impossible to directly measure the heat fluxes between air and sea, the bulk method is an exclusive way for the evaluation of the heat fluxes at the sea surface. It was noted that the large deviation of air temperature in the winter season by the linear regression despite good correlation coefficients. We propose a new algorithm based on the Fourier series with which the SST and the air temperature. We found that the mean of air temperature is a function of the mean of SST with the monthly gradient of SST inferred from the latitudinal variation of SST and the spectral energy of air temperature is related linearly to that of SST. An algorithm to obtain the air temperature over the sea was completed with a proper analysis on the relation between of air temperature and of SST. This algorithm was examined by buoy data and therefore the air temperature over the sea can be retrieved based on just satellite data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.140-145
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• 2022

In an advanced modern society, among air pollutants caused by urban industrialization and public transportation, fine dust flows into indoors from the outdoors. The fine dust meter used indoors provides limited information and measures the pollution level differently, so there is a problem that users cannot monitor and monitor the data they want. To solve this problem, in this paper, indoor air quality data fine dust and ultra-fine dust (PM1.0, PM2.5, PM10), VOC (Volatile Organic Compounds) and PIR (Passive Infrared Sensor) are used to measure fine dust. and a monitoring system were designed and implemented. We propose a fine dust meter and monitoring system that is installed in a designated area to measure fine dust in real time, collects, stores, and visualizes data through App Engine of Google Cloud Platform and provides it to users.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.10
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• pp.1017-1025
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• 2008

The air data system(ADS) was developed for unmanned aerial vehicle(UAV) in this paper. Generally, the ADS helps flight control computer(FCC) to control the UAV above the stall speed and to hold the given altitude. The accurate measurement of airspeed and altitude of UAV is important because it indicates a flight performance and assures a safe flight. The ADS consists of MEMS pressure sensors, a lowpass filter, a micro controller unit and a pitot-tube. The ADS errors were reduced by pressure and temperature compensation of MEMS sensors. Finally, the altitude and airspeed data of the ADS was compared with GPS data in the flight test.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.1
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• pp.23-29
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• 2016

In this paper, in order to quantify the peristalsis occurrence in a guinea pig's large intestine, a miniaturized air-gap capacitive pressure sensor was fabricated through micro-electro-mechanical system (MEMS). The proposed pressure sensor is a two-layered biocompatible polyimide substrate consisting of an air-gap capacitive plates between the substrates. The proposed pressure sensor was designed with a careful consideration of the structure and motility mechanism of the guinea pig's large intestine. Artificial pellets were mounted on a prototype pressure sensor to provide some redundancies in the form of size and shape of the guinea pig feces. Capacitance of a prototype sensor was recorded to be 2.5 ~ 3 pF. This capacitance value was later converted to count value using a lab fabricated data conversion system. Sensitivity of the pressure sensor was recorded to be below 1 mmHg per atmospheric pressure. During in vivo testing, artificial peristalsis caused by drug injection was measured by inserting the prototype pressure sensor into the guinea pig's large intestine and pressure data obtained due to artificial peristalsis was graphed using a labview program. The proposed pressure sensor could measure the pressure changes in the proximal, medial, and distal parts of the large intestine. The results of the experiment confirmed that pressure changes of guinea pig's large intestine was proportional to the degree of drug injection.

• Journal of Aerospace System Engineering
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• v.11 no.5
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• pp.20-27
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• 2017

The present paper describes the flow analysis of the flows around the multicopter for the selection of optimal position of air data sensor. For the flow analysis, the commercial fluid dynamics solver, STAR-CCM+ was used with polygon mesh and k-w SST turbulence modeling options. For the simulation of each rotating 4 propellers, unstructured overset mesh method was used. Hovering, forward flight, ascending and descending flight conditions are selected for the analysis and airspeed and flow angle errors were investigated using the CFD results. Through the flow field analysis, sensor location above one propeller diameter distance from the propeller rotating plane showed airspeed error less than 1m/s within the typical flight conditions of multicopter except descending.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.6
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• pp.639-649
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• 2020

Air data systems measure airspeed, pressure altitude, angle of attack and angle of sideslip. These measurements are essential for operating flight control laws to ensure safe flights. Since the loss or corruption of air data measurements is considered as catastrophic, a high level of operational reliability needs to be achieved for air data systems. In the case of unmanned air vehicles, failure of any of air data sensors is more critical due to the absence of onboard pilot decision aid. This paper presents design of a dual redundancy air data system and the integration process for an unmanned air vehicle. The proposed dual-redundant architecture is based on two independent air data probes and redundancy management by central processing in two independent flight control computers. Starting from unit testing of single air data sensor, details are provided of system level tests used to meet overall requirements. Test results from system integration demonstrate the efficiency of the proposed process.