• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.123-126
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• 2005

Wireless Sensor Networks will revolutionize applications such as environmental monitoring, home automation, and logistics. We developed forest fire surveillance system. In this paper, Considering the fact that in Korea, during November to May, forest fires occur very frequently causing catastrophic damages on the valuable environment, Although exists other forest fire surveillance system such as surveillance camera tower, infrared ray sensor system and satellite system. Preexistence surveillance system can't real-time surveillance, monitoring, database and automatic alarm. But, forest fire surveillance system(FFSS) support above. In this paper, we describes a system development approach for a wireless sensor network based FFSS that is to be used to measure temperature and humidity as well as being fitted with a smoke detector. Such a device can be used as an early warning fire detection system and real-time surveillance in the area of a bush fire or endangered public infrastructure. Once the system has being development, a mesh network topology will be implemented with the chosen sensor node with the aim of developing a sophisticated mesh network.

• Smart Structures and Systems
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• v.8 no.1
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• pp.119-137
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• 2011

A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.281-293
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• 2018

As the public interest in environmental issues increased, the "Act On The Integrated Control Of Pollutant-Discharging Facility" was enacted. Through the integrated environmental pollution prevention act in which 19 industries with large environmental impacts are sequentially applied, pollutants can be managed in a medium-integrated manner and integrated permission of the business unit is possible and BAT can be applied to enable a scientific and proactive environmental management system. This study analyzed the overview of BAT reference documents(BREF), BAT setting procedure and method, and then suggested the development direction BAT and BAT-AEL monitoring method of a Electricity and Steam production facility.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.770-780
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• 2022

In 1993 the University of Extremadura initiated the design, construction and management of the Radiological Alert Network of Extremadura (RAREx). The goal was to acquire reliable near-real-time information on the environmental radiological status in the surroundings of the Almaraz Nuclear Power Plant by measuring, mainly, the ambient dose equivalent. However, the phased development of this network has been carried out from two points of view. Firstly, there has been an increase in the number of stations comprising the network. Secondly, there has been an increase in the number of monitored parameters. As a consequence of the growth of RAREx network, large data volumes are daily generated. To face this big data paradigm, software applications have been developed and implemented in order to maintain the indispensable real-time and efficient performance of the alert network. In this paper, the description of the current status of RAREx network after 30 years of design and performance is showed. Also, the performance of the graphing software for daily assessment of the registered parameters and the automatic on real time warning notification system, which aid with the decision making process and analysis of values of possible radiological and non-radiological alterations, is briefly described in this paper.

• Journal of Environmental Science International
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• v.3 no.4
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• pp.381-391
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• 1994

This paper presents the disributions and variations of CO, $CO_2$, number of people and temperature in underground shopping center and subway of Seomyeon and Jagalchi in Pusan, Korea for two times during October and November in 1993, respectively. NDIR analyzer is used for the analysis of CO and $CO_2$. The temperature is obtained from a mercury therometer. The results o( observation and analysis show that the variation of $CO_2$ is strongly related to number of people and temperature. The correlation coefficients between temperature, COB and Number of people are higher than 0. at both of places. The pollution of CO2 of Seomyeon is higher than that of Jagachi in underground shopping center. However, CO is not correlated with the temperature and the Number of people. From the results, we found that the indoor air quality monitoring system is needed for the prevention of the underground air Pollution.

• Journal of electromagnetic engineering and science
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• v.15 no.2
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• pp.104-110
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• 2015

As civil infrastructures continue to deteriorate, the demand for structural health monitoring (SHM) has increased. Despite its outstanding capability for damage identification, many conventional SHM techniques are restricted to huge structures because of their wired system for data and power transmission. Although wireless data transmission using radio-frequency techniques has emerged vis-$\grave{a}$-vis wireless sensors in SHM, the power supply issue is still unsolved. Normal batteries cannot support civil infrastructure for no longer than a few decades. In this study, we develop a magnetic resonance-based wireless power transmission system, and its performance is validated in three different mediums: air, unreinforced concrete, and reinforced concrete. The effect of concrete and steel rebars is analyzed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.896-898
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• 2012

Recently, many countries are making efforts for the development of ocean resources because the necessity and importance of the ocean resources are increased. Underwater sensor networks have emerged as a very powerful technique for many applications, including monitoring, measurement, surveillance and control and envisioned to enable applications for oceanographic data collection, ocean sampling, environmental and pollution monitoring, offshore exploration, disaster prevention, tsunami and seaquake warning, assisted navigation, distributed tactical surveillance, and mine reconnaissance. The idea of applying sensor networks into underwater environments (i.e., forming underwater sensor networks) has received increasing interests in monitoring aquatic environments for scientific, environmental, commercial, safety, and military reasons. The data obtained by observing around the environment are wireless-transmitted by a radio set with various waves. According to the technical development of the medium set, some parameters restricted in observing the ocean have been gradually developed with the solution of power, distance, and corrosion and watertight by the seawater. The actual matters such as variety of required data, real-time observation, and data transmission, however, have not enough been improved just as various telecommunication systems on the land. In this paper, a wireless management system will be studied through a setup of wireless network available at fishery around the coast, real-time environmental observation with RF sensor, and data collection by a sensing device at the coastal areas.

• Smart Structures and Systems
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• v.29 no.1
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• pp.93-103
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• 2022

With the wider availability of sensor technology through easily affordable sensor devices, several Structural Health Monitoring (SHM) systems are deployed to monitor vital civil infrastructure. The continuous monitoring provides valuable information about the health of the structure that can help provide a decision support system for retrofits and other structural modifications. However, when the sensors are exposed to harsh environmental conditions, the data measured by the SHM systems tend to be affected by multiple anomalies caused by faulty or broken sensors. Given a deluge of high-dimensional data collected continuously over time, research into using machine learning methods to detect anomalies are a topic of great interest to the SHM community. This paper contributes to this effort by proposing a relatively new time series representation named "Shapelet Transform" in combination with a Random Forest classifier to autonomously identify anomalies in SHM data. The shapelet transform is a unique time series representation based solely on the shape of the time series data. Considering the individual characteristics unique to every anomaly, the application of this transform yields a new shape-based feature representation that can be combined with any standard machine learning algorithm to detect anomalous data with no manual intervention. For the present study, the anomaly detection framework consists of three steps: identifying unique shapes from anomalous data, using these shapes to transform the SHM data into a local-shape space and training machine learning algorithms on this transformed data to identify anomalies. The efficacy of this method is demonstrated by the identification of anomalies in acceleration data from an SHM system installed on a long-span bridge in China. The results show that multiple data anomalies in SHM data can be automatically detected with high accuracy using the proposed method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.3
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• pp.11-17
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• 2007

RWe have developed an infrared temperature monitoring system to measure the temperature of hot iron plate in very harsh environmental conditions as iron making equipment. We performed extensive field test for 3 months at the front side of iron plate rolling process of POSCO in Gwang-Yang. From the experimental test, we have confirmed the reliability of the developed system. We adjust the curve fit method to solve the non-linearity equations of A2TPMI sensor, and establish the under $1[^{\circ}C]$precision ratio and 25[msec] process speed each range. As experimental, we have confirmed the reliability of an infrared temperature monitoring system as POSCO test result and CAN network traffic monitoring of polling method.

• Nuclear Engineering and Technology
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• v.37 no.4
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• pp.395-400
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• 2005

An environmental radon monitoring system, comprising a radon-cup, an etching system, and a track counting system, was constructed. The radon cup is a cylindrical chamber with a radius of 2.2 cm and a height of 3.2 cm in combination with a CR-39 detector. Carbon is impregnated in the bodies of the detector chamber to avoid problem of an electrostatic charge. The optimized etching condition for the CR-39 exposed to a radon environment turned out to be a 6 N NaOH solution at 70^{\circ}$ over a 7hour period. The bulk etch rate under the optimized condition was $1.14{\pm}0.03\;{\mu}m\;h^{-1}$. The diameter of the tracks caused by radon and its progeny were found to be in the range of $10\~25\;{\mu}m$ under the optimized condition. The track images were observed with a track counting system, which consisted of an optical microscope, a color charged couple device (CCD) camera, and an image processor. The calibration factor of this system is obtained to be $0.105{\pm}0.006$ tracks $cm^2$ per Bq $m^{-3}$ d.