• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.235-240
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• 2006

The paper will give an overview of the mission of GalTeC and then concentrate on two main aspects. The first more detailed aspect, is the analysis of the key performance parameters for the Galileo system services and presenting a technical overview of methods and algorithms used. The second more detailed aspect, is the service volume prediction including service dimensioning using the Prediction tool. In order to monitor and validate the Galileo SIS performance for Open Service (OS) and Safety Of Life services (SOL) regarding the key performance parameters, different analyses in the SIS domain and User domain are considered. In the SIS domain, the validation of Signal-in-Space Accuracy SISA and Signal-in-Space Monitoring Accuracy SISMA is performed. For this purpose first of all an independent OD&TS and Integrity determination and processing software is developed to generate the key reference performance parameters named as SISRE (Signal In Space Reference Errors) and related over-bounding statistical information SISRA (Signal In Space Reference Accuracy) based on raw measurements from independent sites (e.g. IGS), Galileo Ground Sensor Stations (GSS) or an own regional monitoring network. Secondly, the differences of orbits and satellite clock corrections between Galileo broadcast ephemeris and the precise reference ephemeris generated by GalTeC will also be compared to check the SIS accuracy. Thirdly, in the user domain, SIS based navigation solution PVT on reference sites using Galileo broadcast ephemeris and the precise ephemeris generated by GalTeC are also used to check key performance parameters. In order to demonstrate the GalTeC performance and the methods mentioned above, the paper presents an initial test result using GPS raw data and GPS broadcast ephemeris. In the tests, some Galileo typical performance parameters are used for GPS system. For example, the maximum URA for one day for one GPS satellite from GPS broadcast ephemeris is used as substitution of SISA to check GPS ephemeris accuracy. Using GalTeC OD&TS and GPS raw data from IGS reference sites, a 10 cm-level of precise orbit determination can be reached. Based on these precise GPS orbits from GalTeC, monitoring and validation of GPS performance can be achieved with a high confidence level. It can be concluded that one of the GalTeC missions is to provide the capability to assess Galileo and general GNSS performance and prediction methods based on a regional and global monitoring networks. Some capability, of which first results are shown in the paper, will be demonstrated further during the planned Galileo IOV phase, the Full Galileo constellation phase and for the different services particularly the Open Services and the Safety Of Life services based on the Galileo Integrity concept.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.6
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• pp.666-682
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• 2010

The forecasting system for Today's and Tomorrow's PM10 was developed based on the statistical model and the forecasting was performed at 9 AM to predict Today's 24 hour average PM10 concentration and at 5 PM to predict Tomorrow's 24 hour average PM10. The Today's forecasting model was operated based on measured air quality and meteorological data while Tomorrow's model was run by monitored data as well as the meteorological data calculated from the weather forecasting model such as MM5 (Mesoscale Meteorological Model version 5). The observed air quality data at ambient air quality monitoring stations as well as measured and forecasted meteorological data were reviewed to find the relationship with target PM10 concentrations by the regression analysis. The PM concentration, wind speed, precipitation rate, mixing height and dew-point deficit temperature were major variables to determine the level of PM10 and the wind direction at 500 hpa height was also a good indicator to identify the influence of long-range transport from other countries. The neural network, regression model, and decision tree method were used as the forecasting models to predict the class of a comprehensive air quality index and the final forecasting index was determined by the most frequent index among the three model's predicted indexes. The accuracy, false alarm rate, and probability of detection in Tomorrow's model were 72.4%, 0.0%, and 42.9% while those in Today's model were 80.8%, 12.5%, and 77.8%, respectively. The statistical model had the limitation to predict the rapid changing PM10 concentration by long-range transport from the outside of Korea and in this case the chemical transport model would be an alternative method.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.95-104
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• 2020

In this paper, we propose the real time indoor air quality monitoring and controlling platform on cloud using IoT sensor data such as PM10, PM2.5, CO2, VOCs, temperature, and humidity which has direct or indirect impact to indoor air quality. The system is connected to air ventilator to manage and optimize the indoor air quality. The proposed system has three main parts; First, IoT data collection service to measure, and collect indoor air quality in real time from IoT sensor network, Second, Big data processing pipeline to process and store the collected data on cloud platform and Finally, Big data analysis and visualization service to give real time insight of indoor air quality on mobile and web application. For the implication of the proposed system, IoT sensor kits are installed on three different public day care center where the indoor pollution can cause serious impact to the health and education of growing kids. Analyzed results are visualized on mobile and web application. The impact of ventilation system to indoor air quality is tested statistically and the result shows the proper optimization of indoor air quality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.807-810
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• 2011

The sensor network technology for core technology of ubiquitous computing is in the spotlight recently, the research on sensor network is proceeding actively which is composed many different sensor node. USN(Ubiquitous Sensor Network) is the network that widely applies for life of human being. It works out to sense, storage, process, deliver every kind of appliances and environmental information from the stucktags and sensors. And it is possible to utilize to measure and monitor about the place of environmental pollution which is difficult for human to install. It's studied constantly since it be able to compose easily more subminiature, low-power, low-cost than previous one. And also it spotlights an important field of study, graft the green IT and IT of which the environment and IT unite stragically onto the Network. The problem for the air pollution in the office or the indoor except a specific working area is the continuously issue since the human beings have lived in the dwelling facilities. Measures for that problem are urgently needed. It's possible to solve for the freshair of outside with enough ventilation but that is the awkward situation to be managed by person. This study is the system engineering to management for indoor air condition under the sensor network. And research for efficiently manage an option.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.6
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• pp.575-582
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• 2016

Seoul city has high population density as well as high traffic congestion, which are vulnerable to exposure of environmental pollutions caused by car traffic. However, recent studies are only on local regions about road traffic and air pollution or health effect of road traffic on residents. Thus, comprehensive study data are needed in terms of overall Seoul regions. In this study utilized the nitrogen dioxide concentration through the national air pollution monitoring network data, 2012 to 2013. It also divided regions into high and low exposure districts via the Origin destination data developed by the Korea transport institute to quantify and evaluate the effect of transport policies and analyzed a correlation of asthma symptoms with high and low exposure districts through raw data of community health survey from the Korea centers for disease control and prevention. Based on the collected data, the pearson's correlation analysis was conducted between air pollution substance concentration and high exposure district and multiple logistic regression analysis was conducted to determine the effect of traffic environment and factors on asthma symptoms of residents. Accordingly, the following results were derived. First, the high exposure district was higher concentrations of nitrogen dioxide ($NO_2$) as per time compared to those of the low exposure district (p<0.01). Second, analysis on correlation between average daily environmental concentration in the air pollution monitoring network and road traffic showed that nitrogen dioxide had a significant positive correlation (p<0.01) with car traffic and total traffic as well as with truck traffic (p<0.05) statistically. Third, an adjusted odds ratio about asthma doctor's diagnosis in the high and low exposure districts was analyzed through the logistic regression analysis. With regard to an adjusted model 2 (adjusted gender, age, health behavior characteristics, and demographic characteristics) odds ratio of asthma doctor's diagnosis in the high exposure district was 1.624 (95% CI: 1.269~2.077) compared to that of the low exposure district, which was significant statistically (p<0.001).

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.485-486
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• 2007

Wireless Sensor Networking is state of the art technology that has a wide range of potential applications. Sensor network generally consists of a large number of distributed nodes that organize themselves into a multi-hop wireless network. Each node has one or more sensors, embedded processors and low-power radios, and is normally battery operated because of small size. In this paper wireless sensor networking technology applies to the environment monitoring system in the underground. This system can monitor a pollution level of the underground in realtime for keeping up a comfortable environment.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.117-127
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• 2024

Purpose: The purpose is to conduct basic research to save energy and improve the safety of manufacturing plant infrastructure by comprehensively monitoring energy management, temperature, humidity, dust and gas, air quality, and machine operation status in small and medium-sized manufacturing plants. Method: To this end, energy-related data and environmental information were collected in real time through digital power meters and IoT sensors, and research was conducted to disseminate and respond to situations for energy saving through monitoring and analysis based on the collected information. Result: We presented an application plan that takes into account energy management, cost reduction, and safety improvement, which are key indicators of ESG management activities. Conclusion: This study utilized various sensor devices and related devices in a smart factory as a practical case study in a company. Based on the information collected through research, a basic system for energy saving and safety improvement was presented.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.73-78
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• 2003

In this research, we implement Realtime Air Diffusion Prediction System which is a parallel Fortran model running on distributed-memory parallel computers. The system is designed for air diffusion simulations with four-dimensional data assimilation. For regional air quality forecasting a series of dynamic downscaling technique is adopted using the NCAR/Penn. State MM5 model which is an atmospheric model. The realtime initial data have been provided daily from the KMA (Korean Meteorological Administration) global spectral model output. It takes huge resources of computation to get 24 hour air quality forecast with this four step dynamic downscaling (27km, 9km, 3km, and lkm). Parallel implementation of the realtime system is imperative to achieve increased throughput since the realtime system have to be performed which correct timing behavior and the sequential code requires a large amount of CPU time for typical simulations. The parallel system uses MPI (Message Passing Interface), a standard library to support high-level routines for message passing. We validate the parallel model by comparing it with the sequential model. For realtime running, we implement a cluster computer which is a distributed-memory parallel computer that links high-performance PCs with high-speed interconnection networks. We use 32 2-CPU nodes and a Myrinet network for the cluster. Since cluster computers more cost effective than conventional distributed parallel computers, we can build a dedicated realtime computer. The system also includes web based Gill (Graphic User Interface) for convenient system management and performance monitoring so that end-users can restart the system easily when the system faults. Performance of the parallel model is analyzed by comparing its execution time with the sequential model, and by calculating communication overhead and load imbalance, which are common problems in parallel processing. Performance analysis is carried out on our cluster which has 32 2-CPU nodes.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.7
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• pp.414-420
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• 2003

The domestic needs for larger capability of power sources are increasing to cope with the expanding power load which results from the industrial developments & the progressed life style. In summer, the peak load is mainly due to the non-industrial reasons such as air-conditioners and other cooling equipments. To cover the concentrated peak load in stable, the power transmission lines should be more constructed and efficiently operated. The ampacity design of the underground cable system is generally following international standards such as IEC287, IEC60853 and JCS168 which regards the shape of 100% daily full power loads. It is not so efficient to neglect the real shapes of load curves generally below 60~70% of full load. The dynamic (real time) rating system tends to be used with the measured thermal parameters which make it possible to calculate the maximum ampacity within required periods. In this paper, the CTM(Conductor Temperature Monitoring) which is the base of dynamic rating systems for tunnel environment is proposed by a design of lumped thermal network ($\pi$-type thermal model) and distribution temperature sensor attached configuration, including the estimation results of its performances by load cycle test on 345kV single phase XLPE cable.

• Proceedings of the Korean Environmental Health Society Conference
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• 2002.04a
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• pp.69-73
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• 2002

There have been few reports on the survey of pathological findings of cetaceans stranded on the coast of Japan. This is partly because of lack of the procedures and/or network of systemic sampling of fresh tissues for the pathological study of stranded marine mammals. In contrast, there are a numbers of reports on the cause of illness and death in wild, free-living cetaceans examined in other countries; the commonest cause of death was parasitic and bacterial pneumonia except for entanglement in fishing gear. Anthracosis, lung and hilar lymph nodes polluted by suspended particulate matter in the air, has been recently found in some cetaceans stranded on the coast of Japan. In addition to the data from the chemical analysis of tissues, scientific data obtained from pathological study of stranded marine mammals would be also one of the useful base for the assessment of global environment. Usefulness of metallothionein in the hepatopancreas of crabs as a biomarker of marine pollution monitoring was also discussed in this study.