• Journal of Korean Society of Water and Wastewater
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• v.19 no.6
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• pp.738-748
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• 2005

Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.1-17
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• 2015

A river water level monitoring system which prevents salt water damages and effectively excludes floods has been developed to contribute efficient operation of Nakdong river estuary barrage. The system can be used for monitoring upstream conditions more quickly and do appropriate responses over changes. Telemetry and telecontrols using PLCs have been built at the three sites that directly influence on the operation of barrage gates, and are linked to Nakdong river estuary barrage's IOS (Integrated Operation System) through public communication networks. By using PLC, the system can achieve even higher reliability and versatility than before as well as easy management. By power control devices, we can remotely control the power of PLCs to treat the minor troubles instantly without going on-sites. The power control devices also save data in preparation for the cases of communication failures. The system uses ADSL (FTTH) as a main network between SCADA server and PLCs, and CDMA (M2M) as a secondary network. In order to compensate security vulnerabilities of public communication network, we have installed the VPNs for secure communication between center and the observation stations, just like a dedicated network. Generally, river water level observations have been used custom-manufactured remote terminals to suit their special goals. However, in this case, we have established a system with open architecture considering the interface between different systems, the ease of use and maintenance, security, price, etc.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.28-38
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• 2009

In this study, a remote air quality monitoring system for underground spaces was developed by using NDIR-based CO$_2$ sensor. And the remote monitoring system based on wireless sensor networks was installed practically on the subway station platform. More than 6.5 million citizens commutate everyday by the Seoul subway transportation that is the most typical public transportation. They concern about air quality with increasing interest on public health or many workers in subway stations or underground shopping centers. Recently, the Korean Ministry of Environment has operated the air quality monitoring system in some subway stations for testing phase. However, it showed many defects which are large-scale, high-cost and maintenance of precision sensors imported from abroad. Therefore this research includes the reliability test and a theoretical study about the inexpensive commercialized CO$_2$ sensor for reliable measurement of air quality which changes rapidly by the surrounding environments. And then we develop the wireless sensor nodes and the gateway applied for remote air quality monitoring. In addition, web server program was realized to manage air quality in the subway platform. This result will be valuable for a basic research for air quality management in underground spaces for future study.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.588-590
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• 2022

Sharing both locations and positions of ships makes it possible to utilize critical item for their safe and efficient navigation in such diversifying meantime environments. AIS is the representative technology for the sharing solutions. The AIS is even used in airspace and ground stations, so that AIS could facilitate the ships' safety navigation and their prevention/rescue from endangers. Due to AIS's many advantages, IMO(International Maritime Organization) made adapting the AIS mandatory for international passenger ships and the ships that are over than 300 tons. AIS uses VHF band areas for transmitting information and the information can be propagated to several hundreds km in range. Due to the large range, AIS monitoring system can acquire huge number of ships, which makes system performance lower and busier. In this paper, we propose the strategy of AIS information extraction for efficient monitoring system. Thus, the monitoring system has higher processing performance and lower network usage. As well as, the proposal affects the monitoring system has more capacity to include other systems' targets, in result.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1208-1215
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• 2017

Recently, people's attention and worries about fine particulate matter have been increasing. Due to the construction and maintenance costs, there are insufficient air quality monitoring stations. As a result, people have limited information about the concentration of fine particulate matter, depending on the location. Studies have been undertaken to estimate the fine particle concentrations in areas without a measurement station. Yet there are limitations in that the estimate cannot take account of other factors that affect the concentration of fine particle. In order to solve these problems, we propose a framework for estimating the concentration of fine particulate matter of a specific area using meteorological data and traffic data. Since there are more grids without a monitor station than grids with a monitor station, we used a domain adversarial neural network based on the domain adaptation method. The features extracted from meteorological data and traffic data are learned in the network, and the air quality index of the corresponding area is then predicted by the generated model. Experimental results demonstrate that the proposed method performs better as the number of source data increases than the method using conditional random fields.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.780-786
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• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.

• Spatial Information Research
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• v.18 no.5
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• pp.1-11
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• 2010

Since January 2009, Seoul Metro Government(SMG) is operating own Network RTK Systems connecting four(4) GNSS Reference Stations which are installed inside Seoul Metro City area. SMG is currently providing VRS data service via wireless internet for Network-RTK and RINEX data observed from GNSS Reference Stations. This paper will discuss utilization of data available from SMG Network-RTK System for various applications, and present the test results on practicalities of Virtual RINEX data. For the utilization of data available from SMG Network- RTK system, 1)NTRIP data delivery of GNSS realtime observables streaming and converting to RINEX at receiving side, 2) monitoring deformation of bulky structures using GNSS observation were discussed. In addition to those discussion, 3) broadcasting VRS correction data for job site via radio modem after acquiring such correction data on-line using NTRIP based GNSS Internet Radio from SMG Network-RTK System were introduced. For the test results on practicalities of Virtual RINEX data, 1) the post-processing results of the GNSS observation data on a certain point with GNSS Reference Station data have been compared to the post-processing results of Virtual RINEX data on the same point generated from SMG Network-RTK System, and 2) VRS RTK positioning results for a certain point and post-processing results of Virtual RINEX data for the point were compared. The results showed only a few mm difference, and the high possibility for using Virtual RINEX data for post-processing applications.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.507-514
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• 2015

The Spatial information research institute of the LX Korea land and geospatial informatix corporation manages infrastructure for the LX global navigation satellite system (GNSS), which comprises 30 monitoring stations nationwide. Since 2014, it has conducted network real-time kinematic (RTK) tests using the master-auxiliary concept (MAC). This study introduces the infrastructure of LX GNSS and presents the results of a performance analysis of the LX RTK service. The analysis was based on a total of 25 cadastral topographic control points in Jeonju, Seoul, and Incheon. For each point, performance was measured over one observation, two repeated observations, and five repeated observations. The measurements obtained from LX MAC and the VRS of the National Geographic Information Institute were compared with the announced coordinates derived from cadastral topographic control points. As a result, the two systems were found to have similar performance with average error and standard deviation differing only by 1 to 2 cm.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.6
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• pp.791-804
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• 2011

Numerical simulations were carried out to investigate the impact of PBL (Planetary boundary layer) scheme implemented in WRF on the result of meteorological fields and CMAQ modeling. 25-day period, representing high ozone concentration, was selected for the simulations. The three WRF domains covered East Asia region, Korean Peninsula and Seoul metropolitan area. The sensitivity of WRF-CMAQ modeling to the various PBL schemes was assessed and quantified by comparing model output and against observation from the meteorological and the air quality monitoring network within the domain. The meteorological variables evaluated included temperature, wind speed and direction over surface sites and upper air sounding sites. The CMAQ variables included gaseous species $O_3$ and $NO_x$ over monitoring stations. Although difference of PBL schemes implemented in WRF, they did not appreciably affect the WRF and CMAQ performance. There are partially differences between non-local and local mixing scheme, but are not distinct differences for the results of weather and air quality. It is suggested that impact of parameterization of vertical eddy diffusivity scheme in CMAQ also need to be researched in the future study.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.159-159
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• 2023

The Amazon River basin is one of the largest basins in the world, and its ecosystem is vital for biodiversity, hydrology, and climate regulation. Thus, understanding the hydrometeorological process is essential to the maintenance of the Amazon River basin. However, it is still tricky to monitor the Amazon River basin because of its size and the low density of the monitoring gauge network. To solve those issues, remote sensing products have been largely used. Yet, those products have some limitations. Therefore, this study aims to do bias corrections to improve the accuracy of Satellite Precipitation Products (SPPs) in the Amazon River basin. We use 331 rainfall stations for the observed data and two daily satellite precipitation gridded datasets (CHIRPS, TRMM). Due to the limitation of the observed data, the period of analysis was set from 1st January 1990 to 31st December 2010. The observed data were interpolated to have the same resolution as the SPPs data using the IDW method. For bias correction, we use convolution neural networks (CNN) combined with an autoencoder architecture (ConvAE). To evaluate the bias correction performance, we used some statistical indicators such as NSE, RMSE, and MAD. Hence, those results can increase the quality of precipitation data in the Amazon River basin, improving its monitoring and management.