• Journal of Wetlands Research
• /
• v.24 no.1
• /
• pp.38-43
• /
• 2022

Smart sewage treatment plant means creating a safe and clean water environment by establishing an ICT-based real-time monitoring, remote control management and intelligent system for the entire sewage treatment process. The core technology of such a smart sewage treatment plant can be operation control technology using measuring instruments. This research team analyzed and suggested the operation control technologies necessary for the establishment of the intelligent business by referring to the intelligent research projects of the sewage treatment plant in progress in Korea. As a result of the analysis, a total of six removal technologies were presented, including control by scale, reflow water control, linked treated water control, chemical quantity control, winter operation control, and total organic carbon control. By size, standards that can be classified into small and medium-sized large-scale are presented, and in the case of reflow water control, the location of water quality and flow sensors capable of managing reflow water is suggested. In the case of the linked treated water control, the influence and control points of the linked treated water on the sewage treatment plant were presented, and in the case of the chemical injection volume control, a system capable of optimizing the amount of chemical injection according to the introduction of an intelligent sewage treatment plant was presented. In the case of winter operation, the sensors and pumps to be controlled are suggested when considering the decrease in nitrification due to the decrease in water temperature. In the case of total organic carbon control, an interlocking system considering the total amount of pollution in the future was proposed. These operation control scenarios are expected to be used as basic data to be used in intelligent sewage treatment algorithms and scenarios in the future.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2002.05a
• /
• pp.43-50
• /
• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Korean Journal of Food Science and Technology
• /
• v.49 no.2
• /
• pp.123-131
• /
• 2017

Norovirus causes frequent epidemic viral gastroenteritis in Korea. The team for the control of noroviral foodborne outbreaks (NOROTECL) executed a project to trace the cause of norovirus contamination in agricultural products and environmental samples to reduce norovirus outbreaks in Korea. Between January and November in 2015, the contaminations by norovirus and indicator microorganisms such as coliforms, Escherichia coil and male specific coliphage (MSC) were examined in 80 agricultural products, 80 soil samples, 78 human feces samples, 3 animal feces samples, 80 agricultural water samples and 80 river water samples. Semi-nested PCR and DNA sequencing revealed 18 genogroup I and 3 genogroup II noroviruses in a total of 18 samples. These noroviruses were validated by real-time (RT)-PCR analysis. For indicator microorganisms, coliform and E. coli were respectively detected in agricultural products (68, 1%), soils (88, 7%), human feces (44, 12.8%), animal feces (67, 67%), agricultural waters (74, 30%) and river waters (96, 51%). The MSC results revealed 14 positive samples.

• Journal of the Korean Geotechnical Society
• /
• v.30 no.10
• /
• pp.19-31
• /
• 2014

In order to investigate ground state change visually in physical model during centrifuge testing, electrical resistivity survey was adopted. Commercial resistivity survey equipment verified at various in-situ sites was utilized. The resistivity survey equipment installed in centrifuge facility was remotely controlled through intranet and electrical resistivity images obtained while centrifuge testing was being checked by real-time inversion. To verify the stable operation of the developed resistivity survey system, preliminary tests were conducted. Model ground was uniformly constructed using unsaturated soil and saline water was dropped on the ground surface to simulate contaminant flow situation. During the 10 g centrifuge tests, electrical resistivity was continuously detected and the testing results were compared with those of identically carried out 1 g centrifuge tests. In addition, the electrical resistivity was directly measured immediately after the centrifuge test by open cutting the model. Finally, reliability of electrical resistivity survey in the centrifuge test was verified by comparing those testing results.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.05b
• /
• pp.801-805
• /
• 2005

수자원의 이수 및 치수관리에 있어서 우량, 하천수위. 하천유속, 하천유량, 지하수위, 하수유량 등의 수문자료는 가장 기초적이면서 중요한 요소이다. 그럼에도 불구하고 최근까지 우리나라의 수자원관리 실태를 살펴보면 신뢰성 있는 수문자료의 구축이 매우 미비한 실정이며, 이로 인해 하천유역의 수문특성 해석에 많은 어려움을 겪고 있다. 본 논문에서는 21세기 프론티어연구사업과 관련하여 구축$\cdot$시범운영하고 있는 "안양천 실시간 통합 수문모니터링 시스템"의 운영현황을 소개하고 2단계 사업에서 신규의 구축된 하수근거 모니터링 시스템에 대해 소개하고자 한다. 실시간 통합 수문 모니터링 시스템이란 하천유역내의 강우량, 하천수위, 지하수위, 하수근거유량, 수질 등 수문 상황을 실시간으로 모니터링함으로써 유역내의 수문자료를 구축함은 물론 지하수위와 하천수위와의 연관성, 하천유량 증가의 인한 하수근거로의 우수유입량 등의 분석을 통해 유역 전반에 걸친 물순환체계에 대한 해석과 평가를 내릴 수 있도록 지원하는 시스템이다. 이를 위해 주요 지점에 수문 모니터링 장비를 설치하고, 통신모듈을 통해 현장에서 서버로 모니터링 자료를 실시간으로 전송하고, 전송된 자료를 웹상에서 보여줌으로써 유역관리자의 의사결정지원 자료로 활용할 뿐만 아니라 일반인들에게 거주지역내 하천에 대한 정보를 제공할 수 있게 된다. 또한 안양시청을 시범 행정기관으로 선정하여 안양시에서 운영하고 있는 실시간 수문모니터링 자료를 취합하여 웹상에서 공유할 수 있도록 시스템을 통합하는 방안을 마련하였으며, 향후 안양천에 속해 있는 지자체이 참여를 유도할 예정이다. 안양천 실시간 모니터링 시스템은 안양천 웹페이지(http://anyang.river.or.kr)에서 구현되고 있으며, 앞서 설명한 바와 같이 1단계 프론티어 사업으로 설치된 4개의 하천수위, 2개의 지하수위 관측시설과 함께, 2단계에 (주)웹솔루스에서 자체적으로 설치 운영하고 있는 2개소의 하수관거 모니터링 관측시설, 그리고 안양시에서 운영하고 있는 5개소의 강우관측소와 7개소의 수위관측소를 모두 통합하여 실시간 자료를 제공하고 있다. 수위자료는 10분단위의 텍스트정보와 그래프형태로 지원되며, 검색기간 설정을 통해 원하는 기간내의 자료를 선별, 검색할 수 있다.

• Journal of Korean Society of Environmental Engineers
• /
• v.39 no.8
• /
• pp.441-448
• /
• 2017

A method for measuring the concentration of surfactant in water was developed. In this technique, microbubbles were used as light scatterers. The polarization change of light scattered by microbubbles was analyzed by Mueller matrix analysis. $M_{11}$, one of the Mueller matrix elements, was found to be a key parameter inferring the surfactant concentration within the concentration range of 0 ppm to 60 ppm. The best results for this measurement were obtained when the scattering angle was $150^{\circ}$ and the extinction ratio was 56.2. This experimental result shows that the EPLS can be effectively used as a real time inspection method for water quality monitoring in lakes or rivers.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.1
• /
• pp.145-151
• /
• 2017

In this paper, we propose the design and implementation of the system that is predicting the failure of ballast water treatment system by analysing its sensor datum and is reserving the most effective service center for sellecting the repair location on the way to the destination port. These data are collected in real time during draining or filling up the sea water from/to the ship, and it is essential to preliminarily repair the equipment showing unstable characteristics by analyzing the normal and abnormal data characteristics. We proposed a software platform for predicting and repairing faults by selecting the most efficient repair center based on this e-Navigation while the vessel is navigating to the next destination port. This system, as announced by the IMO Convention for the Prevention of Marine Pollution in 2017, provides a stable economic impact from stable cargo operation and stable out/in from/to port and marine ecosystem.

• Journal of Digital Convergence
• /
• v.10 no.11
• /
• pp.351-358
• /
• 2012

This study is aimed at suggesting optical communication equipment that can deliver high quality video information in high speed, to efficiently handle the flood and water pollution in the river basin. This system is cheaper than existing equipment, and can monitor optical Internet as well as the condition of equipment. Generally, the communication equipment to prevent flood is installed in an unmanned control box and operated by the flood control office situated at the fiver mouth in a long distance section. Therefore, it is hard to promptly cope with communication interruptions, which occur by the cutting or aging of the optical cable. Under the circumstances, this study suggested an efficient system that can deliver high quality video information in high speed (Optical Transmission Convert System) by using optical fiber. The system also solves problems by making use of automatic protection switching (APS) when an accident happens. Its real-time monitoring function gives notice of the problem-occurring points. The system is expected to be widely used in various areas such as intelligent traffic systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.1
• /
• pp.139-143
• /
• 2019

Measurement of flow rate is required in various fields. Water meters are often used at home, and flow meters are used in water and sewage plants, petrochemical industries and so on.. A system is needed to monitor the flow rate in real time and notify immediately when flow rate is abnormal. Recently, with the development of the IoT it is possible to construct such devices at low cost. WeMos can be programmed with Arduino IDE as a mini wifii IoT module. The flow sensor can output a digital pulse proportional to the flow rate. In this paper, we developed the flow monitoring and warning system using WeMos and IoT technology. When the system operates, it calculates the flow rate, sends the value as JSON format to the server, monitors the flow rate as graph from the remote with the smartphone. We also implement the system to promptly send alert message to the smart phone using Pushbullet when the flow rate is abnormal.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.315-315
• /
• 2023

급격한 기후변화에 기인하여 전 세계적으로 거듭되는 돌발홍수로 인한 피해가 급격히 증가하고 있는 실정이다. 우리나라에서도 최근 중소 규모의 하천 뿐 아니라 도시 생활하천, 도심지 저지대에서 갑작스런 홍수와 침수로 인해 많은 인명과 재산 피해를 경험하고 있다. 이런 문제를 인식하여 최근 정부차원에서 다양한 센서와 인공지능에 기반하는 많은 인프라 및 연구 투자가 이루어지고 있지만, 높은 설치 및 운영 비용과 우리나라의 복잡한 하천 환경 특성으로 인해 소하천이나 도심지 저지대에서는 그 효율성을 제대로 발휘하지 못하고 있다. 따라서 본 논문에서는 주변환경의 변화에 강인한 복합 센서단말을 통해, 하천 정보(유량, 유속, 수위 등)을 실시간 측정하고, 해당지역의 특성을 고려한 하천 또는 저지대의 위험도를 스스로 판단할 수 있는 기술을 제안한다. 또한, 본 논문에서는 제안한 저비용 초소형의 단말 장치로 지점의 하천 정보를 실시간 측정하여 IoT망을 통해 3차원 하천 디지털트윈 모델로 전달하여, 유속과 수위를 그대로 재연함으로써, 하천 침수 위험 감시의 효율성을 검증하였다. 3차원 DEM(Digital Elevation Models) 데이터와 실제 하천을 관측한 데이터를 이용한 디지털트윈 검증 결과, 데이터 전송 지연시간을 감안하여 3초 이내에 하천의 수위와 유속이 3차원 모델에 반영되는 것을 확인하였다. 이 결과로부터 열악한 환경에서도 실시간 하천 상황을 원거리에서 모니터링 할 수 있으며, 강우와 유출에 따른 하천 홍수 메카니즘을 새롭게 시뮬레이션할 수 있는 방법론을 제시할 수 있을 것으로 기대한다.