• International Journal of Advanced Culture Technology
• /
• 제5권1호
• /
• pp.64-69
• /
• 2017

The rapid growth of algae occurs can induce the algae bloom when nutrients are supplied from anthropogenic sources such as fertilizer, animal waste or sewage in runoff the water currents or upwelling naturally. The algae blooms creates the human health problem in the environment as well as in the water resource managers including hypoxic dead zones and harmful toxins and pose challenges to water treatment systems. The algal blooms in the source water in water treatment systems affects the drinking water taste & odor while clogging or damaging filtration systems and putting a strain on the systems designed to remove algal toxins from the source water. This paper propose the emerging In-Situ self-diagnosable smart algae sensing device with wireless connectivity for smart remote monitoring and control. In this research, we developed the In-Site Algae diagnosable sensing device with wireless sensor network (WSN) connectivity with Optical Biological Sensor and environmental sensor to monitor the water treatment systems. The proposed system emulated in real-time on the water treatment plant and functional evaluation parameters are presented as part of the conceptual proof to the proposed research.

• 한국가시화정보학회지
• /
• 제19권2호
• /
• pp.41-47
• /
• 2021

River and stream are the important water supply source in our lives. Eutrophication causes excessive green algae growth including microcystis, which makes harmful to ecosystem and human health. Therefore, the water purification process to remove green algae is essential. In Korea, green algae alarm system exists depending on the concentration of green algae cells in river or stream. To maintain the growth amount under control, green algae monitoring system is being used. However, the unmanned, small and automatic monitoring system would be preferable. In this study, we developed the 3D printed device to measure the concentration of green algae cell using microfluidic droplet generator and deep learning. Deep learning network was trained by using transfer learning through pre-trained deep learning network. This newly developed microfluidic cell counter has sufficient accuracy to be possibly applicable to green algae alarm system.

• 한국수자원학회논문집
• /
• 제55권4호
• /
• pp.301-308
• /
• 2022

조류는 수생태계에서 소비자의 에너지를 공급하여 생태계 내 없어서는 안 될 1차 생산자로서 크게 녹조류, 남조류, 규조류로 나뉘어진다. 남조류의 경우 수온이 상승하여 여름철 발생하여 과대 증식하여 녹조현상의 주원인이 되며, 최근 기후 변화로 인해 녹조현상의 발생시기의 변화와 빈도수가 늘고 있는 추세이다. 기존의 조류 조사 방식은 채수 및 센서를 통한 측정으로 이루어지고 있으며 시간, 비용 및 인력의 한계가 나타난다. 이러한 기존 모니터링 방법의 한계를 극복 하기위해 위성영상이나 무인항공기(Unmanned Aearial Vehicles, UAV), 등 탑제체를 운용한 다중분광 및 초분광과 같은 분광기기를 이용하여 원격 모니터링을 수행하는 연구가 진행되어 왔다. 본 연구에서는 조류 배양액 및 하천수 채수를 통한 실험실 규모의 실험을 통해 원격 모니터링의 종 구분에 대한 가능성에 대하여 확인 해보고자 하였다. 초분광 영상을 취득하기 위해 400-1000 nm에서 분석할 수 있는 초분광 센서를 활용하였다. 채수한 하천수의 조류 종 구분을 위한 분광특성을 추출하기 위해 GF/C필터를 이용하여 여과를 진행하여 시료를 제조하여 영상을 수집하였다. 수집된 영상을 방사보정 및 Base (하천수 및 배양보존액 통칭) 제거를 진행하였고 조류의 분광 정보 추출 과정을 통해 시료별 분광 정보를 추출, 분석하여 조류의 분광특성을 파악, 비교분석하여 하천·호소에서의 초분광영상 기반 원격탐사 모니터링의 적용성을 검토하고자 하였다.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2007년도 춘계학술대회B
• /
• pp.3122-3127
• /
• 2007

Water resource can be examined using biological sensors. Algae has been one of the biological sensors used to evaluate and monitor the water pollution. The monitoring system, however, could determine whether the examined water was safe or not. It needs additional expensive chemical test to figure out the cause of the water pollution. In this study, an endeavor is given to identify the toxicant in the water using the shape of the chlorophyll fluorescence induction curve(FIC) from algae using monitoring system. Fundamental curves are obtained from the experiments with specified amount of toxicant. Baysian method is utilized to determine the unknown toxicant in the water by comparing it with the fundamental curves. The results shows that the proposed method works fairly well.

• 상하수도학회지
• /
• 제22권1호
• /
• pp.73-78
• /
• 2008

Water resource can be examined using biological sensors. Algae has been one of the biological sensors used to evaluate and to monitor the water pollution. The monitoring system, however, has not been used to determine what kind of the toxicological substance is in the water. It needs additional expensive chemical test to figure out the cause of the water pollution. In this study, an endeavor is made to identify the toxicant in the water using the shape of the chlorophyll fluorescence induction curve(FIC) from algae using monitoring system. Fundamental curves are obtained from the experiments with specified amount of toxicant. Baysian method is utilized to determine the unknown toxicant in the water by comparing it with the fundamental curves. The results shows that the proposed method works fairly well.

• 상하수도학회지
• /
• 제31권3호
• /
• pp.197-204
• /
• 2017

This study was carried out to apply the UAV(Unmanned Aerial Vehicle) coupled with Multispectral sensor for the algae bloom monitoring in river. The study acquired remote sensing data using UAV on the midstream area of Gum River, one of four major rivers in South Korea. Normalized difference vegetation index (NDVI) is used for monitoring algae change. This study conducted water sampling and analysis in the field for correlating with NDVI values. Among the samples analyzed, the chlorophyll concentration exhibited strong and significant linear relationships with NDVI, and thus NDVI was chosen for algae bloom index to identify emergence aspect of phytoplankton in river. Aerial remote sensing technology can provide more accurate, flexible, cheaper, and faster monitoring methods of detecting and predicting eutrophication and therefore cyanobacteria bloom in water reservoirs compared to currently used technology. As a result, there was high level of correlation in chlorophyll-a and NDVI. It is expected that when this remote water quality and pollution monitoring technology is applied in the field, it would be able to improve capabilities to deal with the river water quality and pollution at the early stage.

• ALGAE
• /
• 제22권1호
• /
• pp.37-44
• /
• 2007

In order to understand the impact of the heavy-oil pollution by the 1997 Nakhodka oil spill on the intertidal macroalgal vegetation, we have been monitoring succession in the intertidal flora since 1997 at Oh-ura, Takno, and Imago-Ura Cove, Kasumi in Hyogo Prefecture, northwestern coast of Honshu, Japan. We employed two different monitoring methods: 1) The percent cover of macro-algae (seaweeds) in 1 x 1 m quadrats along 450 m intertidal transects parallel to the shoreline were assessed and recorded by photographic imaging until 2002, and for 30-40 m transects of the most heavily polluted areas in 2004 and 2006; 2) The percent cover of macro-algae in 0.5 x 0.5 m quadrats along a transect line perpendicular to the shore were recorded and all macrophytes within the quadrat were completely removed to record the wet weight of each taxon (1997-2006). Based on the monitoring data, we conclude that the high intertidal zone at Imago-ura, where a large part of the stranded oil accumulated, suffered the heaviest damage and experienced the slowest recovery. In addition, although the original status of macroalgal vegetation before the impact was not well-documented, it appeared that recovery from the damage caused by the oil pollution required four to five years.

• 한국지능시스템학회논문지
• /
• 제27권2호
• /
• pp.164-169
• /
• 2017

본 연구는 지속적으로 수계 내 녹조를 모니터링할 수 있도록 고정익 무인비행기에 멀티스펙트럴 센서를 탑재시켜 금강 유역의 하천을 촬영하고, NDVI 분석을 수행함으로써 수계환경을 효율적으로 관리하는 것을 목적으로 하고 있다. 연구 대상지역은 금강 유역의 백제보 인근이며, 연구수행에 사용된 데이터는 녹조 발생 초기인 2016년 7월에 촬영된 영상이다. 데이터 처리과정으로서, Pix4D 소프트웨어를 이용하여 NDVI 영상을 생성하는 작업을 수행하였다. 생성된 NDVI 영상을 클로로필 실측값과 비교하여 관계식을 도출하고 영상 수치 변환 작업을 수행하였다. 그 결과 실측값이 반영된 클로로필 영상을 추출할 수 있었으며, 앞으로 수계환경관리를 위한 녹조 관측 및 모니터링, 그리고 재해예방 측면에서 무인비행기를 이용한 클로로필 정보 취득은 매우 유용할 것으로 판단된다.

• 수산해양교육연구
• /
• 제28권2호
• /
• pp.376-383
• /
• 2016

In this paper, the blue-green algae monitoring program of applying IoT(Internet of things) technologies is designed and implemented that can check out the status of the river's water quality in real time. The proposed system is to extract the image data from the camera of raspberry pi by an wireless network, and it is analyzed through the HSV color model. We measure the temperature using a DS18B20 1-wire temperature sensor. The extracted information of image data and temperature is then analyzed in C and Python programs for use with Raspberry Pi. The XML data in PHP program is made from the analyzed information and provides Web services. It also allows to refer the XML data using mobile devices.

• Journal of Ecology and Environment
• /
• 제36권1호
• /
• pp.95-100
• /
• 2013

Many countries have adopted a single, well-described approach to the use of phototrophs for monitoring river water quality, which involves the use of indices related to diatom composition at a site. Increasingly these indices have focussed on assessing ambient phosphate concentration. However, there is a wide range of other methods which can provide additional information to make up for any weaknesses in the standard method. Some of these methods are reviewed briefly here. They can be useful, for instance, when considering temporal and spatial variability in phosphate concentration at a particular site and providing much more insight on heavy metal or pesticide pollution than revealed by routine water analysis.