• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.4C
• /
• pp.401-410
• /
• 2007

In this paper, we propose water quality monitoring system using vision camera and multiple objects tracking method. The proposed system analyzes object individually using vision camera unlike monitoring system using sensor method. The system using vision camera consists of individual object segmentation part and objects tracking part based on interrelation between successive frames. For real-time processing, we make background image using non-parametric estimation and extract objects using background image. If we use non-parametric estimation, objects extraction method can reduce large amount of computation complexity, as well as extract objects more effectively. Multiple objects tracking method predicts next motion using moving direction, velocity and acceleration of individual object then carries out tracking based on the predicted motion. And we apply exception handling algorithms to improve tracking performance. From experiment results under various conditions, it shows that the proposed system can be available for real-time water quality monitoring system since it has very short processing time and correct multiple objects tracking.

• Journal of Sensor Science and Technology
• /
• v.31 no.2
• /
• pp.102-106
• /
• 2022

Currently, the demand for real-time monitoring of water quality has increased dramatically. Total organic carbon (TOC) analysis is a suitable method for real-time analysis compared with conventional biochemical oxygen demand (BOD) and chemical oxygen demand (COD) methods in terms of analysis time. However, this method is expensive because of the complicated internal processes involved. The photocatalytic titanium dioxide (TiO2)-based TOC method is simpler as it omits more than three preprocessing steps. This is because it reacts only with organic carbon (OC) without extra processes. We optimized the rate between the TiO2 photocatalyst and binder solution and the TiO2 concentration. The efficiency was investigated under 365 nm UV exposure onto a TiO2 coated substrate. The optimized conditions were sufficient to apply a real-time monitoring system for water quality with a short reaction time (within 10 min). We expect that it can be applied in a wide range of water quality monitoring industries.

• Journal of Sensor Science and Technology
• /
• v.21 no.1
• /
• pp.46-52
• /
• 2012

The rapid water pollution in stream, river, lake and sea in recent years raises an urgent need for continuous monitoring and policymaking to conserve the global clean environment. In particular, the increasing water pollution in coastal marine areas adds to the importance of the environmental monitoring systems. In this paper, the mobile server is designed to gathers information of the water quality at coastal areas. The obtained data by the server is transmitted from field servers to the base station via multi-hop communication in wireless sensor network. The information collected includes dissolved oxygen(DO), hydrogen ion exponent(pH), temperature, etc. By the information provided the real-time monitoring of water quality at the coastal marine area. In addition, wireless sensor network-based flooding routing protocol was designed and used to transfer the measured water quality information efficiently. Telosb sensor node is programmed using nesC language in TinyOS platform for small scale wireless sensor network monitoring from a remote server.

• Journal of Korea Water Resources Association
• /
• v.38 no.7 s.156
• /
• pp.565-574
• /
• 2005

It is used water quality data that was measured at Pyeongchanggang real time monitoring stations in Namhan river. These characteristics were analyzed with the water qualify of rainy and nonrainy periods. TOC (Total Organic Carbon) data of rainy periods has correlation with discharge and shows high values of mean, maximum, and standard deviation. DO (Dissolved Oxygen) value of rainy periods is lower than those of 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 qualify forecasting models were applied. LMNN, MDNN, and ANFIS models have achieved the highest overall accuracy of TOC data. LMNN (Levenberg-Marquardt Neural Network) and MDNN (MoDular Neural Network) model which are applied for DO forecasting shows better results than ANFIS (Adaptive Neuro-Fuzzy Inference System). MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. The observation of discharge and water quality are effective at same point as well as same time for real time management. But there are some of real time water quality monitoring stations far from the T/M water stage. Pyeongchanggang station is one of them. So discharge on Pyeongchanggang station was calculated by developed runoff neural network model, and the water quality forecasting model is linked to the runoff forecasting model. That linked model shows the improvement of waterquality forecasting.

• Journal of Environmental Impact Assessment
• /
• v.30 no.2
• /
• pp.75-88
• /
• 2021

Six locations in the automated monitoring network at the Geum River Basin were selected forthis study. The water quality characteristics at two of the locations in the water quality monitoring network that were identical, or nearby, were examined, and their correlations were evaluated through statistical analysis. The results of the water quality analysis were converted to the water quality index and expressed in grades for comparison. For the data necessary for the study, public data from four years, from 2016-2019 were used and the evaluation parameters were water temperature, pH, EC, DO, TOC, TN, and TP. Results of the analysis showed that the water quality concentrations measured in the automated monitoring network and the water quality monitoring network differed in some measured values, but they tended to register variation in a specified ratio in most of the locations in the network. The analysis of the correlations of the parameters between the two monitoring networks found that water temperature, EC, and DO showed high correlations between the two monitoring networks. The TOC, TN, and TP showed high correlations, with a 0.7 or higher (correlation coefficient r), with the exception of some of the monitoring networks, although their correlations were lower than those of the basic parameters. The water quality index analysis showed that the water quality index values of the automated monitoring network and the water quality monitoring network were similar. The water quality index decreased and the pollution degree increased in the downstream direction, in both networks.

• Journal of Korean Society on Water Environment
• /
• v.26 no.4
• /
• pp.700-706
• /
• 2010

Along the 4 major rivers in korea, there are automatic water quality monitoring (AWQM) stations to immediately respond to any pollution incident. Real-time data (temperature, DO, pH, EC and TOC) collected at each station were statistically treated to exclude outliers and keep valid data using Dixon's test and Discordance test. These applied methods were compared in terms of the number of the outliers sorted out. There was no significant difference between these methods. On the other hand, more outliers were sorted out from EC and TOC data, comparing with other water quality items. EC data did not show partly any variation for a long time at H station. If measured signal does not exceed ${\pm}0.001mS/cm$ from the sectional mean, the signal should be treated as normal data. Therefore, another routine was added to the data screening system, some data which were removed as outlier were restored.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.1
• /
• pp.209-216
• /
• 2024

Land shrimp farms can control the growth environment more stably than coastal ones, making them advantageous for high-quality, large-scale production. In order to maintain an optimal shrimp growth environment, various factors such as water circulation, maintaining appropriate water temperature, oxygen supply, and feed supply must be managed. In particular, failure to properly manage water quality can lead to the death of shrimp, making it difficult to have people stationed at the farm 24 hours a day to continuously manage them. In this paper, to solve this problem, we design an integrated monitoring system for land farms that can be operated with minimal manpower. The proposed design plan uses IoT technology to collect real-time images of land farms, pump status, water quality data, and energy usage and transmit them to the server. Through web interfaces and smartphone apps, administrators can check the status of the farm stored on the server anytime, anywhere in real time and take necessary measures. Therefore, it is possible to significantly reduce field work hours without the need for managers to reside in the farm.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.09b
• /
• pp.1164-1165
• /
• 2005

• Journal of Sensor Science and Technology
• /
• v.32 no.2
• /
• pp.82-87
• /
• 2023

This study proposes a pH-dissolved-oxygen monitoring system using 8-HydroxyPyrene-1,3,6-trisulfonic acid Trisodium Salt (HPTS) and tris(4,7-diphenyl-1,10-phenanthroline)Ruthenium(II) chloride (Ru_dpp). Commercial water-quality sensors are electrochemical devices that require frequent calibration and cleaning, are subject to high maintenance costs, and have difficulties conducting measurements in real-time. The proposed pH-dissolved-oxygen monitoring system selects a thin-film sensing layer to measure the change in fluorescence intensity. This change in fluorescence intensity is based on reactions with hydrogen ions in an aqueous solution at a given pH and specific amount of dissolved oxygen. The change in fluorescence intensity is then measured using light-emitting diodes and photodiodes in response to HPTS and Ru_dpp. This method enables the development of a relatively small, inexpensive, and real-time measureable water-quality measurement system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.10a
• /
• pp.447-450
• /
• 2010

Today a relatively small reservoirs and reclamation insufficient freshwater Agricultural Water Quality to collect and analyze information online, Analyzed in real-time information delivery and database hwahameurosseo agricultural water quality management of reservoirs and freshwater lakes can be systematically. In this paper, a remote user to automatically measure water and measured to provide information collected from each sensor and integrate information connected to your wireless network and Integrated control measures as well as real-time monitoring of the operational point of observation from a web site in real-time information about the water to retrieve the user's computer and the user consists of a mobile communication terminal.