Ten Years of Practical Experience with the Dreissena-Monitor, a Biological Early Warning System for Continuous Water Quality Monitoring

Hydrobiologia ◽  
2006 ◽  
Vol 556 (1) ◽  
pp. 417-426 ◽  
Author(s):  
Jost Borcherding
Keyword(s):  
Water Quality ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Water Quality Monitoring ◽  
Practical Experience ◽  
Quality Monitoring ◽  
Biological Early Warning System

Research and Application of Real-Time Remote Monitoring and Early Warning System of Source Water Quality

2013 ◽  
Vol 779-780 ◽  
pp. 1408-1413
Author(s):  
Shu Yuan Li ◽  
Jian Hua Tao ◽  
Lei Yu
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Early Warning ◽  
Remote Monitoring ◽  
Early Warning System ◽  
Warning System ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
The Real ◽  
Monitoring And Early Warning

Drinking water sources play an important role in assurance of life safety, normal production and social stability. In this paper, a real-time remote water quality monitoring and early warning system has been developed. The paper concentrates on the system architecture and key techniques of the real-time water quality monitoring and early warning. The implementation of the system by advanced water quality sensor techniques, wireless transmission, databases and water quality modeling is retraced in detail. It can be applied to the real-time remote monitoring of water quality and decision support for water pollution incidents.

scholarly journals Remote Water Quality Monitoring with Early –Warning System for Marine Aquaculture

2021 ◽  
Vol 324 ◽  
pp. 05007
Author(s):  
Rozeff Pramana ◽  
Bhakti Yudho Suprapto ◽  
Zainuddin Nawawi
Keyword(s):  
Water Quality ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Quality Data ◽  
Alarm System ◽  
Water Quality Data ◽  
Marine Aquaculture

Rapid technological developments have penetrated the application of technology in the field of aquaculture. Climate Changes that are currently uncertain and beyond prediction encourage the application of technology to increase fishery production and modernization. The purpose of this study is to design a water quality monitoring system that can be monitored remotely in real-time using an internet-based smartphone/PC application. It is equipped with an early warning system to monitor the water quality set by the upper and lower thresholds. This device is based on Robotdyn Uno Wifi R3 ESP8266 with IoT technology. The alarm system uses a buzzer and LED indicator to make it understandable to fishermen. We tested the device in two stages. Results showed that the alarm system responds to all changes in water quality that exceeds the set threshold. Water quality data can be monitored with an internet-based smartphone application and updated every 15-16 seconds

The “Dreissena-Monitor” – First Results on the Application of this Biological Early Warning System in the Continuous Monitoring of Water Quality

1994 ◽  
Vol 29 (3) ◽  
pp. 199-201 ◽  
Author(s):  
Jost Borcherding ◽  
Markus Volpers
Keyword(s):  
Water Quality ◽  
Early Warning ◽  
Early Warning System ◽  
Dreissena Polymorpha ◽  
Continuous Monitoring ◽  
Warning System ◽  
Small Rivers ◽  
First Results ◽  
Biological Early Warning System ◽  
High Degree

The “Dreissena-Monitor” is a biological early warning system used in the continuous monitoring of water quality. The system is based on a computer assessment of valve movements in two groups of up to 42 zebra mussels (Dreissena polymorpha). Every 5 minutes, the percentage of open mussels and the average number of valve movements per mussel are calculated to describe the activity behaviour of the mussels. Rapid changes in both parameters normally reflect the onset of stress. More than 5½ years of experience in the continuous monitoring of water quality have revealed (1) that the “Dreissena-Monitor” is suited to large rivers like the Rhine as well as small rivers like the Erft or Ruhr, (2) that a lack of technical interruptions guarantees reliable, unattended operation, (3) that normally less than 3 hours of weekly maintenance are required, (4) that the validity check of the primary measurements was capable of identifying dead mussels and poorly aligned measurement components, (5) that the system can operate under unfavourable conditions (e.g. temperatures below 5° C), (6) that mortality rates were low and correlated positively with temperature, and (7) that the alarm thresholds provided a high degree of statistical security.

New Design for Water Quality Early Warning System

2012 ◽  
pp. 681-685
Author(s):  
Tian Jing ◽  
Zheng Shuyin ◽  
Zhang Guangxin ◽  
Hou Dibo ◽  
Huang Pingjie ◽  
...  
Keyword(s):  
Water Quality ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System

Developing a knowledge-based early warning system for fish disease/health via water quality management

2009 ◽  
Vol 36 (3) ◽  
pp. 6500-6511 ◽  
Author(s):  
Nan Li ◽  
Ruimei Wang ◽  
Jian Zhang ◽  
Zetian Fu ◽  
XiaoShuan Zhang
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Early Warning ◽  
Early Warning System ◽  
Water Quality Management ◽  
Warning System ◽  
Fish Disease ◽  
Knowledge Based

An On-Line Water Quality Monitoring System for the Reservoirs Based on Android

2014 ◽  
Vol 945-949 ◽  
pp. 2199-2202
Author(s):  
Zi Wen Dai ◽  
Hai Yang Liao
Keyword(s):  
Water Quality ◽  
Monitoring System ◽  
Early Warning ◽  
Automatic Monitoring ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Water Quality Change ◽  
Long Time ◽  
On Line ◽  
Warning Model

According to the demand of water quality automatic monitoring in many large or medium reservoirs, we proposed an on-line water quality monitoring system. It is composed of wireless sensor networks and an embedded monitoring platform. We built a novel early-warning model to well adapt to the regular pattern of water quality change in the reservoirs. As a result, an Android application with outstanding control experience is achieved for real-time monitoring, water pollution early warning and water quality comprehensive assessment. Experimental results show that the system can work stably for a long time and provide accurate monitoring information continuously. It can also detect the abnormal signals of water quality in time and alarm. The system efficiently satisfies the requirement of water quality on-line automatic monitoring.

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