A critical review on early-warning electrochemical system on microbial fuel cell-based biosensor for on-site water quality monitoring

Chemosphere ◽  
2021 ◽  
pp. 133098
Author(s):  
Tukendra Kumar ◽  
Sweta Naik ◽  
Satya Eswari Jujjavarappu
Keyword(s):  
Water Quality ◽  
Fuel Cell ◽  
Microbial Fuel Cell ◽  
Early Warning ◽  
Critical Review ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Electrochemical System ◽  
Site Water

scholarly journals Portable, Disposable, Paper-Based Microbial Fuel Cell Sensor Utilizing Freeze-Dried Bacteria for In Situ Water Quality Monitoring

ACS Omega ◽  
2020 ◽  
Vol 5 (23) ◽  
pp. 13940-13947 ◽  
Author(s):  
Jong Hyun Cho ◽  
Yang Gao ◽  
Jihyun Ryu ◽  
Seokheun Choi
Keyword(s):  
Water Quality ◽  
Fuel Cell ◽  
Microbial Fuel Cell ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Freeze Dried

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.

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 Applying a deployment strategy and data analysis model for water quality continuous monitoring and management

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092982
Author(s):  
Fan-Lun Chen ◽  
Bo-Chieh Yang ◽  
Shu-Yi Peng ◽  
Tzu-Chi Lin
Keyword(s):  
Water Quality ◽  
Internet Of Things ◽  
Early Warning ◽  
Continuous Monitoring ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Source Analysis ◽  
Analysis Model ◽  
Environment Analysis ◽  
The Impact

In Taiwan, where residential and industrial areas are in close proximity, finding ways to effectively continuous monitor and manage water quality is an essential issue. This study established a total solution for an Internet of things water quality monitoring network that integrates domestic miniaturized water quality monitoring sensors for real-time transport data of pH, temperature, conductivity, chemical oxygen demand, and copper ions. The data will be used to establish an analysis model based on continuous monitoring of the nation’s background concentration. We designed an automatic continuous monitoring and early warning analysis module for automatic analysis of environmental and instrumental anomalies for decision makers, a “pollution source analysis module” utilizing static and dynamic cross-environment data to swiftly trace upstream pollution sources, and a “pollution hotspot analysis module” to evaluate the impact area of pollutants, and immediate response measures to achieve early warning and swift evaluation for the prevention of water pollution. To do this, we installed 100 domestic miniaturized water monitoring devices in Taoyuan City for testing the solution. We found that the establishment of an Internet of things environment analysis and response model integrated with cross-environment analysis can be applied in water quality monitoring and management to assure improved environmental quality.

scholarly journals STUDY OF WATER POLLUTION EARLY WARNING FRAMEWORK BASED ON INTERNET OF THINGS

2016 ◽  
Vol XLI-B8 ◽  
pp. 335-338
Author(s):  
H. Chengfang ◽  
X. Xiao ◽  
S. Dingtao ◽  
C. Bo ◽  
W. Xiongfei
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Internet Of Things ◽  
Early Warning ◽  
High Speed ◽  
Water Quality Monitoring ◽  
Pollution Monitoring ◽  
Quality Monitoring ◽  
Monitoring Method ◽  
Application Systems

In recent years, with the increasing world environmental pollution happening, sudden water pollution incident has become more and more frequently in China. It has posed a serious threat to water safety of the people living in the water source area. Conventional water pollution monitoring method is manual periodic testing, it maybe miss the best time to find that pollution incident. This paper proposes a water pollution warning framework to change this state. On the basis of the Internet of things, we uses automatic water quality monitoring technology to realize monitoring. We calculate the monitoring data with water pollution model to judge whether the water pollution incident is happen or not. Water pollution warning framework is divided into three layers: terminal as the sensing layer, it with the deployment of the automatic water quality pollution monitoring sensor. The middle layer is the transfer network layer, data information implementation is based on GPRS wireless network transmission. The upper one is the application layer. With these application systems, early warning information of water pollution will realize the high-speed transmission between grassroots units and superior units. The paper finally gives an example that applying this pollution warning framework to water quality monitoring of Beijing, China, it greatly improves the speed of the pollution warning responding of Beijing.

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