Design and realization of a water quality monitoring system based on the Internet of Things

ABSTRACT Water quality monitoring is a key means of ensuring the safety of water resources, protecting the ecological environment and maintaining public health. This paper describes a water quality monitoring system based on the Internet of Things (IoT), which supports real-time monitoring, remote c...

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Bibliographic Details
Published inWater practice and technology Vol. 19; no. 9; pp. 3538 - 3554
Main Authors Tang, Jinyuan, Lin, Haimi, Tian, Qingqing
Format Journal Article
LanguageEnglish
Published London IWA Publishing 01.09.2024
Subjects
Accuracy
Algorithms
Alkalinity
Data processing
Design
Embedded systems
Environmental monitoring
Internet of Things
Machine learning
Machinery condition monitoring
Monitoring
Monitoring systems
Power
Public health
Real time
Remote control
Remote monitoring
Sensors
Software reliability
System reliability
Water monitoring
Water pollution
Water quality
Water quality management
Water resources
Water temperature
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Summary:ABSTRACT Water quality monitoring is a key means of ensuring the safety of water resources, protecting the ecological environment and maintaining public health. This paper describes a water quality monitoring system based on the Internet of Things (IoT), which supports real-time monitoring, remote control and intelligent early warnings. It is concluded that the system can effectively collect, process and display data on water quality. To further improve the level of intelligence of the water quality monitoring system, the ability of machine learning algorithm to analyze and predict the water quality data has also been separately tested. In this paper, the hardware design, software design, test results and algorithm evaluation of the system are described. The actual performance and reliability of the system in practical application under various field conditions have not yet been verified. This new system is compared with other water quality monitoring systems.
ISSN:1751-231X
1751-231X
DOI:10.2166/wpt.2024.222