Raspberry Pi-based smart sensing platform for drinking-water quality monitoring system: a Python framework approach

This paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters was made based on guidelines of the Central Pollution and Control Board (CPCB), New Delhi, India. A graphical user interface (GUI) was develo...

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Veröffentlicht in:Drinking water engineering and science Jg. 12; H. 1; S. 31 - 37
Hauptverfasser: Khatri, Punit, Gupta, Karunesh Kumar, Gupta, Raj Kumar
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Katlenburg-Lindau Copernicus GmbH 25.06.2019
Copernicus Publications
Schlagworte:
Analysis
Benchmarking
Data acquisition
Data analysis
Data collection
Data processing
Decision analysis
Decision making
Drinking water
End users
Environmental monitoring
Graphical user interface
Man-machine interfaces
Monitoring systems
Pollution
Pollution control
Pollution monitoring
Programming languages
Python
Quality control
Quality management
Technology application
User interface
Water
Water analysis
Water monitoring
Water pollution
Water quality
Water quality management
Water sampling
ISSN:1996-9465, 1996-9457, 1996-9465
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Abstract This paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters was made based on guidelines of the Central Pollution and Control Board (CPCB), New Delhi, India. A graphical user interface (GUI) was developed for providing an interactive human machine interface to the end user for ease of operation. The Python programming language was used for GUI development, data acquisition, and data analysis. Fuzzy computing techniques were employed for decision-making to categorize the water quality in different classes like “bad”, “poor”, “satisfactory”, “good”, and “excellent”. The system has been tested for various water samples from eight different locations, and the water quality was observed as being good, satisfactory, and poor for the measured water samples. Finally, the obtained results were compared with the benchmark for authentication.
AbstractList This paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters was made based on guidelines of the Central Pollution and Control Board (CPCB), New Delhi, India. A graphical user interface (GUI) was developed for providing an interactive human machine interface to the end user for ease of operation. The Python programming language was used for GUI development, data acquisition, and data analysis. Fuzzy computing techniques were employed for decision-making to categorize the water quality in different classes like “bad”, “poor”, “satisfactory”, “good”, and “excellent”. The system has been tested for various water samples from eight different locations, and the water quality was observed as being good, satisfactory, and poor for the measured water samples. Finally, the obtained results were compared with the benchmark for authentication.
This paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters was made based on guidelines of the Central Pollution and Control Board (CPCB), New Delhi, India. A graphical user interface (GUI) was developed for providing an interactive human machine interface to the end user for ease of operation. The Python programming language was used for GUI development, data acquisition, and data analysis. Fuzzy computing techniques were employed for decision-making to categorize the water quality in different classes like “bad”, “poor”, “satisfactory”, “good”, and “excellent”. The system has been tested for various water samples from eight different locations, and the water quality was observed as being good, satisfactory, and poor for the measured water samples. Finally, the obtained results were compared with the benchmark for authentication.
Audience Academic
Author Khatri, Punit
Gupta, Raj Kumar
Gupta, Karunesh Kumar
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Snippet This paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters...
This paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters...
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StartPage 31
SubjectTerms Analysis
Benchmarking
Data acquisition
Data analysis
Data collection
Data processing
Decision analysis
Decision making
Drinking water
End users
Environmental monitoring
Graphical user interface
Man-machine interfaces
Monitoring systems
Pollution
Pollution control
Pollution monitoring
Programming languages
Python
Quality control
Quality management
Technology application
User interface
Water
Water analysis
Water monitoring
Water pollution
Water quality
Water quality management
Water sampling
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Title Raspberry Pi-based smart sensing platform for drinking-water quality monitoring system: a Python framework approach
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