Applications of Artificial Neural Network in the Prediction of Water Quality Index

Tshedza Murivhami; Lagouge Kwanda Tartibu; Isaac Oyeyemi Olayode

doi:10.1109/ICMIMT59138.2023.10199388

Applications of Artificial Neural Network in the Prediction of Water Quality Index

Tshedza Murivhami
, Lagouge Kwanda Tartibu
, Isaac Oyeyemi Olayode

Mechanical and Industrial Engineering Technology

University of Johannesburg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

Artificial intelligence can significantly lower water supply and sanitation systems and assist to ensure compliance with drinking water and wastewater treatment standards. As a result, there has been extensive research on modelling and forecasting water quality to reduce water pollution. The proposed system's uniqueness is offered to create an effective monitoring operation. This paper uses Artificial Neural Network (ANN) for the prediction of water quality index (WQI). Seven important water quality parameters were considered, namely the Dissolved Oxygen (DO), the pH, the conductivity, the Biochemical Oxygen Demand (BOD), the nitrate, faecal coliform, and the total coliform. In the study, seven parameters were used for the modelling and prediction of water quality index. A design concept of a water purification system is disclosed in this work. The proposed model exhibits a prediction performance of 0.98114.

Original language	English
Title of host publication	2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	100-104
Number of pages	5
ISBN (Electronic)	9798350313093
DOIs	https://doi.org/10.1109/ICMIMT59138.2023.10199388
Publication status	Published - 2023
Event	14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023 - Cape Town, South Africa Duration: 26 May 2023 → 28 May 2023

Publication series

Name	2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023

Conference

Conference	14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023
Country/Territory	South Africa
City	Cape Town
Period	26/05/23 → 28/05/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 6 Clean Water and Sanitation

Keywords

artificial intelligence
artificial neural network
water purification
water quality index

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Computational Mechanics
Industrial and Manufacturing Engineering
Mechanical Engineering
Safety, Risk, Reliability and Quality
Materials Science (miscellaneous)

Access to Document

10.1109/ICMIMT59138.2023.10199388

Cite this

Murivhami, T., Tartibu, L. K., & Olayode, I. O. (2023). Applications of Artificial Neural Network in the Prediction of Water Quality Index. In 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023 (pp. 100-104). (2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMIMT59138.2023.10199388

Murivhami, Tshedza ; Tartibu, Lagouge Kwanda ; Olayode, Isaac Oyeyemi. / Applications of Artificial Neural Network in the Prediction of Water Quality Index. 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 100-104 (2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023).

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abstract = "Artificial intelligence can significantly lower water supply and sanitation systems and assist to ensure compliance with drinking water and wastewater treatment standards. As a result, there has been extensive research on modelling and forecasting water quality to reduce water pollution. The proposed system's uniqueness is offered to create an effective monitoring operation. This paper uses Artificial Neural Network (ANN) for the prediction of water quality index (WQI). Seven important water quality parameters were considered, namely the Dissolved Oxygen (DO), the pH, the conductivity, the Biochemical Oxygen Demand (BOD), the nitrate, faecal coliform, and the total coliform. In the study, seven parameters were used for the modelling and prediction of water quality index. A design concept of a water purification system is disclosed in this work. The proposed model exhibits a prediction performance of 0.98114.",

keywords = "artificial intelligence, artificial neural network, water purification, water quality index",

author = "Tshedza Murivhami and Tartibu, \{Lagouge Kwanda\} and Olayode, \{Isaac Oyeyemi\}",

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year = "2023",

doi = "10.1109/ICMIMT59138.2023.10199388",

language = "English",

series = "2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023",

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Murivhami, T, Tartibu, LK & Olayode, IO 2023, Applications of Artificial Neural Network in the Prediction of Water Quality Index. in 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023. 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023, Institute of Electrical and Electronics Engineers Inc., pp. 100-104, 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023, Cape Town, South Africa, 26/05/23. https://doi.org/10.1109/ICMIMT59138.2023.10199388

Applications of Artificial Neural Network in the Prediction of Water Quality Index. / Murivhami, Tshedza; Tartibu, Lagouge Kwanda; Olayode, Isaac Oyeyemi.
2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 100-104 (2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Applications of Artificial Neural Network in the Prediction of Water Quality Index

AU - Murivhami, Tshedza

AU - Tartibu, Lagouge Kwanda

AU - Olayode, Isaac Oyeyemi

PY - 2023

Y1 - 2023

N2 - Artificial intelligence can significantly lower water supply and sanitation systems and assist to ensure compliance with drinking water and wastewater treatment standards. As a result, there has been extensive research on modelling and forecasting water quality to reduce water pollution. The proposed system's uniqueness is offered to create an effective monitoring operation. This paper uses Artificial Neural Network (ANN) for the prediction of water quality index (WQI). Seven important water quality parameters were considered, namely the Dissolved Oxygen (DO), the pH, the conductivity, the Biochemical Oxygen Demand (BOD), the nitrate, faecal coliform, and the total coliform. In the study, seven parameters were used for the modelling and prediction of water quality index. A design concept of a water purification system is disclosed in this work. The proposed model exhibits a prediction performance of 0.98114.

AB - Artificial intelligence can significantly lower water supply and sanitation systems and assist to ensure compliance with drinking water and wastewater treatment standards. As a result, there has been extensive research on modelling and forecasting water quality to reduce water pollution. The proposed system's uniqueness is offered to create an effective monitoring operation. This paper uses Artificial Neural Network (ANN) for the prediction of water quality index (WQI). Seven important water quality parameters were considered, namely the Dissolved Oxygen (DO), the pH, the conductivity, the Biochemical Oxygen Demand (BOD), the nitrate, faecal coliform, and the total coliform. In the study, seven parameters were used for the modelling and prediction of water quality index. A design concept of a water purification system is disclosed in this work. The proposed model exhibits a prediction performance of 0.98114.

KW - artificial intelligence

KW - artificial neural network

KW - water purification

KW - water quality index

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DO - 10.1109/ICMIMT59138.2023.10199388

M3 - Conference contribution

AN - SCOPUS:85168764507

T3 - 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023

SP - 100

EP - 104

BT - 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023

Y2 - 26 May 2023 through 28 May 2023

ER -

Murivhami T, Tartibu LK, Olayode IO. Applications of Artificial Neural Network in the Prediction of Water Quality Index. In 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 100-104. (2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023). doi: 10.1109/ICMIMT59138.2023.10199388

Applications of Artificial Neural Network in the Prediction of Water Quality Index

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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