The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management

Hesam Kamyab; Tayebeh Khademi; Shreeshivadasan Chelliapan; Morteza SaberiKamarposhti; Shahabaldin Rezania; Mohammad Yusuf; Mohammad Farajnezhad; Mohamed Abbas; Byong Hun Jeon; Yongtae Ahn

doi:10.1016/j.rineng.2023.101566

The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management

Hesam Kamyab
, Tayebeh Khademi
, Shreeshivadasan Chelliapan
, Morteza SaberiKamarposhti
, Shahabaldin Rezania
, Mohammad Yusuf
, Mohammad Farajnezhad
, Mohamed Abbas
, Byong Hun Jeon
, Yongtae Ahn

Universidad Tecnológica Equinoccial
Saveetha Institute of Medical and Technical Sciences (Deemed to be University)
Universiti Teknologi Malaysia
Multimedia University
Sejong University
University of Regina
King Khalid University
Hanyang University
Kyonggi University

Research output: Contribution to journal › Article › peer-review

285 Citations (Scopus)

Abstract

The effective management of water resources is essential to environmental stewardship and sustainable development. Traditional approaches to water resource management (WRM) struggle with real-time data acquisition, effective data analysis, and intelligent decision-making. To address these challenges, innovative solutions are required. Artificial Intelligence (AI) and Big Data Analytics (BDA) are at the forefront and have the potential to revolutionize the way water resources are managed. This paper reviews the current applications of AI and BDA in WRM, highlighting their capacity to overcome existing limitations. It includes the investigation of AI technologies, such as machine learning and deep learning, and their diverse applications to water quality monitoring, water allocation, and water demand forecasting. In addition, the review explores the role of BDA in the management of water resources, elaborating on the various data sources that can be used, such as remote sensing, IoT devices, and social media. In conclusion, the study synthesizes key insights and outlines prospective directions for leveraging AI and BDA for optimal water resource allocation.

Original language	English
Article number	101566
Journal	Results in Engineering
Volume	20
DOIs	https://doi.org/10.1016/j.rineng.2023.101566
Publication status	Published - Dec 2023
Externally published	Yes

UN SDGs

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

SDG 4 Quality Education
SDG 6 Clean Water and Sanitation
SDG 8 Decent Work and Economic Growth
SDG 17 Partnerships for the Goals

Keywords

Artificial intelligence
Big data analytics
Water demand forecasting
Water quality monitoring
Water resource management

Access to Document

10.1016/j.rineng.2023.101566

Cite this

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title = "The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management",

abstract = "The effective management of water resources is essential to environmental stewardship and sustainable development. Traditional approaches to water resource management (WRM) struggle with real-time data acquisition, effective data analysis, and intelligent decision-making. To address these challenges, innovative solutions are required. Artificial Intelligence (AI) and Big Data Analytics (BDA) are at the forefront and have the potential to revolutionize the way water resources are managed. This paper reviews the current applications of AI and BDA in WRM, highlighting their capacity to overcome existing limitations. It includes the investigation of AI technologies, such as machine learning and deep learning, and their diverse applications to water quality monitoring, water allocation, and water demand forecasting. In addition, the review explores the role of BDA in the management of water resources, elaborating on the various data sources that can be used, such as remote sensing, IoT devices, and social media. In conclusion, the study synthesizes key insights and outlines prospective directions for leveraging AI and BDA for optimal water resource allocation.",

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AU - Kamyab, Hesam

AU - Khademi, Tayebeh

AU - Chelliapan, Shreeshivadasan

AU - SaberiKamarposhti, Morteza

AU - Rezania, Shahabaldin

AU - Yusuf, Mohammad

AU - Farajnezhad, Mohammad

AU - Abbas, Mohamed

AU - Hun Jeon, Byong

AU - Ahn, Yongtae

PY - 2023/12

Y1 - 2023/12

N2 - The effective management of water resources is essential to environmental stewardship and sustainable development. Traditional approaches to water resource management (WRM) struggle with real-time data acquisition, effective data analysis, and intelligent decision-making. To address these challenges, innovative solutions are required. Artificial Intelligence (AI) and Big Data Analytics (BDA) are at the forefront and have the potential to revolutionize the way water resources are managed. This paper reviews the current applications of AI and BDA in WRM, highlighting their capacity to overcome existing limitations. It includes the investigation of AI technologies, such as machine learning and deep learning, and their diverse applications to water quality monitoring, water allocation, and water demand forecasting. In addition, the review explores the role of BDA in the management of water resources, elaborating on the various data sources that can be used, such as remote sensing, IoT devices, and social media. In conclusion, the study synthesizes key insights and outlines prospective directions for leveraging AI and BDA for optimal water resource allocation.

AB - The effective management of water resources is essential to environmental stewardship and sustainable development. Traditional approaches to water resource management (WRM) struggle with real-time data acquisition, effective data analysis, and intelligent decision-making. To address these challenges, innovative solutions are required. Artificial Intelligence (AI) and Big Data Analytics (BDA) are at the forefront and have the potential to revolutionize the way water resources are managed. This paper reviews the current applications of AI and BDA in WRM, highlighting their capacity to overcome existing limitations. It includes the investigation of AI technologies, such as machine learning and deep learning, and their diverse applications to water quality monitoring, water allocation, and water demand forecasting. In addition, the review explores the role of BDA in the management of water resources, elaborating on the various data sources that can be used, such as remote sensing, IoT devices, and social media. In conclusion, the study synthesizes key insights and outlines prospective directions for leveraging AI and BDA for optimal water resource allocation.

KW - Artificial intelligence

KW - Big data analytics

KW - Water demand forecasting

KW - Water quality monitoring

KW - Water resource management

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DO - 10.1016/j.rineng.2023.101566

M3 - Article

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SN - 2590-1230

VL - 20

JO - Results in Engineering

JF - Results in Engineering

M1 - 101566

ER -

The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management

Abstract

UN SDGs

Keywords

Access to Document

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