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

Results in Engineering (Dec 2023)

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

Affiliations

Hesam Kamyab: Faculty of Architecture and Urbanism, UTE University, Calle Rumipamba S/N and Bourgeois, Quito, Ecuador; Department of Biomaterials, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, 600 077, India; Process Systems Engineering Centre (PROSPECT), Faculty of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia; Corresponding author. Faculty of Architecture and Urbanism, UTE University, Calle Rumipamba S/N and Bourgeois, Quito, Ecuador.
Tayebeh Khademi: Azman Hashim International Business School (AHIBS), Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia; Corresponding author.
Shreeshivadasan Chelliapan: Engineering Department, Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Jln Sultan Yahya Petra, 54100, Kuala Lumpur, Malaysia; Corresponding author.
Morteza SaberiKamarposhti: Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100, Cyberjaya, Malaysia
Shahabaldin Rezania: Department of Environment and Energy, Sejong University, Seoul, 05006, South Korea
Mohammad Yusuf: Clean Energy Technologies Research Institute (CETRI), Process Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, 3737 Wascana Parkway, Regina, SK, S4S 0A2, Canada
Mohammad Farajnezhad: Azman Hashim International Business School (AHIBS), Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia
Mohamed Abbas: Electrical Engineering Department, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia
Byong Hun Jeon: Department of Earth Resources & Environmental Engineering, Hanyang University, 222-Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea
Yongtae Ahn: Department of Civil & Energy System Engineering, Kyonggi University, Suwon, 16227, Republic of Korea

Journal volume & issue: Vol. 20
p. 101566

Abstract

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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.

Published in Results in Engineering

ISSN: 2590-1230 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Technology
Website: https://www.journals.elsevier.com/results-in-engineering

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