Citation

Che Samsuria, Nur Nazifa and Wan Ismail, Wan Zakiah and Nazli, Muhammad Nurullah Waliyullah Mohamed and Ab Aziz, Nor Azlina and Ghazali, Anith Khairunnisa (2025) Problems, Effects, and Methods of Monitoring and Sensing Oil Pollution in Water: A Review. Water, 17 (9). p. 1252. ISSN 2073-4441

Text Problems, Effects, and Methods of Monitoring and Sensing Oil Pollution in Water_ A Review.pdf - Published Version Restricted to Repository staff only Download (513kB)

Abstract

: Oil pollution in water bodies is a substantial environmental concern that poses severe risks to human health, aquatic ecosystems, and economic activities. Rising energy consumption and industrial activity have resulted in more oil spills, damaging longterm ecology. The aim of the review is to discuss problems, effects, and methods of monitoring and sensing oil pollution in water. Oil can destroy the aquatic habitat. Once oil gets into aquatic habitats, it changes both physically and chemically, depending on temperature, wind, and wave currents. If not promptly addressed, these processes have severe repercussions on the spread, persistence, and toxicity of oil. Effective monitoring and early identification of oil pollution are vital to limit environmental harm and permit timely reaction and cleanup activities. Three main categories define the three main methodologies of oil spill detection. Remote sensing utilizes satellite imaging and airborne surveillance to monitor large-scale oil spills and trace their migration across aquatic bodies. Accurate real-time detection is made possible by optical sensing, which uses fluorescence and infrared methods to identify and measure oil contamination based on its particular optical characteristics. Using sensor networks and Internet of Things (IoT) technologies, wireless sensing improves early detection and response capacity by the continuous automated monitoring of oil pollution in aquatic settings. In addition, the effectiveness of advanced artificial intelligence (AI) techniques, such as deep learning (DL) and machine learning (ML), in enhancing detection accuracy, predicting leak patterns, and optimizing response strategies, is investigated. This review assesses the advantages and limits of these detection technologies and offers future research directions to advance oil spill monitoring. The results help create more sustainable and efficient plans for controlling oil pollution and safeguarding aquatic habitats.

Item Type:	Article
Uncontrolled Keywords:	Oil pollution sensing method
Subjects:	Q Science > QH Natural history T Technology > TD Environmental technology. Sanitary engineering > TD813-870 Street cleaning. Litter and its removal
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	30 May 2025 06:12
Last Modified:	30 May 2025 06:12
URII:	http://shdl.mmu.edu.my/id/eprint/13900

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