Water, soil and air pollutants' interaction on mangrove ecosystem and corresponding artificial intelligence techniques used in decision support systems : A review

Wong, Wen Yee and Al-Ani, Ayman Khallel Ibrahim and Hasikin, Khairunnisa and Khairuddin, Anis Salwa Mohd and Razak, Sarah Abdul and Hizaddin, Hanee Farzana and Mokhtar, Mohd Istajib and Azizan, Muhammad Mokhzaini (2021) Water, soil and air pollutants' interaction on mangrove ecosystem and corresponding artificial intelligence techniques used in decision support systems : A review. IEEE Access, 9. pp. 105532-105563. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2021.3099107.

Full text not available from this repository.

Abstract

The feasibility of artificial intelligence (AI) as a predictive model for thorough efficacy analysis on environmental pollution applied on mangrove forests are discussed. Mangrove forests are among the most productive and biological diverse ecosystems on the planet. However, due to environmental pollution and climate change, mangrove forests are in serious decline. Despite crucial issues pertaining mangrove forests, the law enforcement on the ecosystem is still dubious due to the lack of evidence and data that could provide accurate analysis and prediction. The main highlight of this review elaborates on pollutant markers in soil, water, and air, by correlating these three aspects to the sustainability of mangrove ecosystem. The research gap identified from this review suggests the application of an integrated environmental prediction system for practical environmental insights. A predictive model for environmental decision-making could be developed by integrating meteorological, climatological, hydrological, atmospheric, and heavy metal concentration to understand the interaction between each factor for an efficient solution of pollutant reduction scheme involving mangrove ecosystems.

Item Type: Article
Funders: Ministry of Higher Education through the Malaysian Research University Network (MRUN) Young Researchers Grant Scheme (MY-RGS)[MR001-2019], Universiti Malaya Living Laboratory[LL037-18SUS]
Uncontrolled Keywords: Metals;Ecosystems;Pollution;Forestry;Water pollution;Artificial intelligence;Soil;Mangrove estuarine; Pollutant interaction;Environmental quality modeling; Integrated environmental decision system
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QK Botany
S Agriculture > SD Forestry
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science
Depositing User: Ms Zaharah Ramly
Date Deposited: 22 Jun 2022 04:35
Last Modified: 22 Jun 2022 04:35
URI: http://eprints.um.edu.my/id/eprint/34126

Actions (login required)

View Item View Item