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Implementing Artificial Intelligence to Reduce Marine Ecosystem Pollution

Fazri, Muhammad Faizal and Kusuma, Lintang Bayu and Rahmawan, Risa Burhani and Fauji, Hardiana Nur (2023) Implementing Artificial Intelligence to Reduce Marine Ecosystem Pollution. IAIC Transactions on Sustainable Digital Innovation (ITSDI), 4 (2). pp. 1-8. ISSN 2715-0461

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Industrial growth has a positive impact because it brings prosperity to humans. But on the other hand, it also has a negative effect, mainly due to industrial pollution produced. The pollution impacts environmental damage, one of which is the marine environment. This damage can be reduced by increasing understanding of the marine environment by monitoring it using technology. Although efforts have been made to monitor the marine environment, there are difficulties interpreting the large amount of data collected. To overcome these obstacles, we need technology that can process big data. One of the technologies that can be used is Artificial Intelligence which will be discussed in this study. This study aims to provide further understanding regarding the application of Artificial Intelligence to monitor the marine environment. This study uses a literature review method from several studies related to Artificial Intelligence. The final result of this study explains the potential and impact of applying Artificial Intelligence in reducing pollution of the marine environment sustainably. Although there have been many efforts to monitor the ocean for pollutants remotely, classifying the data is challenging because of the high volume of data. Therefore, the novelty of this research is to discuss a use case of a new approach to monitoring the ocean with the help of Artificial Intelligence. This research is expected to be motivated to develop better solutions in overcoming marine environment pollution using Artificial Intelligence technology.

Item Type: Article
Subjects: Technologies > Artificial Intelligence
Technologies > Machine Learning
Depositing User: Admin Digital Blue Ocean
Date Deposited: 27 Jun 2023 08:36
Last Modified: 27 Jun 2023 08:36

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