A Review to do Fishermen Boat Automation with Artificial Intelligence for Sustainable Fishing Experience Ensuring Safety, Security, Navigation and Sharing Information for Omani Fishermen

Author:

Amuthakkannan Rajakannu1,Vijayalakshmi K.2ORCID,Al Araimi Saleh2,Ali Saud Al Tobi Maamar1

Affiliation:

1. Department of Mechanical and Industrial Engineering, National University of Science and Technology, Muscat 130, Oman

2. Department of Electrical and Communication Engineering, National University of Science and Technology, Muscat 130, Oman

Abstract

Fishing wealth is one of the richest resources in the Sultanate of Oman. It is considered as one of the most important economic developments that nation depends on in a larger way. The Sultanate of Oman is characterized by the presence of a large fishing fleet as the number of fishing vessels and boats in it. Good research with the application of modern technology in fishermen boats is required to increase the quality of fishing by providing fishermen with a safe and secure fishing experience. Artificial intelligence (AI) in boat automation technology is new and it is a mandatory demand for Oman’s fisheries sector. At the time of fishing, there are a lot of problems fishermen face such as weather changes, border tracking, navigation, illegal fishing, pirate attack, oil spill, technical fault in boats, etc. Therefore, the application of AI and related techniques in boat automation, information sharing, and preparation of documentation resources is very important in this sector. The main requirement for a fisherman is a high-quality fishing boat with proper communication devices to provide all the required information to fishermen and the control room. In this paper, a review has been made on fishermen’s boats with artificial intelligence for a sustainable fishing experience ensuring safety, security, navigation, and sharing information for Omani fishermen.

Funder

research council Oman

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

Reference47 articles.

1. Fisheries and Aquaculture Department—FAO (2022, November 10). The Sultanate of Oman, Report by Food and Agriculture of United Nations. Available online: http://www.fao.org/figis/pdf/fishery/facp/OMN/en?title=FAO%20Fisheries%20%26%20Aquaculture%20%20Fishery%20and%20Aquaculture%20Country%20Profiles%20.

2. Rowan 2023 The role of digital technologies in supporting and improving fishery and aquaculture across the supply chain—Quo Vadis?;Neil;Aquac. Fish.,2023

3. Al Badi, H. (2022, July 10). E-System for Tracking Fishing Vessels and Boat in Oman. Oman Observer. Available online: https://www.omanobserver.om/article/1122019/business/economy/e-system-for-tracking-fishing-vessels-and-boats-in-oman.

4. NCSI (2022, November 10). Statistical Yearbook 2019: Issue 47, Available online: https://www.ncsi.gov.om/Elibrary/LibraryContentDoc/bar_Statistical%20Year%20Book_%207-5-2020_3d83f732-9fdf-4523-a64d-8c9dac8c19cb.pdf.

5. Al Kalbaniyeh, F., and Qanat, M. (2023, February 27). Sagueni: Maximize the Utilization of the Fisheries Sector to Provide 29 Thousand Jobs and Increase the Contribution to GDP and Economic Diversification. Available online: https://alroya.om/post/162280.

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