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How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends
Abstract
Illegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported. A key role in this topic is played by machine learning algorithms which exploit data provided by classical and high-tech sensors, devices and systems such as for example: CCTV, onboard cameras placed on autonomous vehicles, Global Positioning Systems, radars, Automatic Identification Systems, Vessel Monitoring Systems, or Coastal Surveillance Systems. The main objective of this paper is to provide the reader with knowledge about the scale of this phenomenon, methods to tackle the issue, and the current state of research on the subject. This has been achieved through a review of existing approaches that deal with these harmful phenomena by using dedicated artificial intelligence and machine learning tools, as well as the accompanying equipment and devices. In addition, flaws and gaps in current methods, and future directions are disscussed.
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- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/ACCESS.2022.3212384
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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IEEE Access
no. 10,
pages 112539 - 112554,
ISSN: 2169-3536 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Klawikowska Z., Ujazdowski T., Grochowski M., Piotrowski R.: How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends// IEEE Access -Vol. 10, (2022), s.112539-112554
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/access.2022.3212384
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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