Implementation of Artificial Intelligence in Aquaculture and Fisheries: Deep Learning, Machine Vision, Big Data, Internet of Things, Robots and Beyond

Authors

DOI:

https://doi.org/10.47852/bonviewJCCE3202803

Keywords:

artificial intelligence, aquaculture, machine vision, Internet of Things, big data

Abstract

The aquaculture and fishery industry are multi-billion-dollar business across the globe, and the demand for aquatic species produce increases exponentially throughout these years. However, the depletion of aquaculture lands and aquatic pollution are some of the major worrying predicaments challenging the future of this industry. Sustainable growth strategies are the only way out, and they must come hand in hand with the implementation of artificial intelligence to achieve the desired outcome high throughput in short time periods. The intelligent fish farm and smart cage aquaculture management system are some of the fruits of this drive, and the system keeps improving to date. In this review, we provide recent updates over the past half-decade of artificial intelligence implementation in fishery and aquaculture in hope to provide highlights and future directions to push the industry to greater heights.

 

Received: 27 February 2023 | Revised: 28 March 2023 | Accepted: 14 April 2023

 

Conflicts of Interest

The author declares that he has no conflicts of interest to this work.

 

Data Availability Statement

Data available on request from the corresponding author upon reasonable request.


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Published

2023-04-19

Issue

Section

Review

How to Cite

Lim, L. W. K. (2023). Implementation of Artificial Intelligence in Aquaculture and Fisheries: Deep Learning, Machine Vision, Big Data, Internet of Things, Robots and Beyond. Journal of Computational and Cognitive Engineering, 3(2), 112–118. https://doi.org/10.47852/bonviewJCCE3202803