A Review on Integrated Artificial Intelligence Approaches for Sustainable Aquaculture

Abstract

As the aquaculture industry continues to expand, there is an increasing need to adopt modern tools to enhance productivity, sustainability, and decision-making. AI technologies are at the forefront of this transformation, offering solutions such as automation of tasks like water quality monitoring, feeding schedules, and disease detection, leading to improved operational efficiency and fish health. AI also aids in early disease detection and supports precision aquaculture by adjusting environmental variables like feeding and oxygen levels to optimize fish growth. However, the adoption of AI comes with challenges. The availability of quality data, the need for domain-specific datasets, and the complexity of AI models can hinder progress. High initial costs and infrastructure demands present obstacles for small-scale farmers. Ethical considerations, such as data privacy and responsible use of AI, also need careful attention. This article reviews the benefits and challenges of AI in aquaculture, highlighting the importance of adopting modern tools as the industry evolves and the barriers that must be addressed for successful implementation. It also discusses how AI can contribute to sustainable practices, improving efficiency while reducing environmental impact, and highlights the potential for AI to shape the future of aquaculture management.