Abstract

Global seafood demand is increasing at a persistent rate to overcome food security issues. Traditional aquaculture methods are not enough to meet these increasing requirements. Therefore, new technologies using artificial intelligence have been introduced in small and large aqua farms. These technologies include IoT, 2D and 3D image detection, machine learning, robotics and computational technologies to overcome severe challenges faced by aqua farms. There are many challenges in the application of such AI techniques in aqua farms including, risks of data leakage, less reliability of stakeholders on AI methods, economic losses, knowledge and training gaps, incomplete information, ethical considerations and large amounts of data received which is again reviewed by peers, which then leads to a reduction in sustainable production. Integration of AI techniques with manual work helps in obtaining better production, enhancing fish growth and breeding, as well as careful monitoring of a complete ecosystem. From a future perspective, AI techniques play an important role in fish behavior analysis, early disease detection, genome sequencing, genome editing, efficient data-based decision making and fish species conservation which then leads to a more sustainable and efficient aquafarm. The involvement of stakeholders in careful monitoring of farming systems, government support and diverse aquaculture practices enhance farm production many times.