Smart fishery: A research review for sustainable fisheries in the age of AI

Abstract

The rapid expansion of the global population and its accompanying rise in seafood demand have propelled the aquaculture industry into a new era. This transition, however, is not without challenges, particularly in achieving efficient and sustainable fish farming. In response, the integration of artificial intelligence (AI) technologies has emerged as a transformative solution. This review paper explores the myriad ways AI is reshaping the landscape of aquaculture. From optimizing fish biomass detection through deep learning networks to enhancing accuracy in fish size and weight estimation using innovative image processing techniques, AI's impact is far-reaching. Object detection algorithms, such as YOLO (You Only Look Once) and SSD (Single Shot Detector), are harnessed for fish target detection, showcasing AI's role in underwater object recognition. Fish counting and species classification benefit from convolutional neural networks, offering potential for automated monitoring and management. The analysis extends the integration of data acquisition and sensing technologies, further propels AI's utility in aquaculture, enabling real-time monitoring and informed decision-making. This review encapsulates the pivotal role of AI in revolutionizing aquaculture practices, facilitating sustainable growth, and addressing the challenges of the modern seafood industry.