Artificial Intelligence in marine technology: improving fishery management & biodiversity monitoring / Nor Aina Afrina Mohd Affandi ... [et al.]

Image identification has been transformed by artificial intelligence (AI) and machine learning (ML), which are essential to marine technology. Using Convolutional Neural Networks (CNNs) for feature extraction, preprocessing, and data collecting, image recognition allows machines to recognize and categorize fish species. Fish species identification, size and weight estimate, and ecosystem monitoring are important applications that support the preservation of marine biodiversity and sustainable fisheries. High accuracy, scalability, and real- time analysis is provided by the technology, which lowers human error and enhances decision-making. However, issues including fish overcrowding, biofouling, and water turbidity may disrupt system function. Despite these drawbacks, developments in AI-powered picture identification keep improving environmental sustainability, fishery management, and marine research. This study shows how image recognition is becoming more and more capable of improving marine technology and encouraging responsible resource management