Artificial Intelligence Applications in Fish Classification and Taxonomy: Advancing Our Understanding of Aquatic Biodiversity

Abstract

The purpose of this research study is determining that artificial intelligence applications related to the fish classification also that taxonomy. Research describes that aquatic biodiversity between them. The research measure that advancing aquatic biodiversity related to the fish classification and taxonomy. Artificial intelligence (AI) systems surpass traditional human-centered methods in the rapid and accurate identification of fine-grained morphological features by analyzing massive datasets. The descriptive statistic, smart PLS Algorithm model related to them. As a result, this gives conservationists useful knowledge to take on new tasks and protect endangered species. It is emphasised that this technological breakthrough depends on ethical concerns and the appropriate use of AI.  The paper also examines citizen science initiatives and public participation in the democratisation of AI-assisted fish identification. The educational component is examined, demonstrating how AI-driven technologies provide immersive learning environments that encourage a deeper understanding and appreciation of aquatic biodiversity. In conclusion, the ingenious partnership of artificial intelligence and fish taxonomy not only clarifies the secrets of the deep blue but also paves the road for a future in which environmental preservation and technological growth coexist together. The result founded that direct and significant link between fish classification and taxonomy related to the artificial intelligence. Result also founded that aquatic biodiversity between them. The various achievements of AI are highlighted in this research, along with the ways in which it might further our knowledge of and efforts to protect the great diversity of species found under the ocean's surface.