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 emphasized 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 
democratization 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.