Abstract

This paper discusses the evolution and application of intelligent systems in extracting ocean internal wave parameters, with special emphasis on the advancements enabled by remote sensing technologies. It investigates historical development, their role in improving data accuracy, efficiency in measurement, challenges in current methodologies, and potential improvements for future systems. The study, using qualitative research methods such as literature reviews and case studies, highlights advancements in intelligent systems, especially in real-time data processing and algorithmic enhancements. Findings show that there is significant improvement in the accuracy of data and efficiency in measurement, which is driven by modern remote sensing technologies and adaptive algorithms. However, challenges persist in integrating diverse data sources and adapting to dynamic oceanographic conditions. This paper concludes with the proposal for the incorporation of machine learning techniques and the development of adaptive algorithms to solve the problems presented. This work contributes further to the knowledge of intelligent systems' transformative potential, especially in oceanographic studies, for parameter extraction of ocean internal waves.