Review and Progress

Development and Application of Key Technologies in Marine Observation and Prediction  

May Wang
Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China
Author    Correspondence author
International Journal of Marine Science, 2024, Vol. 14, No. 3   
Received: 15 May, 2024    Accepted: 20 Jun., 2024    Published: 11 Jul., 2024
© 2024 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

This study explores the development and application of key technologies in marine observation and prediction, presenting a comprehensive analysis of the advancements and their impacts on marine science. The key findings highlight the roles of technologies such as remote sensing technology, acoustic monitoring, and the Internet of Things (IoT) in ocean observations. The integration of artificial intelligence (AI) and machine learning (ML) with traditional numerical models has significantly improved prediction accuracy and efficiency. By reviewing the successful implementation cases of Drifting Buoys, Satellite Remote Sensing, High-Frequency Radar (HFR), Autonomous Underwater Vehicles (AUVs) and Ocean Gliders, this study demonstrates the significant contributions of these technologies to marine environmental monitoring and summarizes the lessons learned from field applications. This research highlights the importance of integrating multiple technologies to enhance marine scientific research and environmental management by showcasing the latest advancements and practical applications in marine observation and prediction technologies, providing valuable insights and recommendations for future research.

Keywords
Marine observation; Remote sensing technology; Prediction technology; Artificial intelligence (AI); Machine learning (ML)
[Full-Flipping PDF] [Full-Text HTML]
International Journal of Marine Science
• Volume 14
View Options
. PDF
. FPDF(win)
. FPDF(mac)
. HTML
. Online fPDF
Associated material
. Readers' comments
Other articles by authors
. May Wang
Related articles
. Marine observation
. Remote sensing technology
. Prediction technology
. Artificial intelligence (AI)
. Machine learning (ML)
Tools
. Post a comment