International Journal of Marine Science, 2024, Vol.14, No.3, 193-203 http://www.aquapublisher.com/index.php/ijms 193 Review and Progress Open Access Development and Application of Key Technologies in Marine Observation and Prediction ManmanLi Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China Corresponding email: 502684238@qq.com International Journal of Marine Science, 2024, Vol.14, No.3, doi: 10.5376/ijms.2024.14.0024 Received: 15 May, 2024 Accepted: 20 Jun., 2024 Published: 11 Jul., 2024 Copyright © 2024 Wang, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproductio4n in any medium, provided the original work is properly cited. Preferred citation for this article: Wang H.M., 2024, Development and application of key technologies in marine observation and prediction, International Journal of Marine Science, 14(3): 193-203 (doi: 10.5376/ijms.2024.14.0024) 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) 1 Introduction Marine observation and prediction are critical components of marine science, encompassing the monitoring and forecasting of various oceanic parameters such as sea surface temperature, ocean currents, and marine ecosystems. These activities are essential for understanding and managing the marine environment, which is increasingly impacted by human activities and climate change. Traditional methods of marine observation have relied heavily on physical models and in-situ measurements, but recent advancements in technology have introduced new tools and methodologies that enhance the accuracy and efficiency of these processes (Sarkar et al., 2020; Immas et al., 2021; Song et al., 2023). The integration of key technologies such as artificial intelligence (AI), the Internet of Things (IoT), and advanced sensing technologies has revolutionized marine observation and prediction. AI, for instance, has been applied to various aspects of marine science, including the identification of ocean phenomena and the prediction of ocean components, significantly improving the accuracy and scope of marine forecasts (Sarkar et al., 2020; Song et al., 2023). IoT has facilitated real-time monitoring of marine environments by enabling the deployment of interconnected sensors that collect and transmit data continuously (Xu et al., 2019). Additionally, advancements in underwater sensing technologies have allowed for more precise and extensive data collection, which is crucial for accurate marine ecosystem modeling and forecasting (Capotondi et al., 2019; Sun et al., 2021). This study aims to provide a comprehensive overview of the current state of research and technological advancements in marine observation and prediction, highlight the significant contributions of AI, IoT, and advanced sensing technologies in enhancing marine science, and identify the challenges and future directions in the application of these technologies for sustainable marine environment management. By synthesizing findings from multiple research studies, this study seeks to offer valuable insights into the evolving landscape of marine observation and prediction technologies and their potential to address pressing environmental challenges.
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