A deep learning-based method and system for processing marine environmental data

Xinggang Du; Daishan Wei; Bojie Fan

doi:10.1117/12.3035446

10 July 2024 A deep learning-based method and system for processing marine environmental data

Xinggang Du, Daishan Wei, Bojie Fan

Proceedings Volume 13223, Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024); 1322329 (2024) https://doi.org/10.1117/12.3035446
Event: 2024 5th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2024), 2024, Wuhan, China

Abstract

This paper introduces a deep learning-based method and system for processing marine environmental data, aiming to address data collection and fusion issues in marine environment monitoring. We collect marine environmental parameters, such as seawater temperature, conductivity, flow velocity, and wind speed, through multiple sensors, generating observational data. To ensure data accuracy, we employ a deep learning-based data cleaning method and the MTConnect data transformation method for data preprocessing to achieve cleaning and transformation. To further improve the effectiveness of data fusion, we utilize a swarm intelligence-based optimization algorithm, Particle Swarm Optimization (PSO), to optimize data from both temporal and spatial dimensions. This will provide more accurate and comprehensive support for marine science research, environmental protection, and resource development, offering a robust foundation for decision-making and marine management.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinggang Du, Daishan Wei, and Bojie Fan "A deep learning-based method and system for processing marine environmental data", Proc. SPIE 13223, Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024), 1322329 (10 July 2024); https://doi.org/10.1117/12.3035446

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