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Machine learning and cloud computing for remote monitoring of wave piercing catamarans: a case study using MATLAB on Amazon web services

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Shabani, B ORCID: 0000-0002-2910-962X, Ali-Lavroff, J ORCID: 0000-0001-5262-8666, Holloway, DS ORCID: 0000-0001-9537-2744, Penev, S, Dessi, D and Thomas, G 2020 , 'Machine learning and cloud computing for remote monitoring of wave piercing catamarans: a case study using MATLAB on Amazon web services', paper presented at the Smart Ship Technology Online Conference 2020, 14-15 October 2020, online.

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Abstract

Wave load cycles, wet-deck slamming events, accelerations and motion comfort are important considerations for high-speed catamarans operating in moderate to large waves. This paper provides an overview of data analytics methods and cloud computing resources for remotely monitoring motions and structural responses of a 111 m high-speed catamaran. To satisfy the data processing requirements, MATLAB Reference Architectures on Amazon Web Services (AWS) were used. Such combination enabled fast parallel computing and advanced feature engineering in a time-efficient manner. A MATLAB Production Server on AWS has been set up for near real-time analytics and execution of functions developed according to the class guidelines. A case study using Long Short-Term Memory (LSTM) networks for ship speed and Motion Sickness Incidence (MSI) is provided and discussed. Such data architecture provides a flexible and scalable solution, leading to deeper insights through big data processing and machine learning, which supports hull monitoring functions as a service.

Item Type: Conference or Workshop Item (Paper)
Authors/Creators:Shabani, B and Ali-Lavroff, J and Holloway, DS and Penev, S and Dessi, D and Thomas, G
Keywords: machine learning, cloud computing, remote monitoring, catamaran
Journal or Publication Title: Proceedings from the Smart Ship Technology Online Conference 2020
Publisher: The Royal Institution of Naval Architects
Copyright Information:

Copyright 2020 The Royal Institution of Naval Architects

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