Deep Learning Test Platform for Maritime Applications: Development of the eM/S Salama Unmanned Surface Vessel and Its Remote Operations Center for Sensor Data Collection and Algorithm Development

Author:

Kalliovaara Juha12ORCID,Jokela Tero1ORCID,Asadi Mehdi1ORCID,Majd Amin1ORCID,Hallio Juhani1ORCID,Auranen Jani1ORCID,Seppänen Mika1,Putkonen Ari1ORCID,Koskinen Juho1ORCID,Tuomola Tommi1ORCID,Mohammadi Moghaddam Reza3ORCID,Paavola Jarkko1ORCID

Affiliation:

1. School of ICT, Turku University of Applied Sciences, 20520 Turku, Finland

2. Department of Computing, University of Turku, 20014 Turku, Finland

3. Independent Researcher, Mashhad 1696700, Iran

Abstract

In response to the global megatrends of digitalization and transportation automation, Turku University of Applied Sciences has developed a test platform to advance autonomous maritime operations. This platform includes the unmanned surface vessel eM/S Salama and a remote operations center, both of which are detailed in this article. The article highlights the importance of collecting and annotating multi-modal sensor data from the vessel. These data are vital for developing deep learning algorithms that enhance situational awareness and guide autonomous navigation. By securing relevant data from maritime environments, we aim to enhance the autonomous features of unmanned surface vessels using deep learning techniques. The annotated sensor data will be made available for further research through open access. An image dataset, which includes synthetically generated weather conditions, is published alongside this article. While existing maritime datasets predominantly rely on RGB cameras, our work underscores the need for multi-modal data to advance autonomous capabilities in maritime applications.

Funder

European Regional Development Fund

Finnish Ministry of Education and Culture in Applied Research Platform for Autonomous Systems

Finnish Ministry of Education and Culture

Business Finland in 5G-Advanced for Digitalization of Maritime Operations (ADMO) project

Publisher

MDPI AG

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