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Toward Digitalization of Fishing Vessels to Achieve Higher Environmental and Economic Sustainability.
Uriondo, Zigor; Fernandes-Salvador, Jose A; Reite, Karl-Johan; Quincoces, Iñaki; Pazouki, Kayvan.
Afiliação
  • Uriondo Z; Energy Engineering Department, Faculty of Engineering of Bilbao, University of the Basque Country (UPV/EHU), Pza. Ingeniero Torres Quevedo 1, 48013 Bilbao, Spain.
  • Fernandes-Salvador JA; AZTI, Marine Research, Basque Research and Technology Alliance (BRTA), Txatxarramendi Ugartea z/g, 48395 Sukarrieta, Bizkaia, Spain.
  • Reite KJ; SINTEF Ocean, Trondheim 7010, Norway.
  • Quincoces I; AZTI, Marine Research, Basque Research and Technology Alliance (BRTA), Txatxarramendi Ugartea z/g, 48395 Sukarrieta, Bizkaia, Spain.
  • Pazouki K; Marine, Offshore and Subsea Technology Group, School of Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU U.K.
ACS Environ Au ; 4(3): 142-151, 2024 May 15.
Article em En | MEDLINE | ID: mdl-38765058
ABSTRACT
Fishing vessels need to adapt to and mitigate climate changes, but solution development requires better information about the environment and vessel operations. Even if ships generate large amounts of potentially useful data, there is a large variety of sources and formats. This lack of standardization makes identification and use of key data challenging and hinders its use in improving operational performance and vessel design. The work described in this paper aims to provide cost-effective tools for systematic data acquisition for fishing vessels, supporting digitalization of the fishing vessel operation and performance monitoring. This digitalization is needed to facilitate the reduction of emissions as a critical environmental problem and industry costs critical for industry sustainability. The resulting monitoring system interfaces onboard systems and sensors, processes the data, and makes it available in a shared onboard data space. From this data space, 209 signals are recorded at different frequencies and uploaded to onshore servers for postprocessing. The collected data describe both ship operation, onboard energy system, and the surrounding environment. Nine of the oceanographic variables have been preselected to be potentially useful for public scientific repositories, such as Copernicus and EMODnet. The data are also used for fuel prediction models, species distribution models, and route optimization models.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ACS Environ Au Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ACS Environ Au Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Espanha