Data management for smart ship or how to reduce machine learning cost in IoS applications

Pérez Fernández, Rodrigo; Benayas Ayuso, Arturo y Pérez Arribas, Francisco Lázaro (2018). Data management for smart ship or how to reduce machine learning cost in IoS applications. En: "Smart Ship Technology 2018", 23 - 24 January 2018, Londres, United Kingdom. pp. 101-106.

Descripción

Título: Data management for smart ship or how to reduce machine learning cost in IoS applications
Autor/es:
  • Pérez Fernández, Rodrigo
  • Benayas Ayuso, Arturo
  • Pérez Arribas, Francisco Lázaro
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: Smart Ship Technology 2018
Fechas del Evento: 23 - 24 January 2018
Lugar del Evento: Londres, United Kingdom
Título del Libro: Proceedings of the Smart Ship Technology 2018
Fecha: 2018
Materias:
Escuela: E.T.S.I. Navales (UPM)
Departamento: Arquitectura, Construcción y Sistemas Oceánicos y Navales (Dacson)
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[img]
Vista Previa
PDF (Document Portable Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (617kB) | Vista Previa

Resumen

Shipbuilding process, generates a lot of information and data, which a priori makes it seem impossible to have all this data in real time, but the new processors, simpler and smaller, with a good connection to the Internet, make it possible. The data management is, however, only one side of the coin of the Internet of Ships (IoS). Energy efficiency is a fundamental aspect also in new devices that connect to the network. But IoS not only covers the stages of design or production of the boat. Once the sensors are in the components whose information want to monitor, we will be able to obtain information throughout the life of the ship. IoS is presented as a solution capable of detecting when a component on a boat is close to fail and must be replace, when we take the boat to repair when we have to paint again, when corrosion has reached a certain limit ... and all this from our pocket tool and early enough to avoid late or unforeseen performances. IoS reaches this sector to ensure profitable production, or safe, efficient and sustainable process for all types of fishing vessels, tugboats, tankers, charges, ferries, dredgers and oceanographic ... Data management in Smart Ships, including collect, process, saving and third party distribution should be regulated, controlled and done in the most efficient and secure way for the ship owner. This can be accomplished based on a deep study of each part which is involved in close-to-real response systems and its machine-learning control unit. In this Systems, each parameter change generates stress and material fatigue, reducing its lifecycle.

Más información

ID de Registro: 52231
Identificador DC: http://oa.upm.es/52231/
Identificador OAI: oai:oa.upm.es:52231
Depositado por: Memoria Investigacion
Depositado el: 14 Ene 2019 11:36
Ultima Modificación: 14 Ene 2019 11:36
  • InvestigaM
  • GEO_UP4
  • Open Access
  • Open Access
  • Sherpa-Romeo
    Compruebe si la revista anglosajona en la que ha publicado un artículo permite también su publicación en abierto.
  • Dulcinea
    Compruebe si la revista española en la que ha publicado un artículo permite también su publicación en abierto.
  • Recolecta
  • Observatorio I+D+i UPM
  • OpenCourseWare UPM