Selected article for: "low address and machine learning"
Author: Gonz'alez, Santiago; Garc'ia, Alvaro; N'unez, Ana
Title: CONECT4: Desarrollo de componentes basados en Realidad Mixta, Realidad Virtual Y Conocimiento Experto para generaci\'on de entornos de aprendizaje Hombre-M\'aquina
  • Cord-id: 1iawwfgo
  • Document date: 2021_5_24
    • ID: 1iawwfgo
    Snippet: This work presents the results of project CONECT4, which addresses the research and development of new non-intrusive communication methods for the generation of a human-machine learning ecosystem oriented to predictive maintenance in the automotive industry. Through the use of innovative technologies such as Augmented Reality, Virtual Reality, Digital Twin and expert knowledge, CONECT4 implements methodologies that allow improving the efficiency of training techniques and knowledge management in
    Document: This work presents the results of project CONECT4, which addresses the research and development of new non-intrusive communication methods for the generation of a human-machine learning ecosystem oriented to predictive maintenance in the automotive industry. Through the use of innovative technologies such as Augmented Reality, Virtual Reality, Digital Twin and expert knowledge, CONECT4 implements methodologies that allow improving the efficiency of training techniques and knowledge management in industrial companies. The research has been supported by the development of content and systems with a low level of technological maturity that address solutions for the industrial sector applied in training and assistance to the operator. The results have been analyzed in companies in the automotive sector, however, they are exportable to any other type of industrial sector. -- -- En esta publicaci\'on se presentan los resultados del proyecto CONECT4, que aborda la investigaci\'on y desarrollo de nuevos m\'etodos de comunicaci\'on no intrusivos para la generaci\'on de un ecosistema de aprendizaje hombre-m\'aquina orientado al mantenimiento predictivo en la industria de automoci\'on. A trav\'es del uso de tecnolog\'ias innovadoras como la Realidad Aumentada, la Realidad Virtual, el Gemelo Digital y conocimiento experto, CONECT4 implementa metodolog\'ias que permiten mejorar la eficiencia de las t\'ecnicas de formaci\'on y gesti\'on de conocimiento en las empresas industriales. La investigaci\'on se ha apoyado en el desarrollo de contenidos y sistemas con un nivel de madurez tecnol\'ogico bajo que abordan soluciones para el sector industrial aplicadas en la formaci\'on y asistencia al operario. Los resultados han sido analizados en empresas del sector de automoci\'on, no obstante, son exportables a cualquier otro tipo de sector industrial.

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