Open AccessData Learning of Fluid Dynamics for Physically Informed Digital Twins
Author(s) -
Beatriz Moya,
Icíar Alfaro,
David González,
Francisco Chinesta,
Elías Cueto
Publication year - 2020
Publication title -
jornada de jóvenes investigadores del i3a
Language(s) - English
Resource type - Journals
ISSN - 2341-4790
DOI - 10.26754/jjii3a.4861
Subject(s) - augmented reality , computer science , dynamics (music) , human–computer interaction , artificial intelligence , multimedia , psychology , pedagogy
We present a novel realtime digital twin based on artificial intelligence to emulate physically sound fluid dynamics, and classify and recognise liquids, with information from video streamings. Results are presented with augmented reality techniques not only for friendly user interaction, but also to provide augmented information in manipulation tasks.