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Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/20.500.12008/27048 Cómo citar
Título: Museum accessibility through Wi-Fi indoor positioning.
Autor: Bracco, Antonio
Grunwald, Federico
Navcevich, Agustín
Capdehourat, Germán
Larroca, Federico
Tipo: Preprint
Palabras clave: Localization, Machine learning, Open source, Computers and Society
Cobertura geográfica: Museo Nacional de Artes Visuales (MNAV), Departamento de Montevideo, Uruguay.
Fecha de publicación: 2020
Resumen: Accessibility has long been a primary concern for major museums around the world. This is no exception for the Museo Nacional de Artes Visuales (MNAV, National Museum of Visual Arts) in Uruguay. Having a special interest in achieving accessibility for visually impaired visitors, the MNAV sought to implement a new system to allow these visitors a seamless tour around a new exhibit. We present here the system we developed and the lessons we learned from its deployment and usage. In particular, we used Wi-Fi indoor positioning techniques, so that visually impaired visitors could hear relevant audios through an Android app from their own smartphones based on their location inside the museum. The system was further adapted and used to assist the general public during their visits, allowing access to texts, audios and images according to their position. We furthermore share the complete source code and the dataset used to train the system
Editorial: arXiv
EN: Computing Research Repository (CoRR), arXiv:2008.11340, pp 1-7, aug 2020
Citación: Bracco, A., Grunwald, F., Navcevich, A. y otros. Museum accessibility through Wi-Fi indoor positioning [Preprint]. EN: Computing Research Repository (CoRR), pp 1-7, aug 2020. arXiv:2008.11340.
Licencia: Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Aparece en las colecciones: Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica

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