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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 |
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. |
Cobertura geográfica: | Museo Nacional de Artes Visuales (MNAV), Departamento de Montevideo, Uruguay. |
Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | ||
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BGNCL20.pdf | Preprint | 1,07 MB | Adobe PDF | Visualizar/Abrir |
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