# Museum Accessibility Through Wi-Fi Indoor Positioning

arXiv: https://arxiv.org/abs/2008.11340 · HTML: https://mlsanity.com/paper/2008.11340/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Aug 2020.

## Built on by (most cited first, 3 of 3)

- [Survey of Graph Neural Network for Internet of Things and NextG Networks](https://mlsanity.com/paper/2405.17309/) (2024)
- [IndoorGNN: A Graph Neural Network based approach for Indoor Localization using WiFi RSSI](https://mlsanity.com/paper/2312.07609/) (2023)
- [Cross-platform Smartphone Positioning at Museums](https://mlsanity.com/paper/2507.01469/) (2025)

## Abstract (arXiv)

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.