Measurement and analysis of visitors' trajectories in crowded museums
Pietro Centorrino, Alessandro Corbetta, Emiliano Cristiani, E. Onofri · arXiv (Cornell University) · 2019
We tackle the issue of measuring and analyzing the visitors' dynamics in crowded museums. We propose an IoT-based system -- supported by artificial intelligence models -- to reconstruct the visitors' trajectories throughout the museum spaces. Thanks to this tool, we are able to gather wide ensembles of visitors' trajectories, allowing useful insights for the facility management and the preservation of the art pieces. Our contribution comes with one successful use case: the Galleria Borghese in Rome, Italy.