Abstract
The RE.S.I.STO project targets visitors of Pisa medieval city, with the goal of providing high-quality digital contents accessible with smart devices. We describe the design, implementation and the test phases of the RE.S.I.STO application, whose goal is to automatically detect the proximity between visitors and artworks. Proximity is detected with a set of algorithms based on the analysis of Bluetooth Low Energy beacons. We detail our experimental campaigns which reproduce several museum layouts of increasing complexity at two pilot sites, and we compute the performance of the implemented algorithms to detect the nearby artworks. In particular, we test our solution in a wide open space located in our research institute and by performing a real deployment at the Camposanto Monumentale located in Pisa (Italy). The obtained performance varies in the range of 40% to perfect accuracy, according to the complexity of the considered museum layouts. We also describe a set of stress and stability tests aimed at verifying the robustness of the application during the data collection process. Our results show that the mobile application is able to reduce the beacon loss rate, with an average value of 77% of collected beacons.
Highlights
With the growing number of IoT-ready devices and their rapid diffusion in our daily lives, in the last decades, we witnessed the pervasive adoption of mobile apps delivering location-based services [1]
Our mobile application relies on the Bluetooth Low Energy protocol and, on the iBeacon technology
We show the performance of the app both in terms of beacon loss rate, accuracy and F1 scores
Summary
With the growing number of IoT-ready devices and their rapid diffusion in our daily lives, in the last decades, we witnessed the pervasive adoption of mobile apps delivering location-based services [1]. In the last few years, a growing interest has been observed in research topics addressing the estimation of the location of mobile users both indoor and outdoor This goal still represents a challenging task for indoor scenarios, where solutions based on Global Navigation Satellite System (GNSS) are unfeasible. Estimating the location of a target requires the adoption of technologies and data analytic tools that most often cannot exploit satellites as walls, wireless signal interference and obstacles significantly reduce the strength of satellite signals in indoor settings. To overcome this issue, in the last years several methods have been proposed, exploiting different kinds of wireless signals and technologies. As a matter of fact, there is no standard de facto localization solution for indoor spaces ( to GPS), leading to a still active and attractive research question
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
