Authors:
Danilo Weber Nunes
and
Klaus Volbert
Affiliation:
Faculty of Computer Science and Mathematics, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany
Keyword(s):
Indoor Navigation, Indoor Localisation, Low-power Devices, Internet of Things, RSSI, BLE Beacons.
Abstract:
Indoor localization has been, for the past decade, a subject under intense development. There is, however, no currently available solution that covers all possible scenarios. Received Signal Strength Indicator (RSSI) based methods, although the most widely researched, still suffer from problems due to environment noise. In this paper, we present a system using Bluetooth Low Energy (BLE) beacons attached to the desks to localize students in exam rooms and, at the same time, automatically register them for the given exam. By using Kalman Filters (KFs) and discretizing the location task, the presented solution is capable of achieving 100% accuracy within a distance of 45cm from the center of the desk. As the pandemic gets more controlled, with our lives slowly transitioning back to normal, there are still sanitary measures being applied. An example being the necessity to show a certification of vaccination or previous disease. Those certifications need to be manually checked for everyon
e entering the university’s building, which requires time and staff. With that in mind, the automatic check for Covid certificates feature is also built into our system.
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