A Wireless Low-power System for Digital Identification of Examinees (Including Covid-19 Checks)

Danilo Nunes, Klaus Volbert

2022

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 everyone 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.

Paper Citation

in Harvard Style

Nunes D. and Volbert K. (2022). A Wireless Low-power System for Digital Identification of Examinees (Including Covid-19 Checks). In Proceedings of the 11th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-551-7, pages 51-59. DOI: 10.5220/0010912800003118

in Bibtex Style

@conference{sensornets22,
author={Danilo Nunes and Klaus Volbert},
title={A Wireless Low-power System for Digital Identification of Examinees (Including Covid-19 Checks)},
booktitle={Proceedings of the 11th International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2022},
pages={51-59},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010912800003118},
isbn={978-989-758-551-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - A Wireless Low-power System for Digital Identification of Examinees (Including Covid-19 Checks)
SN - 978-989-758-551-7
AU - Nunes D.
AU - Volbert K.
PY - 2022
SP - 51
EP - 59
DO - 10.5220/0010912800003118