id |
acadia20_94 |
authors |
Yoo, Wonjae; Kim, Hyoungsub; Shin, Minjae; J.Clayton, Mark |
year |
2020 |
title |
BIM-Based Automatic Contact Tracing System Using Wi-Fi |
doi |
https://doi.org/10.52842/conf.acadia.2020.1.094
|
source |
ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 94-101. |
summary |
This study presents a BIM-based automatic contact tracing method using a stations-oriented indoor localization (SOIL) system. The SOIL system integrates BIM models and existing network infrastructure (i.e., Wi-Fi), using a clustering method to generate roomlevel occupancy schedules. In this study, we improve the accuracy of the SOIL system by including more detailed Wi-Fi signal travel sources, such as reflection, refraction, and diffraction. The results of field measurements in an educational building show that the SOIL system was able to produce room-level occupant location information with a 95.6% level of accuracy. This outcome is 2.6% more accurate than what was found in a previous study. We also describe an implementation of the SOIL system for conducting contact tracing in large buildings. When an individual is confirmed to have COVID-19, public health professionals can use this system to quickly generate information regarding possible contacts. The greatest strength of this SOIL implementation is that it has wide applicability in largescale buildings, without the need for additional sensing devices. Additional tests using buildings with multiple floors are required to further explore the robustness of the system. |
series |
ACADIA |
type |
paper |
email |
|
full text |
file.pdf (1,198,143 bytes) |
references |
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last changed |
2023/10/22 12:06 |
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