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COVID-19 e-print

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[Submitted on 19 May 2020]

Title:Coronavirus Contact Tracing: Evaluating The Potential Of Using Bluetooth Received Signal Strength For Proximity Detection

Authors:Douglas J. Leith, Stephen Farrell
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Abstract: We report on measurements of Bluetooth Low Energy (LE) received signal strength taken on mobile handsets in a variety of common, real-world settings. We note that a key difficulty is obtaining the ground truth as to when people are in close proximity to one another. Knowledge of this ground truth is important for accurately evaluating the accuracy with which contact events are detected by Bluetooth LE. We approach this by adopting a scenario-based approach. In summary, we find that the Bluetooth LE received signal strength can vary substantially depending on the relative orientation of handsets, on absorption by the human body, reflection/absorption of radio signals in buildings and trains. Indeed we observe that the received signal strength need not decrease with increasing distance. This suggests that the development of accurate methods for proximity detection based on Bluetooth LE received signal strength is likely to be challenging. Our measurements also suggest that combining use of Bluetooth LE contact tracing apps with adoption of new social protocols may yield benefits but this requires further investigation. For example, placing phones on the table during meetings is likely to simplify proximity detection using received signal strength. Similarly, carrying handbags with phones placed close to the outside surface. In locations where the complexity of signal propagation makes proximity detection using received signal strength problematic entry/exit from the location might instead be logged in an app by e.g. scanning a time-varying QR code or the like.
Subjects: Signal Processing (eess.SP); Machine Learning (cs.LG); Networking and Internet Architecture (cs.NI)
Cite as: arXiv:2006.06822 [eess.SP]
  (or arXiv:2006.06822v1 [eess.SP] for this version)
  https://doi.org/10.48550/arXiv.2006.06822
arXiv-issued DOI via DataCite

Submission history

From: Douglas Leith [view email]
[v1] Tue, 19 May 2020 13:51:23 UTC (13,385 KB)
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