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

05/19/2020
by   Douglas J. Leith, et al.
0

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.

READ FULL TEXT
research
11/09/2020

An Empirical Evaluation of Bluetooth-based Decentralized Contact Tracing in Crowds

Digital contact tracing is being used by many countries to help contain ...
research
12/21/2021

Hiding Signal Strength Interference from Outside Adversaries

The presence of people can be detected by passively observing the signal...
research
01/05/2021

Janus: Efficient and Accurate Dual-radio Social Contact Detection

Determining when two individuals are within close distance is key to con...
research
07/09/2020

Inferring proximity from Bluetooth Low Energy RSSI with Unscented Kalman Smoothers

The Covid-19 pandemic has resulted in a variety of approaches for managi...
research
06/07/2023

Deep Learning with Partially Labeled Data for Radio Map Reconstruction

In this paper, we address the problem of Received Signal Strength map re...
research
01/11/2022

Tackling Multipath and Biased Training Data for IMU-Assisted BLE Proximity Detection

Proximity detection is to determine whether an IoT receiver is within a ...
research
12/10/2019

Accurate Entrance Position Detection Based on Wi-Fi and GPS Signals Using Machine Learning

This paper aims at detecting an accurate position of the main entrance o...

Please sign up or login with your details

Forgot password? Click here to reset