Distance Estimation for BLE-based Contact Tracing -- A Measurement Study
This addresses the problem of unreliable contact tracing for public health during pandemics like COVID-19, but it is incremental as it builds on existing wireless technologies.
The study tackled the challenge of inaccurate distance estimation for BLE-based contact tracing by conducting measurements in various scenarios, finding that BLE is not accurate enough for precise distance estimation but can detect contacts below 2.5 m with true positive rates of 0.65 (logarithmic model) and 0.54 (linear model).
Mobile contact tracing apps are -- in principle -- a perfect aid to condemn the human-to-human spread of an infectious disease such as COVID-19 due to the wide use of smartphones worldwide. Yet, the unknown accuracy of contact estimation by wireless technologies hinders the broader use. We address this challenge by conducting a measurement study with a custom testbed to show the capabilities and limitations of Bluetooth Low Energy (BLE) in different scenarios. Distance estimation is based on interpreting the signal pathloss with a basic linear and a logarithmic model. Further, we compare our results with accurate ultra-wideband (UWB) distance measurements. While the results indicate that distance estimation by BLE is not accurate enough, a contact detector can detect contacts below 2.5 m with a true positive rate of 0.65 for the logarithmic and of 0.54 for the linear model. Further, the measurements reveal that multi-path signal propagation reduces the effect of body shielding and thus increases detection accuracy in indoor scenarios.