Page 110 - ITU Journal, Future and evolving technologies - Volume 1 (2020), Issue 1, Inaugural issue
P. 110
ITU Journal on Future and Evolving Technologies, Volume 1 (2020), Issue 1
shows that most Bluetooth-based contact tracing apps
use just the received signal strength indicator (RSSI)
of the Bluetooth for distance measurements. Unfor-
tunately, in practice, numerous factors can affect the
RSSI that can make the distance measurement inaccu-
rate, such as the power of the antenna used for broad- Advertising
casting (i.e., the TxPower) and the obstacles blocking 1
transmission paths. Moreover, Bluetooth-based proxim- 2 Connection
ity tracing can also raise false positives because of the
potential misinterpretation of various scenarios. For ex-
ample, a proximity tracing system may interpret two 3 Ultrasound Signal
users have contact even if they are separated by a solid
wall, where the risk of infection is much lower than the 4 Ultrasound Signal
risk indicated by the measured distance.
5 Ultrasound Data
Therefore, we would like to propose an improved ap- Exchange
proach by combining as many data sources as possible
in an integrated way, with the key objective of mini- 6 Disconnection
mizing false positives and false negatives in the contact
tracing and meanwhile protecting user’s privacy. The
contact tracing data we can collect includes (1) multi- Fig. 1 – A Simplified Protocol for Improved Data Exchange.
ple channels including both Bluetooth and ultrasound 2. IMPROVED DATA COLLECTION
(using both microphones and speakers available in the
smartphone), and multiple sources including (2) WiFi There are two fundamental objectives that a good digital
and (3) cellular networks if they are available. We show contact tracing system must satisfy: (1) it should be ef-
how we can use improved methodology to collect data fective in tracking an individual (e.g., few false positives
that is privacy aware, transparent, and integrated in and missed detections), and (2) it should protect the pri-
Section 2. vacy of users. For example, a CCTV footage would be
highly effective if (1) were the sole objective, however it
Similarly, while testing followed by quarantining/iso- does not meet (2) since it is too much privacy-invasive.
lation is a powerful tool against a pandemic such as Therefore, we must look for effective and privacy-aware
COVID-19, testing capacity remains an issue, especially digital contact tracing techniques.
in hard hit areas where testing results could take multi-
ple days, even up to a week, to arrive. While traditional Since the outbreak of Covid-19, numerous techniques
approaches have focused on testing individuals who ex- based on Bluetooth, WiFi, and cellular networks have
hibit symptoms or have come in contact with other in- been developed for contact tracing. Each technique has
fected individuals, these approaches miss out many po- its own pros and cons. For instance, Bluetooth based
tential areas of outbreak where asymptomatic or pre- solutions can achieve reliable communication and a low
symptomatic super-spreaders seed the virus, which gets energy operation, but these suffer from a high rate of
detected only after it has already spread significantly. false positives due to a long communication range. WiFi
Thus, testing capacity needs to be used judiciously to based solutions do not require installation of apps on
prevent widespread outbreaks. In Section 4, we argue mobile phones, and they rely heavily on access point
that the current myopic approach to testing focuses on (AP) deployment, and its coverage. Therefore, in this
identifying individuals with the highest probability of paper, we aim to present an integrated approach that
being infected, which does not help minimize the over- improves the accuracy of a Bluetooth-based approach
all number of infected individuals. with additional channels, and combines WiFi and cel-
Organization. The rest of this paper is organized as lular information if they are available. Furthermore by
utilizing clever algorithms that are provably optimal, it
follows: In Section 2, we describe an improved and inte- aims to increase the efficiency with which infected indi-
grated methodology to collect contact tracing data. In viduals are contained early without infecting too many
Section 3, we describe techniques that enable us to effi- of their “neighbors”.
ciently integrate the data collected from various streams.
This allows us to reduce the “error probabilities” asso- Improving Bluetooth-based Contact Tracing
ciated with false alarms or missed detection of diseases, with Ultrasound Signals. Since Bluetooth-signals
and generate a dynamic susceptibility graph. In Sec- can penetrate obstacles such as solid walls, and also
tion 4, we address the practical problem of testing un- have a long transmission range, we would like to leverage
der constraints on resources. We perform simulations to other sensors in a smartphone to improve its proximity
show necessities of contact tracing and building a con- accuracy. In particular, we can use the inaudible ultra-
tact graph in Section 5, and conclude in Section 6. sound generated from the speaker and recorded by the
90 © International Telecommunication Union, 2020