Meyer S, Windisch T, Perl A, Dzibela D, Marzilger R, Witt N, Benzler J, Kirchner G, Feigl T (2021)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2021
Publisher: IEEE Xplore
Pages Range: 1-8
Conference Proceedings Title: Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN 2021)
DOI: 10.1109/IPIN51156.2021.9662591
Digital Contact Tracing (CT) protocols based on Bluetooth are best implemented at the system level to save resources and preserve security aspects. Combined with a government-monitored software platform, these CT-protocols can then be used to support controlling pandemics such as COVID-19. However, it is unclear how these protocols have to be parameterized to ensure the most accurate and reliable CT.
This paper describes how we derived optimal parameters for a decentralized CT from extensive measurement campaigns that we carried out together with Deutsche Telekom (DT) and SAP under the supervision of the Robert Koch Institut (RKI). We examined the Google/Apple Exposure Notification Framework (ENF), which in combination with the front-end, i.e., the German Corona-Warn-App (CWA), enables digital CT in Germany. With centimeter accurate optical reference systems we show that optimal parameters are application-specific. However, they cause impractical high resource costs. In contrast, optimized general parameters offer an everyday compromise between energy costs, applicability, accuracy, and reliability of the ENF.
APA:
Meyer, S., Windisch, T., Perl, A., Dzibela, D., Marzilger, R., Witt, N.,... Feigl, T. (2021). Contact Tracing with the Exposure Notification Framework in the German Corona-Warn-App. In Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN 2021) (pp. 1-8). Lloret de Mar, ES: IEEE Xplore.
MLA:
Meyer, Steffen, et al. "Contact Tracing with the Exposure Notification Framework in the German Corona-Warn-App." Proceedings of the 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Lloret de Mar IEEE Xplore, 2021. 1-8.
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