Abstract
The COVID-19 pandemic has spurred the development of a large number of automated and semi-automated contact tracing frameworks. Many of these are reactive and require active client participation, such as installing a specific contact tracing app on the clients’ smartphones, and they are often unable to scale in time to reach the requisite critical mass adoption. To be better prepared for the emergence and re-emergence of coronavirus epidemics, we seek to leverage on the availability of common existing digital infrastructure such as the increasingly ubiquitous Wi-Fi networks that can be readily activated to assist in large-scale contact tracing. We present and discuss the design, implementation, and deployment of a data warehouse of Wi-Fi sessions for contact tracing and disease outbreak investigation. We discuss the conceptual design of the data warehouse and present the logical model that implements the conceptual model. We describe the data staging procedures and discuss the analysis of the Wi-Fi session data for mobility-based contact tracing and disease outbreak investigation. Finally, we present the case where the data warehouse of Wi-Fi sessions is experimentally deployed at full scale on a large local university campus in Singapore.
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Notes
- 1.
All of the spatial data types are defined in more details in [13].
- 2.
Again, all of the temporal data types are defined in more details in [13].
- 3.
As opposed to devices that might not be in the possession of an individual while connected to the network (e.g. a laptop computer in the library could be connected to the network while the individual is away for lunch).
- 4.
[18] mentions that mobile devices are likely to stay connected to the network while an individual is walking, but laptops and similar devices likely hibernate while the individual is on the move. Laptops are also likely to remain static in the workplace overnight, while mobile devices are almost always in the possession of an individual.
- 5.
Latest data at the time of writing of this document.
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Zagatti, G.A., Ng, SK., Bressan, S. (2021). A Data Warehouse of Wi-Fi Sessions for Contact Tracing and Outbreak Investigation. In: Hameurlain, A., Tjoa, A.M. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVIII. Lecture Notes in Computer Science(), vol 12670. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-63519-3_4
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