Efficient Detection of COVID-19 Exposure Risk

被引:0
|
作者
Nixon, Brian T. [1 ]
Alseghayer, Rakan [1 ]
Graybill, Benjamin [1 ]
Zhang, Xiaozhong [1 ]
Costa, Constantinos [1 ]
Chrysanthis, Panos K. [1 ]
机构
[1] Univ Pittsburgh, Dept Comp Sci, Pittsburgh, PA 15260 USA
来源
2022 23RD IEEE INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENT (MDM 2022) | 2022年
关键词
indoor; outdoor; congestion forecasting; contact tracing; spatio-temporal aggregate join;
D O I
10.1109/MDM55031.2022.00068
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this demo paper, we present the new module of our HealthDist system that performs contact tracing in a privacy-preserving manner and considers the COVID-19 exposure risk. This is achieved by answering a new spatio-temporal query, dubbed ST-Aggregate Join, which calculates the COVID-19 exposure risk of an individual on their devices. It utilizes a special-purpose access structure to record the trajectories of users on their devices and optimize the ST-Aggregate Join processing. We demonstrate interactively using a smartphone application how our system can provide effective contact tracing within a university campus. We also illustrate how our new module is working through an intuitive web interface that shows the exposure risk of a person by coloring the trajectory of the infected person and the person(s) in high risk in a preloaded real dataset.
引用
收藏
页码:310 / 313
页数:4
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