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SmartDistance: A Mobile-based Positioning System for Automatically Monitoring Social Distance
40th IEEE Conference on Computer Communications (IEEE INFOCOM) ; 2021.
Article in English | Web of Science | ID: covidwho-1522583
ABSTRACT
Coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic. Since COVID-19 spreads mainly via close contact among people, social distancing has become an effective manner to slow down the spread. However, completely forbidding close contact can also lead to unacceptable damage to the society. Thus, a system that can effectively monitor people's social distance and generate corresponding alerts when a high infection probability is detected is in urgent need. In this paper, we propose SmartDistance, a smartphone based software framework that monitors people's interaction in an effective manner, and generates a reminder whenever the infection probability is high. Specifically, SmartDistance dynamically senses both the relative distance and orientation during social interaction with a well-designed relative positioning system. In addition, it recognizes different events (e.g., speaking, coughing) and determines the infection space through a droplet transmission model. With event recognition and relative positioning, SmartDistance effectively detects risky social interaction, generates an alert immediately, and records the relevant data for close contact reporting. We prototype SmartDistance on different Android smartphones, and the evaluation shows it reduces the false positive rate from 33% to 1% and the false negative rate from 5% to 3% in infection risk detection.

Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: 40th IEEE Conference on Computer Communications (IEEE INFOCOM) Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: 40th IEEE Conference on Computer Communications (IEEE INFOCOM) Year: 2021 Document Type: Article