Contact Tracing in Healthcare Settings During the COVID-19 Pandemic Using Bluetooth Low Energy and Artificial Intelligence—A Viewpoint
Título
Contact Tracing in Healthcare Settings During the COVID-19 Pandemic Using Bluetooth Low Energy and Artificial Intelligence—A Viewpoint
Autor
Guanglin Tang, Kenneth Westover, Steve Jiang
Descripción
The COVID-19 pandemic has inflicted great damage with effects that will likely linger for a long time. This crisis has highlighted the importance of contact tracing in healthcare settings because hospitalized patients are among the high risk for complications and death. Moreover, effective contact tracing schemes are not yet available in healthcare settings. A good contact tracing technology in healthcare settings should be equipped with six features: promptness, simplicity, high precision, integration, minimized privacy concerns, and social fairness. One potential solution that addresses all of these elements leverages an indoor real-time location system based on Bluetooth Low Energy and artificial intelligence.
Fecha
2021
Materia
covid-19, contact-tracing, artificial intelligence, deep learning, Bluetooth, real-time location system
Identificador
10.3389/frai.2021.666599
Fuente
Epidemiology and Health
Editor
Korean Society of Epidemiology
Cobertura
Electronic computers. Computer science
Archivos
Colección
Citación
Guanglin Tang, Kenneth Westover, Steve Jiang, “Contact Tracing in Healthcare Settings During the COVID-19 Pandemic Using Bluetooth Low Energy and Artificial Intelligence—A Viewpoint,” SOCICT Open, consulta 21 de abril de 2026, https://socictopen.socict.org/items/show/6424.
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