Researchers at technology company Synergies Intelligent Systems and Germany's Universität Hamburg have developed a machine learning algorithm that can identify which people in a moving crowd are most likely asymptomatic carriers of Covid-19.
The continuous learning and inference of individual probability (CLIIP) algorithm bases its predictions on global positioning system (GPS)-tracked movement of people in a city, and known cases of infection.
CLIIP's accuracy relies on people using a GPS-based smartphone application that tracks their location to within a meter (3.2 feet), and logging their positive viral test results.
Synergies' Michael Chang said, "With this type of technology, we can quarantine a very small fraction of people—just 3% to 5%—and pretty effectively reduce the effect of the disease."
From IEEE Spectrum
View Full Article
Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA
No entries found