Organizations around the world have created coronavirus-tracking tools to monitor COVID-19 cases through real-time analytics. An FIU professor, who specializes in theoretical optimization and learning algorithms, and his research team at FIU, have created a dashboard that can predict the number of cases and deaths from COVID-19 using data analytics.
The tool, created by M. Hadi Amini, assistant professor, and his research team, including undergraduate researcher, Meleik Hyman, and doctoral student, Ahmed Imteaj, from the School of Computing and Information Sciences within the College of Engineering & Computing, forecasts the cases of COVID-19 worldwide.
The dashboard allows users to select a specific country or city on a global map. The map shows data reflecting the confirmed number of cases and deaths, and the number of recovered patients.
“I’m fascinated by data and knew we needed to adapt to the new situation we’re all facing,” said Amini. “My students and I were observing the current dashboards available online and how they show real-time data. But, we were looking to design something predictive that could be understandable for everyone.”
The data found in the dashboard predicts daily and is updated frequently using spatiotemporal data collection. Spatiotemporal data collection refers to the process of discovering patterns and knowledge of data that describes a phenomenon in a particular location and period of time. Typical examples include uncovering weather patterns, hurricane prediction and climate change trends. In this case, Amini is using it for COVID-19 patterns.
Read more at FIU News.