Wirelessly COVID-19 Patient Tracking and Risk Assessment Using Edge AI Platform

The ability of the health system to manage a massive influx of patients is based on the combination of four factors: the personnel, the equipment, the physical spaces and the system in place. A combination better known in jargon as the 4 "S" (staff, stuff, structure / space, system). A fifth factor that is often misunderstood is synchronicity. With great adaptation to the workspace and team structures, a newly trained staff with new equipment, and a system of critical processes that evolve according to the evolution of the environment and the healthcare system status, synchronicity is essential. This synchronicity requires real time data and automations to enable already pressured teams and a stressed healthcare organization to adapt to unforeseen requests and needs.

In this project, we want to rapidly assess the risk of COVID-19 infection of people living in a building or healthcare facilities through analyzing their distance to other people who might or might not have been in contact with COVID-19 patients. This will be achieved with the help of wireless data collection, and artificial intelligence algorithms running on the hardware and software platform located within or in proximity to the building.

Intern: 
Ghazaleh Boroomand;Sana Alsadat Razavi
Faculty Supervisor: 
Brigitte Jaumard;Kim-Khoa Nguyen
Province: 
Quebec
Partner University: 
Program: