Early detection of symptoms of COVID-19 infection is of utmost importance. In this project, we are focusing on early detection using thermal imaging cameras that allow for non-contact, non-invasive monitoring of temperature, heart rate and breathing rate. We propose to develop two solutions: 1. to detect early symptoms by detecting an increase in people’s temperature through crowd sensing and 2. to monitor the vital signs of elderly patients continuously using thermal cameras next to the places where they spend most of their time. These solutions will be based on advanced signal processing algorithms and machine learning models.

At the end of the project, we will provide a stand-alone solution that will include a thermal camera, processing hardware and our software and algorithms. This will represent a minimum viable product that will be taken by our industrial partner J&M Group and further developed into a commercial product.

This project is important for Canada because it addresses early detection of COVID-19 of both people who are active and might not know that they have COVID-19 symptoms as well as elderly people who are at their homes or retirement homes and require constant monitoring of their vital non-invasively.

Industry Partner(s):J&M Group

Academic Institution:University of Ottawa

Academic Researcher: Bolic, Miodrag

Focus Areas: AI, COVID-19, Health

Platforms: GPU