Using artificial intelligence to track and destroy COVID-19 on surfaces
Share this story

Ultraviolet-C light can disinfect surfaces against pathogens such as COVID-19 but existing delivery methods miss high-risk ‘shadow’ regions – the undersides of surfaces and doorknobs. York University is addressing this problem with agile, fully autonomous robots driven by artificial intelligence.

The robots use learning algorithms to visually monitor a room for human activity, building a map of high-risk areas. Then they autonomously tour the room, optimally orienting UV-C LED panels to disinfect high-risk surfaces, including those not reachable by existing systems. James Elder, a Lassonde School of Engineering Professor, is leading the project in partnership CrossWing Inc., Baycrest Health Sciences, Mon Sheong Home and Southlake Regional Health Centre. Funding comes from the Canada Foundation for Innovation.

By ensuring maxim efficiency and coverage, this novel technology can reduce infection rates at hospitals and long-term care facilities.

For more information, visit York University.

“Our researchers are called to serve the public through exploration and discovery and together with our partners in industry, government and community organizations, we are embracing our role in aiding the world’s recovery from the pandemic.”
Amir Asif
Vice-President Research & Innovation, York University
More Stories
New program helps provide students with job-ready skills
Bringing Lakehead University to Orillia
Protecting home owners from flooding