Detection of PPE in healthcare settings using machine learning

We propose utilizing real-time image detection of humans (visitors and healthcare workers) using personal protective equipment (I.e. masks, gloves, and gowns) in healthcare settings. This system would ensure proper compliance of PPE use to reduce the transmission COVID and other healthcare based infections, thereby saving lives, reducing hospital stays and costs. This builds off literature of the importance of strict adherence to best practices in hospitals as well as pathogen transmission from healthcare workers to patients via hospital uniforms. Authors of this work are students in AI program at Queens University.

Faculty Supervisor:

Tina Dacin

Student:

Amrit Sehdev;Shelley Lineham;Ruchika Julka;Eman Smadi;Ethan Wu

Partner:

Med Duck Solutions Inc.

Discipline:

Other

Sector:

Professional, scientific and technical services

University:

Queen's University