Remote Monitoring of Production Operations During COVID-19 using a Smart Gateway Device

Since the COVID-19 outbreak, social distancing became the most effective approach to guarantee safety. In manufacturing operations this has been achieved through a work from home policy for non-essential personnel and staggered shift operations for essential personnel. However, it is near impossible to track essential personnel compliance to social distancing as well as optimize production operations manually due to the COVID-19 safety restrictions. Therefore, automated computer-vision-based alternatives have attracted interest for such applications. This project is expected to address this challenge by developing a platform to monitor social distancing using fog computing and deep learning.

Intern: 
Mohammad Anvaripour
Faculty Supervisor: 
Afshin Rahimi
Province: 
Ontario
Partner: 
Partner University: