Dragonfruit Module
’s been widely acknowledged that face mask usage helps curtail the spread of COVID-19. Video data from existing surveillance cameras can be collected and, with the right AI object detection tools, face mask usage can be identified. Retailers, schools, hospitals, and other organizations are exploring face mask detection at key entryways and locales to ensure that people are following safety regulations. Dragonfruit’s face mask module easily overlays on top of existing surveillance infrastructure to detect and count mask usage. The resulting metrics can be used to improve mask-wearing policies to reduce exposure risk, with the ultimate goal of limiting the spread of COVID-19.
Dragonfruit easily identifies and keeps track of people who are wearing masks. Mask usage can be detected in a particular area (geofence) or at a virtual crossing (tripwire).
Dragonfruit can count the number of people who did or did not wear a mask during a specified time period (end of the day or end of the hour) based on your needs. Mask usage can be counted in a particular area (geofence) or across a virtual boundary (tripwire).
Dragonfruit sends reports with important metrics on mask usage so that you can have a better understanding of your workplace and implement appropriate policies during the pandemic.
