Engineering: leader della Digital Transformation
Respecting the social distancing in order to protect public health
Safe Eye is our AI based, Video & Picture analysis solution to monitor that social distancing measures are maintained by people in public places. It can be used to protect public health by helping people to respect social distancing measures in the post COVID’s lockdown phase.
How does it work
The solution, thanks to AI & Advanced Analytics technology, provides an end-to-end video and image-based, real time 24 x 7, analysis of humans and objects to recognize / detect / highlight potentially harmful behavior in public places (such as squares, streets, offices, stations, shops, public transport and generally wherever video and image systems can be leveraged). If social distancing measures are not respected the solution can automatically generate warning messages (push messages, calls, screen warnings, etc..) to those who are entitled to monitor those areas.
Benefits and Applications
Safe Eye calculates the distance among people within a certain (limited) area, measuring the density of population within the area (the camera’s shot), and sends overcrowding warnings if the social distance measure is not adequate. It also checks if Personal Protective Equipment (PPE) is actually and correctly worn. It addresses in particular to the following areas: Transportation
- Queues in and outside underground sites
- Queues in and outside entrance
- On shopping floors/premises/offices
- Playing sports.
GDPR Compliancy and predictive analytics
No specific personal information is ever extracted (face recognition, video identification, etc.) as the solution is recognizing situations and not specific people. Obviously, if needed and where allowed, according to GDPR laws, all the video and detected information can be stored and used as permitted by law. So, if needed, the stream and/or the pictures together with the events can be further analyzed, by applying predictive models in order to forecast the patterns that bring to crowd or, more basically, to get better refinements on the recognition.