Through Facial Recognition technology – SAFR it is possible to detect the use of masks for COVID-19 through video analysis in real time, guaranteeing that all those who access a room or area use it and in the correct way.
With the expansion of the coronavirus since the end of 2019 and the COVID-19 pandemic, it is necessary for all people to comply with the health security measures in place and, among them, the use of masks. Wearing a hygienic face mask during this pandemic is a critical preventive measure and vital in circumstances where social distancing is difficult to maintain. Wearing a mask is essential, especially for those at higher risk of developing serious illness from COVID-19. Studies indicate that the spread of COVID-19 occurs mainly between people who are in immediate contact with each other and that it can be transmitted by people who have no symptoms and do not know they are infected.
The work of controlling this obligation becomes complicated when the transit of people in a facility is massive, or when this work is carried out by means of video surveillance systems. However, real-time video analysis through facial recognition and AI enables the exhaustive detection of people who do not use a sanitary mask or who do so incorrectly.
Facial Recognition technology – SAFR for mask detection allows to optimally control that the flow of visualized people are wearing a mask and activate the required alerts or alarms in real time.
Matches faces appearing on live video feeds in real-time with 98.87% accuracy so registered individuals are always spotted despite challenging real-world conditions. More accurate and faster than manual monitoring.
Provides a central knowledge bank of known faces and monitoring activity that’s always up to date. Consistent across distributed locations, simple to update to ensure records are correct, and easy to search to perform post-event analysis.
Get instant notifications when persons of interest are spotted. Customize notifications and alarms based on a variety of detection or recognition events and program automated security response workflows and SMS and email notifications.
Video analytics for forest fire detection is an innovative technology that has proven to be highly effective in forest fire prevention and control. One of the most prominent systems in this area is Watchman, developed by Grekkom.
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