REDUCED TCO, FASTER ALERTING AND GREATER FLEXIBILITY IN DEPLOYMENT OPTIONS FOR REAL-TIME ANALYTICS
The new hybrid deployment option for the BriefCam platform; edge video processing on Axis deep learning cameras, reduces the total cost of ownership of a real-time video analytics deployment, enables operation in low-bandwidth environments, and makes for faster real-time alerting.
BriefCam analytics, enabled on the Axis deep learning cameras include the AXIS P3255 and AXIS Q1615 Mk III, which features a dual chipset of ARTPEC-7 and a deep-learning processing unit (DLPU), as well as the ARTPEC 8 camera series. By enabling BriefCam analytics on the edge, along with post processing and management capabilities, users experience up to six times faster real-time alerting, a 5-10x reduction in bandwidth, and up to 55% less real-time GPU processing servers for real-time processing. In turn, enabling greater flexibility and cost efficiency for large scale or distributed video analytics deployments.
THE HYBRID DEPLOYMENT MODEL
BriefCam Video Analytics enabled on Axis Deep Learning Cameras enables a new, flexible hybrid deployment model to transform video surveillance into valuable insights. BriefCam’s complete, comprehensive video analytics platform is optimized when combined with Axis Deep Learning Cameras for real-time use. The result, a hybrid Solution including on-camera pre-processing and server based post-processing.
Reduction in TCO
Utilize up to 55% less GPU’s for real-time processing, significantly reducing the hardware footprint and processing power required for real-time video analytics.
Flexible Deployment Options
Enables 5-10x less network bandwidth by transmitting only metadata from the Deep Learning camera to the Post Processing Server for real-time alerts.
Faster Real-Time Alerts
Experience up to 6x faster real-time alerts for greater situational awareness.