The smart city reference pipeline integrates various media building blocks, with analytics powered by the OpenVINO™ Toolkit, for traffic or stadium sensing, analytics and management tasks. This Intel E2E sample implements aspects of smart city sensing, analytics and management features:

Camera Provisioning: Tag and calibrate cameras for installation locations, calibration parameters and other usage pattern information.

Camera Discovery: Discover and register IP cameras on specified IP blocks. Registered cameras automatically participate into the analytics activities. See Sensor Simulation and Discovery for additional details.

Recording: Record and manage segmented camera footage for preview or review (at a later time) purpose.

Analytics: Perform analytics on the live/recorded camera streams. Latency-sensitive analytics are performed on Edge while others are on cloud.

Triggers and Alerts: Manage triggers on analytics data. Respond with actions on triggered alerts.

Smart Upload and Archive: Trans code and upload only critical data to cloud for archival or further offline analysis.

Stats: Calculate statistics for planning/monitoring purpose on analytical data.

UI: Present above data to users/administrators/city planners.

Scenarios
These OpenVINO™ Toolkit Smart Cities Reference VM implements the Smart City traffic and Smart Stadium scenarios. The traffic scenario measures vehicle/pedestrian flow for planning purpose. The stadium scenario focuses on different access control techniques, including entrance people counting, service-point queue counting and stadium seating zone crowd counting.

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OpenVINO™ Smart-City Reference Implementation VMDace IT℠d/b/a Sense Traffic Pulse™

OpenVINO™ Smart-City Reference Implementation VM

Dace IT℠d/b/a Sense Traffic Pulse™

OpenVINO™ Smart-City Reference Implementation VM

Dace IT℠d/b/a Sense Traffic Pulse™

OpenVINO™ Smart-City Reference Implementation VM
Dace IT℠d/b/a Sense Traffic Pulse™