Smart Intersection#
The Smart Intersection sample application uses edge AI to improve the traffic flow. It combines feeds from multiple cameras to track vehicles from different angles, analyze their speed and direction, and understand interactions in real space. The system can be implemented with existing cameras and deliver real-time, coordinated insights for smarter traffic monitoring.
Example Use Cases
Pedestrian Safety: enhance safety for people crossing the street. The system tracks pedestrians at crosswalks and generates alerts when people walk outside safe crossing areas.
Traffic Flow Monitoring: count vehicles and measure dwell time in each lane, detecting when vehicles stay in their lanes for too long. This identifies stalled cars, accidents, and traffic jams.
Key Benefits
Multi-camera multi-object tracking: enables tracking of objects across multiple camera views.
Scene-based analytics: regions of interest that span multiple views can be easily defined on the map rather than independently on each camera view. This greatly simplifies business logic, enables more flexibility in defining regions, and enables additional sensors such as lidar and radar to be used to track vehicles and people.
Improved Urban Management: object tracking and analytics are available near-real-time on MQTT broker to enable actionable insights for traffic monitoring and safety applications.
Reduced TCO: works with the existing cameras, and makes scaling with additional sensors and cameras easy. This simplifies business logic development, and future-proofs the solution.
Learn More#
Intel® SceneScape: Intel Scene-based AI software framework.
DL Streamer Pipeline Server: Intel microservice based on Python for video ingestion and deep learning inferencing functions.