Analytics
OpenEye Web Services AI Analytics
OWS analytics provide you with more actionable intelligence, natively available in OWS, enhancing the value from your existing video surveillance system.
| OWS AI Analytic Type | Description |
| Smart Motion |
OWS smart motion detects motion events tied to persons and vehicles while eliminating false positives created by reflections, shadows, moving foliage and other items in the environment. |
| Person and Vehicle |
Get notified and quickly view video of events tied to persons and vehicles through OWS server-side analytics. |
| Line Crossing, Loitering and Intrusion |
Configure your system to be alerted of line crossing or intrusion events with OWS server-side analytics. |
| Attribute Filters | Quickly locate persons and vehicles of interest using attribute filters powered by OWS AI Analytics in the cloud web client. |
| Similarity Search |
Search for similar persons or vehicles using OWS AI Analytics in the cloud web client by selecting an object in the scene to quickly locate related video across cameras and locations. |
Edge Analytics
With analytic event processing being performed by the camera hardware, users can deploy analytics across the full range of OpenEye recorders without concern for increased system load or recorder performance.
| Third-party Edge Video Analytics | Description |
|
Area Entered, Area Exited |
Detect when a person or vehicle enters or leaves a defined zone. |
|
Area Motion, Change in Area |
Identify motion or significant visual changes within a selected region. |
|
Camera Out of Focus, Camera Tampering |
Alert when the camera becomes obscured, defocused, or tampered with. |
|
Line Crossed |
Detect objects crossing a virtual boundary in one or more directions. |
|
Loitering |
Identify individuals remaining in a monitored area beyond a set duration. |
|
Person / Vehicle
|
Detect and classify people and vehicles within the field of view. |
|
Queue
|
Monitor and detect when lines form or queue lengths exceed defined thresholds. |
|
Face Detection |
Detect human faces within the camera view. |
|
Mask Detection |
Identify whether individuals are or are not wearing face masks. |
|
Elevated Skin Temperature |
Detect elevated skin-surface temperatures based on thermal imaging. |
|
Fog / Smoke |
Identify the presence of smoke, haze, or reduced visibility conditions. |
|
Detect and capture license plates for recognition or event-based actions. |
|
| Third-party Edge Audio Analytics | Description |
|
Gunshot |
Detect the acoustic signature of gunfire. |
|
Glass Break |
Identify the sound pattern associated with breaking glass. |
|
Scream |
Detect distress-related sounds such as screams or calls for help. |
|
Explosion |
Identify loud impulse sounds consistent with explosions. |
Operational Analytics
Operational Analytics in OpenEye Web Services (OWS) uses powerful video analytic tools to detect, analyze, and uncover insights into the complex behaviors of customers, staff, vehicles or objects in a users' business.
| Operational Analytic Tasks | Description |
|
Vehicle Journey Time |
Detect when a vehicle remains within a defined region of interest (ROI) for longer than a specified duration. When the vehicle exceeds the configured wait time, a ticket or alert is generated. |
|
Queue Length Detection (Person or Vehicle) |
Monitor the number of people or vehicles within a defined queue region. If the count exceeds the configured Maximum Queue Length for more than the set duration (e.g., 5 seconds), a ticket or alert is generated. |
|
Wait Time (Person or Vehicle) |
Track the time people or vehicles spend in a region of interest. Generate a ticket or alert when the configured wait time threshold is exceeded. |
|
Customer Walk-in Count (Employee Exclusion) |
Count customer entries into a designated region while excluding staff using defined exclusion zones or AI-based employee filtering. |
|
Heatmapping |
Identify and visualize high-traffic areas within a defined space using heat-based color mapping from camera data. |
| Unattended Customer (No Employee Present at Register) | Monitor when an area of interest is unattended for x number of seconds and customers are present. |
| Occupancy | Measure occupancy levels by counting the number of people entering and exiting all ingress and egress points. |