Hanwha / Samsung
Hanwha XNV-8093R 6MP AI IR Vandal Dome Camera
10.9-29mm lens
Quantity:
• 6MP resolution
• 10.9~29mm (2.7x) motorized varifocal
• Color: 0.06 Lux (F1.7, 1/30sec, 30IRE), 0 Lux (IR LED on)
• Maximum 30 fps (H.265/H.264)
• WiseIR: IR viewable length 70m(229.66ft)
• Day & Night (ICR), extremeWDR (120 dB)
• Hard-coated dome bubble
• WiseNRⅡ (Based on AI engine), WiseStreamⅢ (Based on AI engine)
• Analytics events based on AI engine (NPU) : Object detection (Person/Face/Vehicle - car, truck, bus, bicycle, motorcycle/License plate),
IVA (Virtual line/Area, Enter/Exit, Loitering, Direction, Intrusion)
• Analytics events : Defocus detection, Motion detection, Tampering, Fog detection
Audio detection, Sound classification, Shock detection, Appear/Disappear
• IP66/IP67/IP6K9K, NEMA4X, IK10+
Reducing False alarm based on AI
The new X series cameras utilize AI to detect and classify people, vehicles, faces, license plates and more in real-time. With a range of available resolutions from 2MP to 4K, the cameras’ deep-learning algorithms can reliably identify multiple distinct objects. Reduce false alarms due to none interesting motion, like wind-blown trees, shadows, or animals. Analytics become a reliable second pair of eyes to operators helping them know where to look for important real-time events, while making post-event forensic searches highly efficient.
AI-based object detection for operational efficiency
Metadata including information (person, face, vehicle, license plate) is sent to the backend server and used to extract information on specific events. Operators are able to search AI events on the backend server. This greatly enhances search efficiency and reduces time spent on searching events. Also it can be reducing false alarm when operators were monitoring scene.
AI-based WiseNRII and Prefer Shutter Control
WiseNRII is a new enhancement which utilizes AI to identify object movement and reduce blur in noisy, low light environments. AI-based Preferred Shutter technology automatically adjusts the shutter speed based on classified objects in motion and the lighting conditions in a scene to reduce motion blur and deliver the clearest images.
