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XNV-6083R - Hanwha X-PLUS SERIES, 2MP OUTDOOR NETWORK AI IR

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$1,975.68
$1,097.60
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SKU: XNV-6083R
Availability: In Stock
Weight: 4.19 LBS
Shipping: Calculated at Checkout
Dynamic range: 150 dB
IK code: IK10
Tilt angle range: -45 - 75°
Pan range: 0 - 360°
White balance: ATW, AWC, Indoor, Manual, Outdoor
Lens viewing angle, horizontal: 119.5°
Lens viewing angle, vertical: 62.8°
Lens viewing angle, diagonal: 142.1°
Sensor type: CMOS
Optical sensor size: 1/2.8";Number of lenses=1"
Zoom capability: Yes
Focal length range: 2.8 - 12 mm
Night vision: Yes
Night vision distance: 50 m
LED type: IR
Noise reduction: Yes
Image stabilizer: Yes
Maximum resolution: 1920 x 1080 pixels
Frame rate: 120 fps
Video streaming: Yes
Total megapixels: 2 MP
Video recording: Yes
Bluetooth: No
Streaming method: Multicast, Unicast
Ethernet LAN: Yes
Wi-Fi: No
Maximum memory card size: 512 GB
Card reader integrated: Yes
Compatible memory cards: MicroSD (TransFlash), MicroSDHC, MicroSDXC
Ethernet LAN (RJ-45) ports: 1
Security algorithms: EAP-LEAP, EAP-PEAP, EAP-TLS, HTTPS
IP address filtering: Yes
Anti-flicker: Yes
Power source type: DC, PoE
Power consumption (max): 20 W
Power consumption (Power over Ethernet (PoE)): 22.5 W
Power consumption (typical): 15.6 W
DC output voltage: 12
Operating temperature (T-T): -50 - 55 °C
Storage temperature (T-T): -50 - 60 °C
Width: 7.09 (180 mm)"
Depth: 7.09 (180 mm)"
Height: 4.92 (125 mm)"
Diameter: 7.09 (18 cm)"
Number of cameras: 1
46C566DB-4644-460E-8DA7-038C0B9646AB E06A9D60-42A9-4459-8131-FA3002495928
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. 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. AI-based Image Optimization, WiseStreamⅢ By utilizing the results of AI-based object detection, WiseStreamIII technology adjusts the video encoder to focus maximum video quality on the detected objects in a scene while scaling back encoding on the rest of the scene.

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