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Hikvision DS-2CD2H43G2-IZS 4 MP AcuSense Motorized Varifocal Turret Network Camera

Technical Specification

Features:

Make: Hikvision
Model code: DS-2CD2H43G2-IZS
Series: Hikvision Pro Series
Chip Inch Size: 1/3 inch
Colour Type: Colour / Monochrome

Additional info:

High quality imaging with 4 MP resolution Motorized varifocal lens for easy installation and monitoring Clear imaging against strong backlight due to 120 dB WDR technology Efficient H.265+ compression technology Water and dust resistant (IP67) and vandal resistant (IK10) Focus on human and vehicle targets classification based on deep learning

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Datasheet Datasheet

Make	Hikvision
Manufacturer	Hikvision
Category	CCTV>IP Dome cameras
Model code	DS-2CD2H43G2-IZS
Series	Hikvision Pro Series
Chip Inch Size	1/3 inch
Colour Type	Colour / Monochrome
Resolution TVL	4MP
Megapixel	Yes
Sensitivity lux	0 ~ 0.005
Digital (DSP)	Yes
Electrical Specifications	Voltage: 12 V DC, PoE Power Consumption: 11 W
Focal length	2.8 ~ 12mm
Compression	H.265, H.264, H.265+, H.264+, MJPEG
Back Light Compensation	Yes
Auto Gain Control	Yes
White Balance	Yes
Electronic Shutter range	1/3 s ~ 1/100,000 s
Built-in IR LED	Yes
Network Properties	Interface: 1 RJ45 10 M/100 M self-adaptive Ethernet port Network Protocols: TCP/IP, ICMP, HTTP, HTTPS, FTP, DHCP, DNS, DDNS, RTP, RTSP, NTP, UPnP, SMTP, IGMP, 802.1X, QoS, IPv6, UDP, Bonjour, SSL/TLS, PPPoE, WebSocket, WebSockets Image Frame Rate: 10 ~ 30 fps
Physical Specifications	Dimensions mm: Ø138.3 × 126 Weight g: 830
Environmental Specifications	Operating Temp ^oC: -30 ~ +60 C (-22 ~ +140 F) Operating Humidity %: 0 ~ 95 Protection: IP67, IK10
System Requirements	Web Browser: IE 10, IE 11, Chrome 57.0+, Firefox 52.0+, Chrome 57.0+, Firefox 52.0+
Additional info	High quality imaging with 4 MP resolution Motorized varifocal lens for easy installation and monitoring Clear imaging against strong backlight due to 120 dB WDR technology Efficient H.265+ compression technology Water and dust resistant (IP67) and vandal resistant (IK10) Focus on human and vehicle targets classification based on deep learning
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