4-ch 1080p 1U H.265 AcuSense DVR
False alarm reduction through human and vehicle target classification based on deep learning
| Product Type | Digital Video Recorder |
| Resolution | Main stream: When 1080p lite mode not enabled: For 4 MP stream access: 4 MP lite@15 fps; 1080p lite/720p/WD1/4CIF/VGA/CIF@25 fps (P)/30 fps (N) For 3 MP stream access: 3 MP/1080p/720p/VGA/WD1/4CIF/CIF@15 fps For 1080p stream access: 1080p/720p@15 fps; VGA/WD1/4CIF/CIF@25 fps (P)/30 fps (N) For 720p stream access: 720p/VGA/WD1/4CIF/CIF@25 fps (P)/30 fps (N) When 1080p Lite mode enabled: 4 MP lite/3 MP@15 fps; 1080p lite/720p lite/VGA/WD1/4CIF/CIF@25 fps (P)/30 fps (N) Sub-stream: WD1/4CIF@12 fps; CIF@25 fps (P)/30 fps (N) |
| System Requirements | Video Bitrate : 32 Kbps to 6 Mbps ; Dual-stream : Support ; Stream Type : Video, Video & Audio ; Audio Compression : G.711u ; Audio Bitrate : 64 Kbps |
| Connectivity | SATA : 1 SATA interface ; Capacity : Up to 10 TB capacity for each disk ; Serial Interface : RS-485 (half-duplex) ; USB Interface : 2 × USB 2.0 |
| Network Interface | 1, RJ45 10M/100M self-adaptive Ethernet interface |
| Network Protocols | TCP/IP, PPPoE, DHCP, Hik-Connect, DNS, DDNS, NTP, SADP, NFS, iSCSI, UPnP™, HTTPS, ONVIF |
| Input | IP Video Input : 1-ch (up to 5-ch） Up to 6 MP resolution , Enhanced IP mode on: 2-ch (up to 6-ch), each up to 4 Mbps Support H.265+/H.265/H.264+/H.264 IP cameras ; Analog Video Input : 4-ch;BNC interface (1.0 Vp-p, 75 Ω), supporting coaxitron connection |
| Output | HDMI Output : 1-ch, 1920 × 1080/60Hz, 1280 × 1024/60Hz, 1280 × 720/60Hz, HDMI/VGA simultaneous output ; CVBS Output : 1-ch, BNC (1.0 Vp-p, 75 Ω), resolution: PAL: 704 × 576, NTSC: 704 × 480 |
| Power | 12 VDC, 1.5A |
| Power Consumption | ≤ 18 W |
| Environment | Working Temperature : -10 °C to +55 °C (+14 °F to +131 °F) ; Working Humidity : 10% to 90% |
| Advanced Features | Video Compression : H.265 Pro+/H.265 Pro/H.265/H.264+/H.264 |
| Dimension | (W × D × H)315 × 242 × 45 mm |
| Weight | ≤ 1.16 kg (2.6 lb) |
False alarm reduction through human and vehicle target classification based on deep learning