Speco N32WNRE NRE Series 32-Channel Wall Mount NVR with Facial Recognition, 12TB HDD, White

Brand: Speco Technologies
ADI #:SO-N32WNRE12 Model #: N32WNRE12TB  Name: Speco N32WNRE NRE Series 32-Channel Wall Mount NVR with Facial Recognition, 12TB HDD, White
  • Find and install IP cameras on the local network without needing to locate the cameras manually
  • Supports different recording types: Continuous, Motion, Analytics, and Sensor
  • Create bookmark pins on playback for easy reference
Speco 32 Channel Facial Recognition Wall Mount NVR
Storage

Product Overview

General Information

Name : Speco N32WNRE NRE Series 32-Channel Wall Mount NVR with Facial Recognition, 12TB HDD, White , Speco Technologies
Category : NVRs
UPC Code : 030519031110
Country of Origin : China. Country of origin is subject to change.

Specifications

General Information

ADI Part Number : SO-N32WNRE12
Brand Name : Speco
Connectivity Technology : Wired
Manufacturer : Speco Technologies
Manufacturer Part Number : N32WNRE12TB
NDAA Compliant : Yes
Product Model : N32WNRE
Product Name : 32 Channel Facial Recognition Wall Mount NVR
Product Type : Video Surveillance Station

Technical Information

HD Recording : Yes
Maximum Frame Rate : 30 fps
Power Consumption : 15 W
System Components : Network Video Recorder
Total Number of Channels : 32
Video Formats : H.264, H.265

Interfaces/Ports

HDMI : Yes
Number of VGA Out : 1
Total Number of Audio In Ports : 1
Total Number of Audio Out Ports : 1
USB : Yes

Network & Communication

Ethernet : Yes
Remote Management : Yes

Physical Characteristics

Depth : 16"
Depth (mm) : 406.4
Height : 19"
Height (mm) : 482.6
Width : 3.5"
Width (mm) : 88.9

Power Description

Power Consumption (W) : 15.000

Storage

Hard Drive Capacity : 12TB
Hard Drive Capacity (Byte) : 13194139533312

Video

Maximum Frame Rate (fps) : 30
Maximum Resolution : 8MP

Warranty

Limited Warranty : 5 Year

Miscellaneous

Country of Origin : China
Package Contents : <ul> <li>32 Channel Facial Recognition Wall Mount NVR</li> <li>Remote Control</li> </ul>