Face recognition machine

4.3inch people Face identify brush Card integrated machine KT- FR003

Technical parameters

Processor: Dual-Core ARM Cortex-A7, @1.0GHz

Storage: RAM: 256MB ROM: 8GB

Operating system: Linux operating system

Lens: 4.32mm focal length

Card swiping module: 13.56MHz high-frequency card swiping module, supports ISO/IEC 14443 TypeA, supports reading IC cards

Ethernet: 100M Ethernet port, compliant with IEEE802.3/802.3u standard, supports IPV4 and IPV6 protocols

Wifi module: 2.4GHz single-frequency WiFi communication, supports 802.11 b/g protocol, maximum rate 54Mbps

Bluetooth module: BT 4.2 Modulation method: DPSK, DQPSK, GFSK Transmission rate: 1Mbps~3Mbps

Screen: 4.3-inch IPS LCD screen

Touch: Capacitive touch

Speaker: adjustable sound loudness, power 1W

Recognition distance: 0.3~1.5 meters

Face angle: 30 degrees left and right, 30 degrees up and down

Recognition time: less than 0.5 seconds

Face capacity: 1000

Record capacity: 70,000 records

Power input: DC12V/2A 

Network interface: 1 100M Ethernet port

Wiegand interface: 1 Wiegand output

Alarm interface: 1 channel alarm input

Door sensor interface: 1 door sensor input

Door opening interface: 1 door opening input

Communication interface: 1 RS485 communication interface

USB interface: 1 USB2.0 Type A interface

Camera: Binocular camera, visible light and near-infrared, supports living body detection

Effective pixels: 2.1 million effective pixels

Minimum illumination: color 0.01Lux @F1.2 (ICR); black and white 0.001Lux @F1.2 (ICR)

Signal-to-noise ratio: ≥50db (AGC OFF)

Wide dynamic range: 100db, ISP algorithm partial exposure of face

Operating temperature: -10℃ to +50℃

Working humidity: 10% ~ 90% relative humidity, no condensation

Equipment power: 10W (MAX)

ESD: contact ±4KV, air ±6KV

Protection level: IP42

Power supply: DC12V/2A

Product size: 173.5*90.0*24.0 (mm)

Features

Support binocular live body detection

·Supports face tracking and exposure of people moving in strong backlight environments

·Unique face recognition algorithm, accurately recognizes faces, face recognition time is less than 0.5s

·Built-in domestic CPU

·Using LINUX operating system, the system is stable

·Mean running time between failures MTBF＞50000h

·Working temperature: -10℃- +50℃

·Support front-end equipment configuration, personnel registration, information query and other operations

·Rich hardware interfaces (USB2.0, door sensor input, door opening input, alarm input, Wiegand output, etc.)

·4.3-inch capacitive touch screen, no image smear or delay