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Data Sheet

Face Recognition Access Control Terminal with Digital Detection Module

Supportnon-contact detection of wrist temperature, support warning people with abnormal body temperature

Support the detection of wrist distance, improve the accuracy of temperature measurement

Support body temperature detection and personnel information binding, which can quickly confirm personnel information and do body temperature detection

Support configure temperature detection threshold value, and personnel access authority can be configured through temperature detection threshold value

Non-contact wrist temperature detection module, measurement range is between 30℃ to 45℃, measurement accuracy can reach 0.1℃, measurement deviation is less than or equal to 0.3℃, and measurement distance is between 1cm to 4cm

Deep learning algorithm model based on UNV independent intellectual property rights, face recognition accuracy rate > 99%, false rate < 1%

Built-in deep learning dedicated chip, supports local offline recognition, 10,000 face capacity, face whitelist (1:N)

Fastest recognition time 0.2 seconds, various model merge mode are used to reduce false rate and increase pass rate

WDR, 2MP (1080P) low illumination wide-angle camera and F1.6 large aperture lens for capturing high quality image with various complex lighting scenes

Support anti-spoofing detection based on deep learning algorithm, effective against fraud such as photo and video

Support face metering and human metering for fast adapting to ambient light

Suggested height for face recognition: between 0.8m and 2.2m, face recognition distance: 0.2m to 2.9m

Support screen sleep mode, keep the minimum brightness to prevent glare at night

Support add up to 6 photos ofthe base library for a single person

Support video capture, support ONVIF protocol

Support face, card, and QR code authentication to control door open

Built-in 4G EMMC front end storage, stable and reliable, up to 8,000 events capacity (with images)

Support tamper protection, support door open timeout and time exceed alarm function to keep door opening during fire alarm active

Features Parameter	Description
Operation System	Linux
Face Recognition Accuracy Rate	>99%
Face Recognition Time	200ms
Face Capacity	10,000
Card Capacity	100,000
Storage Capacity	4GB
Event Capacity	8,000(with images)；30,000(without images)
Authentication Mode	Face Whitelist∶ (1∶ N)
	Card:(1:N)
	Face +Body temperature + Mask Detection
Door Opening Method	Face, Password, Card
Communication Mode	10/100Mbps adaptive network port
Card Type	Mifare1 Card
User Management	Support user library addition, deletion, update
Record Management	Support local recording and real-time upload
Interface	LAN×1, Wiegand Input×1, Wiegand Output×1, RS485×1, Alarm Input×2, Alarm Output×1, USB2.0×1, Lock×1, Door Contact ×1, Exit Button×1
Power Supply	Input 12V±25% DC
Power Consumption	Terminal: 10W Module: 756mW
Weight	Terminal:641g Module: 131g
Screen	Touch Screen, Size:7 inch, Resolution: 600×1024
Camera	Dual Lens, 2MP, 1080P
Supplement Light	LED soft light and infrared light
Dimensions (L×W×H)	Forterminal: 134.0mm×33.0mm×305.0mm For module: 87.0mm×45.0mm×27.0mm
Working Environment	For terminal: -20℃-65℃, Relative Humidly<95% (non-condensing) For module: 10℃-40℃
Protection Level	Both terminal and module: IP 54
Application Situation	Indoor, No wind

ALL UNIVIEW

UNIVIEW OEP-BTS1-BD-NB Face Recognition Access Control Terminal with Digital Detection Module