UNV OET-213H-BTS1 Face Recognition Access Control Terminal with Digital Temperature Measurement Module

Product Overview

OET-213H-BTS1 digital temperature measurement face recognition access control terminal is a kind of access control device with precise recognition rate, largestorage capacity and fast recognition, which integrates UNV face recognition technology and non-contact temperature detection technology. The digital temperature measurement module supports rapid body temperature detection. Thus, the product can achieve face recognition and temperature detection at the same time, and support warning people with abnormal body temperature. It can be widely applied in the crowded places, such as smart communities, schools, office buildings, hospitals and other important areas.

UNV_OET_213H-BTS1
UNV_OET_213H-BTS1

press to zoom
UNV_OET_213H-BTS1_View_02
UNV_OET_213H-BTS1_View_02

press to zoom
UNV_OET_213H-BTS1_Standalone
UNV_OET_213H-BTS1_Standalone

press to zoom
UNV_OET_213H-BTS1
UNV_OET_213H-BTS1

press to zoom
1/4

Product Features
 

  • Support non-contact detection of wrist temperature, support warning people with abnormal body temperature

  • 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 0.5℃, and measurement distance is between 1cm to 2.5cm

  • 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

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


OET-213H-BTS1: Datasheet