OET-213H-BTS1

 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 0.3℃, and measurement distance is between 1cm to 3cm

 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 of the base library for a single person

 Support video capture, support ONVIF protocol

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

 Two-way audio with indoor monitor

 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