OET-213H-BTM32
- Support non-contact detection, 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
- 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 white list (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, and password 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 opening timeout, support time exceeding alarm, support keeping door opening while fire alarm active