Description

• 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, the 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 IDView 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 is used to reduce the false rate and increase the 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 the 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 an indoor monitor
• Built-in 4G EMMC front end storage, stable and reliable, up to 30,000 events capacity (with images)
• Support tamper protection, support door open timeout, and time exceed alarm function to keep door opening during fire alarm active