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 |
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