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Automatic face recognition with infrared human body temperature measurement system
| Size | 8 inch | Camera | 200W pixel |
| CPU | Android mainboard | GPU | 64 bit, 4-core |
| O/S | Android 5.0 or above | RAM | 2GB |
| Nand flash | 8GB flash/emmc | Bluetooth | 2.402GHz to 2.48GHz, optional |
| Networking | RJ45/ WIFI | Resolution | 800*1280 |
| Interface | Power port,USB,Relay output,RJ45 ,Wiegand,MC Signal,XF | ||
| Temperature Range | -10ºC to 55ºC,<90ºCRH | Detection distance | 0.5-1.5m |
LS080, pass management vertical module of temperature measurement & face recognition uses Rockchip RK3288 high-performance hardware platform, equipped with binocular wide dynamic camera, live face recognition technology and infrared thermal imaging module to support face-with-mask identify. with face recognition, temperature detection and masks checking etc. functions, the aim of designing is to implement contactless employees attendance, contactless pass and non-contact temperature detection system. It can be widely used in the transportation, education, government etc, industries, acting on the terminal equipment of the smart gate, the smart access control and the smart working attendance.
1.Supports human body temperature detection and temperature display. The best temperature detection distance is 0.5 meters. The longest distance at which body temperature can be measured is 1 meter. The measurement error is plus or minus 0.5 ºC.
2.It only takes a few seconds for detection, and supports automatic alarm for body temperature abnormality.
3. Attendance temperature measurement data is exported in real time.
4. Supports various peripheral expansions such as ID card reader, fingerprint reader, IC card reader, two-dimensional code reader, etc.
5.The documentation is complete and supports secondary development.
6.Support system level, APP offline level, APP + background network level multiple API docking.
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