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AI Facial Recognition Thermal Fever Detection System With Tripod Or Wall Mounted Installation

Securina Detection System Co., Limited
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Securina Detection System Co., Limited

AI Facial Recognition Thermal Fever Detection System With Tripod Or Wall Mounted Installation

Country/Region china
City & Province shenzhen guangdong
Categories Other Access Control Products
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Product Details

AI Facial Recognition Thermal Fever Detection System With Tripod Or Wall Mounted Installation

 


 

This face recognition and thermal detection can detect elevated skin temperatures brought on by various external causes,support access control system,and time attendance 30000pcs face picture for white list capacity,1920*1080p resolution.

Can be widely used in aisles, gates, gates and other controlled entrances or areas. If Temp is more than 37.3℃,will be voice alarm and red words alards,Temp will be show on screen. If Temp is ok,will show green and temperature normal. All display and voice in English,can update Language according to customer requirements.

 

Introduction:

Thermometric face recognition is a kind of biometric recognition technology based on human facial feature information for identity recognition. Its uniqueness and good characteristics that are not easy to be copied provide the necessary premise for identity authentication. The current temperature of pedestrians is also a prerequisite for whether to open the gate. Face recognition pedestrian channel gate system is the combination of face recognition technology and pedestrian channel system, through the face recognition as the key to open the pedestrian channel. It not only saves you the trouble of forgetting to bring a key or card, but also saves a lot of costs because the face recognition walkway gate system does not need any medium to open the door, such as personnel changes do not need to replace the IC card, etc., only need to re-enter the person Just register the face information;

 

The temperature measuring face recognition all-in-one machine adopts the international advanced neural network algorithm (CNN), which is a product formed after tens of millions of algorithm trainings. It integrates functions such as image acquisition, face detection, face tracking and face comparison. , Not only high recognition rate but also fast recognition speed. The offline dynamic portrait recognition machine does not require pedestrians to cooperate with direct recognition, and does not require computer control. Pedestrians can also be recognized in motion, which greatly improves the ease of use of portrait recognition. The product can be applied to any channel gate (wing gate, swing gate, three-roll gate, etc.), access control and advertising gates that are commonly available in the market, and can directly output the opening signal and Wiegand signal; it can be widely used in its own doorway, community access control, Scenes such as school entrance and exit, Daozha passage, office building, subway, airport, high-speed rail, etc.

 

Specifications of SA230: 

Hardware
CPURK3288
Operation systemandriod
storage8GB
Image device1/2.7" CMOS
Len4.3mm
Camera
CameraBinocular camera, support in vivo detection
pixels2 million pixels, 1920*1080
SensitometryColor 0.01Lux @F1.2(ICR);W/B 0.001Lux @F1.2
SNR≥50db(AGC OFF)
Wide dynamic range≥80db
Face recognition performance
Recognition height1.2-2.2m adjustable
Recognition distance0.5-2m
Angle of view40 degrees up and down
Recognition time<500ms
FunctionSupport 30,000 face comparison libraries
Body Temperature Measurement
Temperature range28-45(ºC)
Temperature accuracy±0.5(ºC)
Detection distance0.5m
Response time<300ms
Interface of ports
Network portRJ45 10M/100M Adaptive Ethernet port
Wiegand interfaceWiegand input and output are supported, and wiegand 26 and 34 are supported
Alarm output1 way switching output
USB1 USB interface (external ID card reader)
Basic specification
Power supplyDC12V/3A
Power20W(MAX)
Operation temperature0ºC ~+40ºC
Operation humidity5~90% Relative humidity, no condensation
Size135.2(W) * 79(T) *365.3(H)mm
Weight1.6kg
Column diameter33mm

 

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