Covid Thermal Detection and Facemask Clocking In Units
£975.00
Fast Detection
(0.05s, the fastest in the market)
Long Detection Range
（0.3m~1.2m, no mis-detection and protect people)
High Accuracy
(±0.2℃ forehead temperature
99.9% Face recognition: fantastic solution for access control )
Powerful AI Chipset
With ISP technologies, images are able to avoid shadowing shorten the detection.
For preventing the spread of COVID-19 (Coronavirus),
Thermal Detector with Time attendance system that adopts the new AI chipset, large thermal sensor array, and the latest algorithm, providing the cutting-edge face recognition and body temperature detection, with ability to detect if employees are wearing a mask.
High Accuracy
± 0.2 ° C forehead temperature detection
99.9%
Face recognition
the best solution for access control and time attendance system Fast Detection 50ms temperature + 200ms face recognition measurement
Long detection Range
0.3 m ~ 1.2 m forehead body temperature detection
Wear mask recognition
Support face recognition with face mask, recognition rate> 95% Detection range: up to 2 meters
Supports 1: 1 or 1: N face comparison
Attribute recognition
Can be set up to recognise if employees are wearing hard hates etc.
Variety of door access control Support
Face recognition for door access control, compatible with many brands.
multi-language support
English, Spanish, French, Italian, Russian, Japanese, Korean UI
| Hardware Specifications Model | Hero-TD01-G |
| Item | Specification |
| Sensor Type | Uncooled infrared focal plane array |
| Infrared Thermography camera | 120*90 |
| Thermal measurement range | 0.3m-1.2m |
| Thermal measurement accuracy | ±0.2℃ |
| Hardware | |
| Processer | AI chipset ARM Cortex-A7 quad-core, 4 x high performance CEVA DSP |
| OS | Linux |
| Storage | 8GB EMMC+1GB DDR4 |
| LCD | 7 inch, 1024*600 resolution |
| Camera | |
| Sensor | Dual 2Mp, low lux sensor |
| WDR | ≥120dB |
| FoV (Diagonal/horizontal/ vertical) | 73degree /65 degree /40 degree |
| Iris | F2.0 |
| Focus length | 4.3mm |
| Performance | |
| Biopsy | Anti-electronic screen, video, mask hacker attack |
| Recognize height | 1.2~2.2 meter, angel adjustable |
| Detection range | 0.5m~2m, lens adjustable |
| Face library | 30,000 (default) |
| Attendance Record | 30,000 |
| Face angle | horizontal 30 degree, vertical 30 degree |
| Interface | |
| Alarm input | 2 pcs |
| Alarm output | 1 pcs |
| Access control | Push out |
| Power supply | DC12V , 2A ( 9 -16V DC) |
| Power consumption | Less than 24W |
| Ethernet | 1 pcs RJ45 10M / 100M Ethernet |
| Wifi | 2.4G Wi-Fi (Optional) |
| USB | 1 pcs USB 2.0 |
| General | |
| Working Temperature | -40 ℃~ + 60 ℃. |
| Dimensions | 120mm*226.5mm*33.5mm |
| Algorithm Parameters Application | Items | Description |
| Face recognition | Face recognition | Local recognition: 30,000 (default ) |
| Algorithm accuracy | 99.9%@0.01% （The accuracy rate is 99% under the 10,000th false alarm rate） | |
| Angle requirements | Yaw ±30°，roll ±30°，pitch ±15° | |
| Face minimum pixels | Face size above 80 * 80 pixels | |
| Face biopsy detection | Angle requirements | Yaw ±30°，roll ±30°，pitch ±15° |
| Face pixel requirements | Interpapillary distance 50 pixels and above | |
| Algorithm accuracy | 98%@0.01% （Real pass rate@Dummy pass rate） | |
| Non-biopsy category | Pictures, videos, coated paper, fake face models, etc. | |
| Face detection and tracking | Number of people captured | More than 30 people / frame |
| Snap frame rate | 25fps | |
| Minimum face size | 30*30 | |
| Adaptation angle | Yaw ±45°，roll ±45°，pitch ±30° | |
| Face attribute | Item | Gender, age, glasses, facial expression (angry, calm, happy, sad, surprised), mask, ethnicity, beard, ethnicity, hat detection, helmet detection |
| Algorithm accuracy | Age accuracy (± 5 years old): more than 85%; Gender accuracy: more than 96%; Skin color accuracy: more than 97%; Beard accuracy: more than 97%; Glasses accuracy: more than 98%; Mask accuracy: more than 98%; Has accuracy: more than 97%; Expression accuracy: more than 88% |
Reviews
There are no reviews yet.