Precise Automatic Face Recognition Reader Body Temperature Detection
A7C is a new high-performance binocular face recognition temperature measurement terminal launched by our company based on the Rockchip RV1109 solution. The core is a high-performance chip with outstanding comprehensive performance. The face recognition speed can reach 300ms and the temperature measurement speed can reach 0.5S., Adopt Hyman 32*32L5.0 module, temperature measurement is more accurate. Through centralized management in the background, effective batch management of equipment, personnel management, access control and attendance management and other functional applications are applicable to office buildings, attendance, communities, scenic spots, office buildings, public service places, construction sites, government units, etc.
Specification
| Basic information | Installation site | Wall, installation, gate installation |
| Working temperature and humidity | -15℃ to 55℃,<90℃RH |
| Protection level | IP55 |
| Dimensions | 246*21.5*123mm |
| Texture | Aluminium alloy |
| Hardware information | System | Linux |
| CPU | RV1109 2 core 1.5GHz |
| Storage | Memory 1GB, data storage 8GB |
| Display screen | 7-inch high-definition IPS LCD screen, resolution 600*1024 |
| Touching | Selected touching |
| Camera | 200W live binocular camera |
| Wide dynamic | Support |
| Fill light | Three-colour fill light Infrared fill light |
| WIFI | Support (Selected) |
| Speaker | 1-way speaker |
| Watchdog | Support hardware watchdog |
| Recognition performance | Face library capacity | 1:N,N<=20000 |
| Accuracy | 99.70% |
| IC/ID card recognition | Support USB swiping module/serial swiping module (optional) |
| ID card recognition | Supporting witness comparison (Support central control, Huashi USB interface universal protocol ID card reader) |
| Working environment | Power supply | DC12V 2A |
| Power consumption | ≤8W |
| Working temperature | -20℃~+60℃ |
| Working humidity | 20%-90% |
| Storage temperature | -40~125℃ |
Characteristics
1. Face recognition accuracy: The accuracy of face recognition can also be improved by adjusting algorithms and tuning parameters to better match and identify faces.
2. Speed and efficiency: Face recognition systems can be optimized to achieve faster processing speeds and improved efficiency by leveraging hardware acceleration, parallel processing, and other optimization techniques.
3. Scalability: Face recognition systems can be customized to support different levels of scalability, from small-scale deployments to large-scale enterprise solutions.
4. Integration with other systems: Face recognition systems can be integrated with other security systems, such as access control systems, video surveillance systems, and alarm systems, to provide a more comprehensive security solution.
5. Customized alerts and notifications: Face recognition systems can be configured to trigger customized alerts and notifications when specific events occur, such as unauthorized access attempts or high-risk individuals being detected.
6. Integration with analytics and reporting tools: Face recognition systems can be integrated with analytics and reporting tools to provide insights into system performance, user behaviour, and security trends.
