- Industrial-grade design presents a classy and elegant appearance.
- Embedded Linux OS ensures stable and reliable operation.
- With UNV deep learning algorithm model, face recognition accuracy rate > 99%, false rate < 1%, fast face recognition speed (up to 0.2s).
- Built-in deep learning chip allows local offline recognition, 20,000 face (1:N) capacity.
- 2MP WDR camera with intelligent metering delivers high quality images in a variety of complex light conditions.
- RGB+IR dual-camera liveness detection function effectively prevents spoofing of images or videos.
- Integrated offline speech synthesis engine supports broadcasting person name after successful authentication and customizing various voice prompts.
- With advertising mode support, user can customize the time to switch to the next picture or video and view playback time statistics.
- Supports temperature measurement (an external temperature measurement module is required) and mask detection for pandemic prevention and control.
- Supports door opening by face, card, password, etc.
- Supports device management in the local interface and web interface, such as personnel entry, parameter configuration, and system maintenance.
- Supports connecting to a security module via RS485 to prevent door opening by tampering the device.
- Supports video collection and connecting VMS/NVR devices via ONVIF.
- Built-in 4G EMMC front-end storage with capacity of 30,000 records, stable and reliable.
- Alarm functions such as tamper protection, door open timeout, and authentication over times; supports connecting fire alarm devices to trigger the door to open in case of fire signal input.
- Provides multiple full-fledged APIs to enable management of personnel, records, configurations, etc. on third-party platforms.
OET-573B-HM-R
Терминал контроля доступа с функцией распознавания лиц и считывателем карт 7"
OET-573B-HM-R
Терминал контроля доступа с функцией распознавания лиц и считывателем карт 7"
Код: 011028
На складе: Под заказ
473.50 € / шт
Изображение может не соответствовать реальному виду товара