Essl K30 pro

The eSSL K30 Pro is a biometric fingerprint time attendance and access control terminal designed for efficient workforce and entry management in offices, factories, schools, gyms, retail shops, and similar workplaces. It uses a 500 DPI optical fingerprint sensor and supports fingerprint plus RFID card recognition, with TCP/IP and USB connectivity and built-in battery backup for reliable performance.

Key Features

 • Large user & log capacity: Stores up to 2,000 fingerprints, 2,000 cards, and 100,000 attendance records.

 • Fast & accurate biometric scanning: High-speed recognition with low false acceptance/rejection rates.

 • Multi-verification support: Accepts fingerprint and RFID card authentication.

 • User-friendly interface: 2.8″ TFT color screen with keypad and LED indicators for easy navigation.

 • Built-in battery backup: Keeps the device operational during power outages.

 • Flexible connectivity: TCP/IP and USB-host support for easy data transfer.

 • Push data & software compatibility: Real-time data push to attendance systems and compatible with eTimeTracklite.

 • Access control ready: Relay output support for door locks and exit button integration.

Applications

 • Employee attendance tracking: Accurate clock-in/out recording for workplaces of all sizes.

 • Access control management: Secure entry control in offices and restricted zones.

 • Education & institution use: Monitoring staff or student attendance efficiently.

 • Clubs, gyms & shop floor: Attendance and access tracking for members and employees.

Summary

The eSSL K30 Pro is a reliable biometric attendance terminal that blends high-capacity fingerprint recognition with access control functionality, suited to a variety of workplaces. Its fast identification, card support, built-in battery backup, and network connectivity make it ideal for automating attendance tracking and secure door access. With intuitive controls and support for desktop/web attendance software, it helps streamline workforce management and reduce manual errors in attendance data.