The NCheck Bio Attendance uses biometric identification of face, fingerprint and iris scanning to efficiently monitor, manage and register attendance on a large and flexible scale, without the need for specialist hardware.
Accurate and efficient reporting of site attendance is vital for the success of large construction projects. The ever-changing and dynamic construction workforce is renowned for payroll errors, poor overtime management and unchecked absenteeism due to the constantly evolving schedules and project requirements. The Bio Attendance system also prevents the fraudulent or incorrect attendance recording associated with other attendance systems such as time cards, fobs or registers.
Whilst the biometric technology has advanced features, the user interface and reporting is simple and intuitive and flexible around your business requirements. The NCheck Bio Attendance system is a turnkey solution that has been designed to fit seamlessly into your construction site HR and payroll operations, helping your construction project to run smoothly, whilst also ensuring your remote workers are compensated fairly and accurately.
Multiple face detection
Our biometric attendance system can detect and recognize faces of all the people seen in the picture, meaning your staff do not have to waste time queuing for the clocking in machine.
Location tracking
Our attendance system can track the geographical location of a person’s place of check-in / check-out.
Liveness detection
Before starting facial recognition, the system can validate that the check-in / check-out is being attempted by a real person.
Hardhat detection
Ensure your construction site staff are following safety procedures when entering your sites with automatic hardhat detection
Remote Location Management
Working time of employees can be easily tracked and calculated even if person works remotely. Users can check-in and check-out simply with their mobile device, tablet or personal computer.
Identification with face mask
Our biometric attendance system is able to recognize a person even if he/she is wearing a face mask, which ensures safe and hygienic identification.
