Face recognition

AI face recognition attendance system

Face recognition is the fastest way through a busy entrance and the only method that works when a workforce's fingerprints have worn down. The matching itself is neural — the terminal compares a mathematical template, not a photograph, in under a second.

A face recognition attendance system verifies an employee by comparing a live capture against a stored mathematical template of their face, using neural matching that runs on the terminal itself in under a second. No photograph is stored, and no internet connection is needed for the match. AionHRMS supports face terminals from eSSL, ZKTeco and Realtime, records which method verified each punch, and carries the resulting attendance into shift-wise payroll — so face recognition produces a salary figure, not just a log.

Contactless

no touch surface at the entrance — the hygiene question disappears

Templates

a mathematical representation, never a stored photograph

On-device

matching happens on the terminal, offline if the link drops

Mixed

face at the main gate, fingerprint or card elsewhere, one register

How face recognition attendance actually works

During enrolment the terminal computes a template — a set of numerical features derived from the face — and stores that. On every subsequent scan it computes the same features and compares. The original image is not retained, which is both a privacy property and the reason the process is fast enough for a queue at 09:00.

  • Enrolment captures a template, which AionHRMS also stores centrally
  • Matching runs on the device, typically in well under a second
  • The template propagates to your other terminals so nobody re-enrols
  • Every punch records that it was verified by face rather than finger or card

Where face beats fingerprint, and where it does not

Neither method is universally better. Choosing per site — and mixing across an estate — produces a register with no gaps in it.

  • Face wins at high-traffic entrances and in clinical or food-handling environments
  • Face wins where manual work has worn fingerprints down
  • Fingerprint costs less per terminal and is unaffected by lighting
  • RFID cards remain the pragmatic fallback for anyone neither method reads reliably
  • AionHRMS supports all of them simultaneously across one organisation

Privacy, stated plainly

Biometric data attracts justified scrutiny, and vague answers make buyers nervous. Here is the specific position.

  • Terminals store templates, not images of faces
  • Templates are never displayed in the interface or included in an ordinary attendance export
  • Deleting an employee deletes their stored templates
  • Locking an employee retains the template so access can be restored without re-enrolment
  • You are the controller of your employees' data; we process it on your instruction

Frequently asked questions

Is face recognition attendance accurate enough for payroll?
The matching is done by the terminal, and modern face terminals from the mainstream brands are accurate enough that the failure mode is a rejected scan rather than a wrong identification. Every punch records the verification method, so if a day is disputed you can see exactly how it was recorded.
Does it work with masks or in low light?
That depends on the terminal, not on us — capability varies by model and generation. Tell us the model you are considering and we will tell you what it claims rather than guessing on the manufacturer's behalf.
Is a photograph of my employees stored?
No. The terminal computes and stores a mathematical template. AionHRMS stores that template centrally so it can be pushed to your other terminals, and it is never rendered in the interface.
Can we use face at one site and fingerprint at another?
Yes, and both report into the same register with the verification method recorded per punch.

Put your existing biometric machines on the cloud

Keep the hardware. Add cloud enrollment, multi-device sync and attendance your HR team can actually read.