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Face-recognition attendance system
IntermediateAI and programmingAbout 8 weeks

Face-recognition attendance system

A camera at the entrance records attendance automatically, with no cards to lose or touch-based fingerprint readers, and produces a ready monthly report.

The problem

Absent people can get signed in on the attendance sheet, a card can be lent to a colleague, and some people avoid touching fingerprint readers since COVID. All these methods prove that something passed, not that a specific person was present. A face can't be lent and needs no contact, and check-in happens without queuing.

How it works

  1. Initial enrollmentEach person is photographed once to extract their face's digital fingerprint.
  2. CaptureThe camera captures the face as the person approaches the entrance.
  3. MatchingThe system compares the captured fingerprint with the database of registered people.
  4. Check-inOn a successful match, attendance is recorded with its time and the name shown on the screen.
  5. Check-outThe same process records the exit time, and hours present are calculated.
  6. ReportThe dashboard produces exportable daily and monthly reports.

Project features

  • A face can't be lent and check-in needs no contact, so the system solves both problems at once.
  • No queues: check-in happens as the person walks by.
  • The monthly report is prepared automatically with no manual input.
  • It allows a live, direct demo of the system in front of the defense committee.
  • It can expand to several entrances working on the same database.

Parts

All the parts you need in one place. Remove what you already have, and swap parts to fit your budget. Parts with a photo are available in our store at their current price.

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Prices are estimates and may change. Parts marked “other supplier” are ordered outside our main store.

Expected challenges

These are the main obstacles to expect during the build, laid out clearly so you know them before you start.

  • Lighting strongly affects the results; shadows and backlighting are the main factors.
  • Accuracy drops with masks, glasses, or a change in appearance.
  • The system can be fooled with a photo, so it needs a liveness check.
  • A face print is personal biometric data that's legally sensitive, requiring privacy protection.
  • The system slows down as the database of registered faces grows.

The consultation gives you a solution for each one.

Expected committee questions

Prepare your answers in advance: these questions come up often in defenses of similar projects.

  1. How accurate is the recognition, and how does it handle changing light, glasses, or a beard?
  2. How does the system prevent check-in using a photo of someone else on a phone?
  3. Where are face images stored, and how is their privacy protected?
  4. How long does each person's check-in take at the entrance?

Practice the defense, question by question

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Need solutions to the challenges and a complete technical path?

In the consultation we give you a solution for each challenge above, plus a practical build plan from the first step to the last: technologies, libraries, wiring diagram, timeline, and tips for the defense.

  • Consultation session
  • PDF with solutions and a plan
  • 20 د.أ فقط
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