Computer Vision / PROJECT NOTES

Presence, verified.

The right person. The right place.

User-described prototype · source unverifiedPython / Flask / SQLite / HTML/CSS
PRESENCE / IDENTITY + LOCATION
DEMO ID · 001Identity + locationWithin illustrative radius
Synthetic demonstration

Interactive editorial illustration · not a screenshot of the implemented product.

01 / THE QUESTION

The problem worth exploring.

A useful attendance check should consider both identity and whether the person is inside an authorized location.

02 / THE APPROACH

From concept to architecture.

The supplied project description combines facial recognition with GPS verification using the Haversine distance calculation, a Flask interface, and SQLite / CSV attendance records.

  1. Facial recognition workflow
  2. GPS geofence verification
  3. Haversine distance calculation
  4. SQLite and CSV records
  5. Flask web interface
03 / CURRENT PROGRESS

What the evidence says.

Stack and features are user-described, not source-verified. The preview uses synthetic identity and location data; no biometric information is collected.

04 / THE NEXT QUESTION

Room to go further.

Connect the repository and verify behavior. Evaluate consent, spoof resistance, and location accuracy before real use.

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