Purpose-built for universities and colleges. A 5-step AI validation chain verifies every student's identity, exam registration, and room assignment in real time — making proxy attendance in examination halls biometrically impossible.
Traditional manual verification in exam halls fails on every dimension: speed, accuracy, fraud prevention, and compliance. MemoFaceAI ExamIntegrityAI is built specifically to fix this.
Impersonation in exams — one student sitting for another — is a documented problem across Indian universities. Manual ID checks are easily circumvented in crowded halls.
10–15 seconds per student at entry means the first 30 minutes of every exam are consumed by entry chaos. Students miss time. Invigilators are stressed.
Attendance sheets are filled manually, transferred by hand, and compiled days after the exam. Errors and omissions are routine. Audit trails are weak.
Students sitting in the wrong hall — due to confusion or intentional fraud — are caught only when registers are reconciled. Sometimes never.
Exam controllers have zero visibility into which halls have attendance gaps, anomalies, or technical issues — until hours after the exam ends.
Generating attendance sheets, absentee lists, and anomaly reports requires 1–2 days of manual data entry. Errors are inevitable. Audit readiness is never guaranteed.
All five checks execute in sequence in under 4 seconds. Every single condition must pass. Failure at any step terminates the chain with a specific, human-readable reason code.
Create exams with subject, code, department, date, time, duration, and seats. Supports multiple concurrent exams. Bulk CSV upload for large schedules. Lifecycle: Draft → Published → Active → Completed → Archived.
Map each student to exam ID, room ID, and optional seat number. Bulk mapping via CSV. Face stored as a 512-dimensional embedding — not raw images. Auto-alerts for low-quality enrollments.
Create and manage exam halls with name, building, floor, and capacity. Assign students to rooms per exam. Capacity vs. count validation. Room-wise live dashboard: Present / Absent / Not Yet Scanned.
Deep learning 1:N face matching. ≥99.5% true acceptance rate at 0.01% false acceptance. Handles glasses, mild facial hair, varied lighting, and ±20° angle variations. Under 4 seconds on any Android and iOS or iPad device.
Passive liveness — no blink or head movement required. Single-frame analysis. Detects printed photos, screen replay, and 3D masks. Liveness score returned with every scan. Failure logged with frame snapshot.
Native Android & iOS. Offline-capable face capture. Large, clear accept (green) / reject (red) screen optimized for hall lighting. Real-time present/total count. Exception log visible during session.
Live attendance across all exams, all halls, all departments on one screen. Drill-down to individual records. Live anomaly feed. Manual override panel with compulsory reason entry. System health monitor.
Hall-wise attendance report, absentee list, anomaly report, department-wide summary, student history report. Export formats: PDF (signature-ready), Excel, CSV for ERP integration. All instant on demand.
Every scan, acceptance, rejection, and manual override is permanently logged with timestamp, device ID, and actor. Records become read-only after exam completion. Digitally signed for legal validity.
All rejection messages are non-technical, unambiguous, and tell the invigilator exactly what to do next.
| Error Code | Message Shown on Device | Invigilator Action |
|---|---|---|
| ERR_LIVENESS | Spoof Detected. Please present live face. | Ask student to face camera directly; retry once. Do not allow entry. |
| ERR_FACE_MATCH | Identity Not Verified. Face not recognized. | Escalate to admin immediately. Do not allow entry under any circumstance. |
| ERR_NOT_REGISTERED | Not Registered for This Exam. Check exam schedule. | Check student's hall ticket. Escalate to exam controller. |
| ERR_WRONG_ROOM | Not Allocated to This Room. Check your hall ticket. | Guide student to their correct hall. Do not admit to this hall. |
| ERR_DUPLICATE | Already Marked Present in This Exam. | Flag for investigation. Do not re-mark. Escalate to admin. |
| SUCCESS | ✅ Attendance Marked. Welcome, [Student Name]. | Student proceeds to their assigned seat. |
| Metric | Manual / Paper | ExamIntegrityAI ✦ |
|---|---|---|
| Proxy attendance | Unquantified / High Risk | ✓ 0% — Biometrically Impossible |
| Hall entry validation time | 10–15 sec per student | ✓ <4 seconds per student |
| Room mismatch detection | ✗ Not caught in real time | ✓ Rejected instantly at entry |
| Duplicate prevention | ✗ Manual check (error-prone) | ✓ Auto-blocked — 100% reliable |
| Attendance data availability | Hours after exam / manual entry | ✓ Real-time, during exam |
| Admin visibility during exam | ✗ Zero | ✓ Live multi-hall dashboard |
| Report generation time | 1–2 days of manual work | ✓ Instant on demand |
| Audit trail | Paper (losable, alterable) | ✓ Tamper-proof, digital, permanent |
| Face match accuracy | Human — variable, fatiguable | ✓ ≥99.5% — consistent every scan |
Every entity in the system is designed to handle 10,000+ concurrent candidates across unlimited departments and exam halls with no performance degradation.
MemoFaceAI ExamIntegrityAI is purpose-built for universities. Request a demo configured for your institution's exam scale and structure.