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EduPresence

For colleges & universities

Lecture-wise attendance and 75% eligibility, handled

Subject-wise percentages update after every lecture and lab. Students see shortfall warnings early, faculty mark nothing by hand, and HODs get department-level reports.

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  • Lecture & lab-wise
  • Subject-wise 75%
  • Student self-service
subject-wise % updates
Every lecturesubject-wise % updates
eligibility with early warnings
75%eligibility with early warnings
or two cameras for 120-seat halls
8 MPor two cameras for 120-seat halls
lab batches modelled natively
B1 / B2lab batches modelled natively

The challenge

What we hear, and how EduPresence answers it

The same four problems come up in almost every conversation. Here's what changes on day one.

  1. 01

    Eligibility disputes at semester end

    Students discover a subject shortfall when it's too late. Early warnings at configurable thresholds change that.

  2. 02

    Proxy attendance in large halls

    Calling 120 names takes a lecture's worth of time and invites proxies. Lecture-hall cameras and voting stop both.

  3. 03

    Complex structures

    Programs, divisions, lab batches B1/B2, electives and semesters - modelled natively, not bolted on.

  4. 04

    Duty leave and events

    Sports, fests and placement drives need On Duty attendance, approved by the right faculty.

Eligibility

Shortfalls caught weeks before the semester ends

Students see their subject-wise percentage after every lecture and lab, with a warning - and the number of classes they need - when they approach the minimum.

  • Defaulter lists per subject
  • Condonation workflows
  • Warnings to students and advisors
Explore reports

Large halls

No more calling 120 names - or answering for a friend

Lecture-hall scans in the first minutes pre-fill attendance for the division. Multi-frame voting and liveness stop proxies, and faculty confirm in one click.

  • Timetable-driven scans
  • Uncertain matches with thumbnails
  • Faculty confirmation
How the AI works

In practice

A college day on EduPresence

See it with your data
  1. 08:50

    Campus entry

    Gate cameras record arrival for students and staff (staff can also use geo check-in).

  2. 09:00

    Lecture 1 - Data Structures

    Lecture-hall scans in the first minutes pre-fill attendance for the division.

  3. 09:05

    Faculty confirms

    One click to confirm; uncertain matches are shown with thumbnails.

  4. 11:00

    Lab - batch B1

    Lab attendance is recorded for the B1 lab batch only.

  5. 17:00

    Shortfall warning

    Students below the warning threshold in a subject get an alert, with the classes they need.

Capabilities

Built for colleges & universities

Every module shares one data model and one set of permissions.

Programs, divisions & lab batches

Program + year, divisions, lab batches and elective groups, with semester-wise subject registration.

  • AISHE code on the institution
  • Credits per subject
  • Elective groups

Lecture-wise attendance

Per-lecture and per-lab attendance from the timetable, marked by AI, QR or faculty.

  • Timetable-driven scans
  • One-click faculty confirmation
  • Corrections with approval

Subject-wise %

Live subject-wise percentage for every student with 75% eligibility tracking.

  • Shortfall warnings
  • Defaulter lists per subject
  • Condonation workflows

Student-applied leave

Students apply directly; faculty advisor then HOD approve. Duty leave for events marks On Duty.

  • Medical certificate rules
  • Period-level leave
  • SLA escalation

Student & staff apps

Students see attendance %, shortfall warnings and timetable; faculty mark, approve and apply leave.

  • Geo-fenced staff check-in
  • Substitute allocation
  • Notices

Adult consent

Adult students and staff consent for themselves; under-18 first-years need parental consent under DPDP.

  • Consent per purpose
  • Withdrawal deletes templates
  • Audit of biometric access

Configuration

Rules that match how colleges work

  • Academic year + semester/trimester structure
  • Program (B.Tech CSE, BBA...) + year, divisions and lab batches
  • Per lecture / lab, subject-wise attendance
  • 75% subject-wise minimum for exam eligibility (common in Indian universities)
  • Leave approval: faculty advisor -> HOD
  • Large lecture halls: 8 MP or two cameras for 50+ students

Your terminology at a glance

Academic year
Academic Year + Semester / Trimester
Level
Program (B.Tech CSE, BBA...) + Year
Group
Division / Section + Lab batch
Attendance unit
Per lecture / lab, subject-wise
Typical rule
75% subject-wise for exam eligibility
Leave approver
Faculty advisor / HOD
Transport
Sometimes (college buses)
“Subject-wise shortfall warnings reach students weeks before exams, so eligibility disputes at the end of the semester have mostly disappeared.”
Sample: Dean of AcademicsEngineering college, 3 departments

Sample testimonial for illustration - names and institutions are placeholders.

Recommended modules

The modules that matter most here

Attendance, leave, transport and alerts share one data model - so an approved leave quietly suppresses the absent and missed-bus alerts.

Smart attendanceAI, RFID, QR and teacher marking feed one registerReports & analyticsRegisters, defaulters and trendsAI face recognitionEdge AI that keeps video on campusLeave managementParent-applied leave, approvals and balancesMobile appsParent, staff and bus kiosk appsSecurity & privacyDPDP-ready consent and encryption

FAQ

Frequently asked questions

Yes, with the right placement: an 8 MP camera or two cameras so that faces at the back bench are at least 60 px tall. Classroom scans run as snapshots in the first minutes of a lecture, not continuous video.

See EduPresence on your own campus

Book a 30-minute walkthrough. We'll map your gates, classrooms and bus routes, and show you an AI-filled register with your own terminology and rules.

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  • Free campus survey
  • Live in days without hardware
  • Hosted in India