Auto Attendance

Accurate and contactless attendance tracking.

Auto Attendance BNR

Track attendance automatically with AI

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Manual attendance systems are outdated and impact reliance due to manual data input. With AI and facial recognition, auto attendance gives way to a fully automated, accurate and much more efficient attendance system. No manual roll calls or other complex sign-ins required.

Our holistic view to challenges

Challenges

Manual roll calls

Manual roll calls

Traditional attendance methods slow down class start times and consume teaching time.

Automated attendance

Automated attendance

AI-driven facial recognition marks attendance instantly and accurately in real-time as students enter.

Proxy attendance

Proxy attendance

Manual methods can be manipulated, leading to proxy entries and inaccurate records.

Secure attendance

Secure attendance

Verify each students identity, eliminate proxy attendance and ensure only actual individual is marked present.

Features

Data management

Data management

Paper-based or outdated digital systems can complicate record-keeping and hinder timely insights.

Cloud-based logs

Cloud-based logs

Access organized, real-time attendance data on a cloud platform for easy retrieval and analysis.

Late arrivals early departures

Late arrivals/early departures

Difficult for traditional systems to record when students arrive later or leave before class ends.

Real-time entries

Real-time entries

AI systems log precise timestamps for each students arrival and departure, tracking tardiness and early exits.

Automated attendance systems can save teachers up to 2 hours per week, allowing focus on instruction and student engagement.

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Who benefits from Auto Attendance?

Auto attendance is advantageous for educational environments as they require accurate and seamless attendance tracking.

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  • Schools & universities
  • Training centers
  • Examination halls
  • Online & hybrid classrooms

How it works?

process
Integration with existing infra

Integration with existing infra

We use the existing classroom cameras to capture facial data without any disruptions.

Model training and calibration

Model training and calibration

The AI model is trained on student images to achieve high accuracy under different scenarios.

Monitoring & data logging

Monitoring & data logging

The system is deployed for live, instant tracking and logging of student presence as they enter.

Reporting & analysis

Reporting & analysis

Detailed attendance reports and performance metrics are generated to support administrative decision-making.

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