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Effective employee attendance monitoring is essential for organizational efficiency. This research paper introduces an innovative Smart Attendance Monitoring system that leverages facial recognition and geofencing technologies. The primary objective of this study is to automate attendance tracking while addressing the prevalent issue of fake attendance reporting. In traditional attendance systems, manual input and record-keeping are prone to errors and manipulation, especially in large organizations. To mitigate the risk of spoofing or impersonation, our system mandates employees to be physically present within a predefined geographical location before utilizing the facial recognition feature to mark their attendance. To develop a robust anti-spoofing mechanism, we curated a custom dataset and employed the MobileNetV2 architecture for model training. This approach not only ensures high accuracy but also reduces computational complexity. The liveness detection model, an integral part of our system, verifies the authenticity of faces, thwarting spoofing attempts effectively. To develop a robust anti-spoofing mechanism, we curated a custom dataset and employed the MobileNetV2 architecture for model training. This approach not only ensures high accuracy but also reduces computational complexity. The liveness detection model, an integral part of our system, verifies the authenticity of faces, thwarting spoofing attempts effectively. By combining liveness facial recognition with geofencing, organizations can bolster security measures, allowing access only to authorized individuals who are physically present within the designated area. This approach not only streamlines attendance monitoring but also enhances overall security. By combining liveness facial recognition with geofencing via the IP stack API, organizations can bolster security measures, allowing access only to authorized individuals who are physically present within the designated area. This approach not only streamlines attendance monitoring but also enhances overall security.

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Face Recognition-Based Smart Attendance Monitoring System Using Liveness Check and Geofencing

  • 会议论文

  • 发表日期：

    2025年

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  • Sarthak Jamdar,
  • Akshita Pandita,
  • Vaishnav Katre,
  • Janvi Thakre,
  • Ritu Jain

摘要

Effective employee attendance monitoring is essential for organizational efficiency. This research paper introduces an innovative Smart Attendance Monitoring system that leverages facial recognition and geofencing technologies. The primary objective of this study is to automate attendance tracking while addressing the prevalent issue of fake attendance reporting. In traditional attendance systems, manual input and record-keeping are prone to errors and manipulation, especially in large organizations. To mitigate the risk of spoofing or impersonation, our system mandates employees to be physically present within a predefined geographical location before utilizing the facial recognition feature to mark their attendance. To develop a robust anti-spoofing mechanism, we curated a custom dataset and employed the MobileNetV2 architecture for model training. This approach not only ensures high accuracy but also reduces computational complexity. The liveness detection model, an integral part of our system, verifies the authenticity of faces, thwarting spoofing attempts effectively. To develop a robust anti-spoofing mechanism, we curated a custom dataset and employed the MobileNetV2 architecture for model training. This approach not only ensures high accuracy but also reduces computational complexity. The liveness detection model, an integral part of our system, verifies the authenticity of faces, thwarting spoofing attempts effectively. By combining liveness facial recognition with geofencing, organizations can bolster security measures, allowing access only to authorized individuals who are physically present within the designated area. This approach not only streamlines attendance monitoring but also enhances overall security. By combining liveness facial recognition with geofencing via the IP stack API, organizations can bolster security measures, allowing access only to authorized individuals who are physically present within the designated area. This approach not only streamlines attendance monitoring but also enhances overall security.