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Manual as well as automatic traditional attendance systems are prone to mistakes, inefficiency, and proxy attendance. Current Wi-Fi-based solutions just provide zone-based localization, which is not precise in classroom environments. We thus propose a strong Face Recognition Attendance System (FRAS) combining RSSI analysis, IP-based tracking and real-time facial verification using individual’s own device. FRAS uses a specified geofencing radius to guarantee students are physically present using RSS techniques. Driven by CNNs and DNNs, the system automatically logs attendance free from human involvement. Integration of Wi-Fi Positioning and anti-spoofing modules strengthens general security, detects proxy attempts and increases accuracy even more. Perfect for colleges and test settings, FRAS provides a dependable, safe, scalable solution.

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Self-adaptive Smart Attendance System Using Facial Recognition and Wi-Fi RSSI-Based Positioning

  • 章节

  • 发表日期：

    2026年

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  • B. Surya Narayanan,
  • G. Vandhana,
  • M. Gowtham Sethupathi,
  • S. Siva Karthick Raj

摘要

Manual as well as automatic traditional attendance systems are prone to mistakes, inefficiency, and proxy attendance. Current Wi-Fi-based solutions just provide zone-based localization, which is not precise in classroom environments. We thus propose a strong Face Recognition Attendance System (FRAS) combining RSSI analysis, IP-based tracking and real-time facial verification using individual’s own device. FRAS uses a specified geofencing radius to guarantee students are physically present using RSS techniques. Driven by CNNs and DNNs, the system automatically logs attendance free from human involvement. Integration of Wi-Fi Positioning and anti-spoofing modules strengthens general security, detects proxy attempts and increases accuracy even more. Perfect for colleges and test settings, FRAS provides a dependable, safe, scalable solution.