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RFID Attendance System using IoT

RFID Attendance IoT System

Manual attendance tracking and basic RFID systems often lack real-time visibility, accurate timestamps, and flexibility for handling new users. Many solutions depend on external software or manual data processing, making them inefficient for classrooms, labs, offices, or training environments where reliable, time-stamped attendance records are essential.

This project implements an IoT-based RFID attendance system using the IndusBoard Coin. The system reads RFID card UIDs via an MFRC522 module, records punch-in and punch-out events with accurate timestamps synchronized through NTP, and displays all attendance data on a real-time web interface hosted directly on the board. Unknown cards are automatically redirected to a registration page, enabling seamless user onboarding.

Key Features
  • RFID-based punch-in and punch-out attendance tracking
  • Real-time web dashboard hosted on the ESP32-S2
  • Accurate date, time, and day using NTP synchronization (IST)
  • UID-based user identification and attendance logging
  • Automatic detection and registration of unknown RFID cards
  • Live status display (“In” / “Out”) for each user
  • CSV export of attendance records for easy reporting
  • SPI-based MFRC522 communication with flexible pin mapping
  • Dynamic data handling using arrays
  • Fully standalone system requiring only Wi-Fi connectivity
Applications
  • Classroom and laboratory attendance systems
  • Office and workplace entry tracking
  • Training centers and workshops
  • Educational IoT and embedded systems projects
  • Access monitoring and time-logging solutions
  • Small organizations needing low-cost attendance automation

By combining RFID, Wi-Fi, and real-time web technologies, this IoT-based attendance system delivers a practical, scalable, and accurate solution for modern attendance tracking. With automated user registration, precise NTP-synced timestamps, and easy data export, it serves as a strong foundation for smart campus, office, or institutional monitoring systems.

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