This project is a Wi-Fi-based attendance tracking system designed to automate student attendance recording by leveraging network connection data. Instead of relying on manual check-ins or QR scans, the system detects when a user’s device connects to the institution’s Wi-Fi network and logs the event securely in a backend database.

MarkMyClass is a smart attendance management application that leverages GPS and WiFi-based verification to ensure accurate, location-based attendance tracking.

ESP32-based attendance tracking system combining NFC technology with WiFi connectivity for seamless, contactless attendance management.

Secure WiFi-based attendance system with Admin and Employee roles for real-time check-in, tracking, and reporting 📶📊

IoT-based attendance system using ESP32 that automates user identification and records real-time attendance via RFID Card. It reduces manual errors, prevents proxy attendance, and enables WiFi-based data transmission for efficient and scalable tracking.

University attendance management system built with Flutter and Firebase. Features QR code-based attendance tracking with time validation, WiFi verification, student/teacher authentication, real-time attendance monitoring, and export to PDF/Excel formats. Clean MVC architecture for maintainable code.

A microservice-based staff and student management system built using Django and Python. The project automates attendance tracking through WiFi signal detection and manages communication using Gmail API–based automated email templates.The system improves workflow accuracy and reduces manual work through automation.

This project is a real-time employee attendance and monitoring system that automatically tracks workers based on their connection to office WiFi networks. Unlike traditional systems that rely on manual login/logout, this system uses network-level detection (MAC address tracking) to determine when employees start and stop working.