Facial Attendance System
In today's digital era, attendance tracking systems are evolving
rapidly, with emerging technologies offering more efficient and secure
solutions. Among these advancements, Facial Attendance Systems
stand out as innovative tools that leverage facial recognition technology
to streamline attendance monitoring processes.
b. These systems provide a seamless and reliable method for tracking
attendance, eliminating the need for cumbersome manual entry or
traditional card-based systems.
c. The proposed Facial Attendance System aims to harness the
capabilities of Arduino and the ESP32-CAM module, a powerful
microcontroller and camera module combination, to create a cost-
effective and accessible solution.
d. By integrating the ESP32-CAM module with Arduino, the system
can capture high-resolution facial images, process them using a facial
recognition algorithm, and mark attendance accordingly.
e. This project addresses the shortcomings of conventional attendance
systems by offering a more accurate and secure method of attendance
tracking. With facial recognition technology, the system can identify
individuals with remarkable precision, even under varying lighting
conditions and angles.
f. Additionally, by utilizing Arduino and the ESP32-CAM module, the
system can be easily deployed and scaled to meet the needs of diverse
environments, including educational institutions, corporate offices, and
organizational settings.
Components Needed:
• Ardiuno ESP32 CAM Module (₹ 600)
• FIDI Module (₹ 300)
• LEDs or light bulbs (₹ 30)
• Jumper wires (₹ 30)
• Power supply for the Bolt WiFi module
• WiFi router for internet connectivity
• Computer or Raspberry Pi for running the Python script
• Python programming environment (e.g., VS Code or plain
Python)
Roll Number Name Enrollment Number
20322 Harsh
Kadam
2001310163
21321 Yash Inamdar 2101310122
21325 Indrajeet Kadam 2101310136
21337 Suyash Magdum 2101310148