Face Recognition Technology for Arduino-Based Attendance Systems

Face recognition technology has become increasingly popular in recent years and has been widely implemented across various sectors such as security, transportation, and healthcare. One practical application of this technology is in attendance systems, where users can use their facial identity to check in or check out of a room or system.

This article discusses the implementation of a face recognition–based attendance system using Arduino. Arduino is a flexible computing platform that can be used to develop a wide range of electronic projects, including attendance systems that leverage face recognition technology.

System Overview

Before starting the implementation, several hardware components and software tools are required. First, a camera is needed to capture facial images. The camera should have sufficient resolution and be capable of capturing clear images. In addition, a face detection or recognition module—such as one based on OpenCV—is required to process and recognize facial data.

On the software side, the OpenCV library is needed to implement face recognition functionality within an Arduino-based attendance system. This library enables image processing and facial recognition tasks.

Once all required components and software are prepared, the next step is to develop an Arduino program capable of capturing facial images, processing them using OpenCV, and performing face recognition.

Implementation Steps

The following steps outline the implementation of an Arduino-based attendance system using face recognition technology:

Install the camera and face recognition module on the Arduino system.
Develop an Arduino program to capture images from the camera and store them in memory.
Use the OpenCV library to process the captured images and perform face recognition.
After successful face recognition, the system outputs user information such as name and identification number.
The recognized user information is stored in a database for future reference.

By implementing face recognition technology in an Arduino-based attendance system, attendance tracking becomes more efficient and accurate. Users can record their attendance quickly and easily using their face as an identity, without manual input or physical attendance devices.

Required Components

To build an Arduino-based attendance system using face recognition technology, the following components are required:

Arduino board (e.g., Arduino Uno, Arduino Nano)
USB camera (e.g., Raspberry Pi Camera, Logitech Webcam)
Face recognition module (e.g., OpenCV Face Detection Module)
Breadboard
Jumper wires
Resistors (optional)
LEDs (optional)
Arduino IDE software
OpenCV library for Arduino

The choice of camera and face recognition module depends on system requirements and available budget. It is important to select a camera with sufficient resolution and a face recognition module that is fully compatible with the OpenCV library.

Resistors and LEDs can be used as visual indicators to show system status, such as when face recognition is in progress or when a user has been successfully identified. However, these components are optional and not strictly required.

Hardware Connections

Follow these steps to assemble the hardware components:

Connect the camera VCC pin to the 5V pin on the Arduino board.
Connect the camera GND pin to the GND pin on the Arduino board.
Connect the camera Data pin to Digital Pin 2 on the Arduino board.
Connect the face sensor module VCC pin to the 5V rail on the breadboard.
Connect the face sensor module GND pin to the GND rail on the breadboard.
Connect the SCL pin of the face sensor module to Analog Pin A5 on the Arduino board.
Connect the SDA pin of the face sensor module to Analog Pin A4 on the Arduino board.
Connect a resistor to Digital Pin 8 on the Arduino board.
Connect the LED anode to the resistor.
Connect the LED cathode to the GND rail on the breadboard.

After completing all connections, carefully recheck the wiring and test the system to ensure all components function correctly.

Coding/Script

#include <Servo.h> // Library for controlling servo motors

#include <Wire.h> // Library for I2C communication

#include <LiquidCrystal_I2C.h> // Library for LCD display

#include <SoftwareSerial.h> // Library for serial communication

#include <Adafruit_MLX90614.h> // Library for temperature sensor

// Object initialization

Servo myservo;

LiquidCrystal_I2C lcd(0x3F, 16, 2);

SoftwareSerial bluetooth(2, 3);

Adafruit_MLX90614 mlx = Adafruit_MLX90614();

// Global variables

int pos = 0;

int led = 8;

int detect = 0;

void setup()

{

pinMode(led, OUTPUT); // Set pin 8 as output

myservo.attach(9); // Attach servo to pin 9

lcd.init(); // Initialize LCD

lcd.backlight(); // Turn on LCD backlight

mlx.begin(); // Initialize temperature sensor

bluetooth.begin(9600); // Initialize Bluetooth communication

Serial.begin(9600); // Initialize serial communication

}

void loop()

{

int val = analogRead(0); // Read value from A0 pin

if (val < 400)

{

digitalWrite(led, HIGH); // Turn on LED

myservo.write(0); // Rotate servo to 0 degrees

delay(500);

detect = 1;

lcd.clear();

lcd.setCursor(0, 0);

lcd.print("Face Detected");

bluetooth.print("Face Detected");

}

else

{

digitalWrite(led, LOW); // Turn off LED

if (detect == 1)

{

myservo.write(90); // Rotate servo to 90 degrees

delay(500);

detect = 0;

}

float tempC = mlx.readObjectTempC(); // Read temperature

Serial.print("Temperature: ");

Serial.println(tempC);

delay(1000);

}

Conclusion

By combining face recognition technology with Arduino, it is possible to build an effective and efficient attendance system. This system improves security and attendance speed while reducing physical contact with attendance devices—an important advantage in preventing virus transmission.

However, like any technology, face recognition–based attendance systems also have limitations and risks. Recognition accuracy may decrease under poor lighting conditions or camera interference. Additionally, privacy concerns must be carefully considered, particularly regarding the collection and use of biometric data such as facial images.

Therefore, before adopting face recognition technology for attendance systems, it is essential to evaluate both its benefits and potential risks, and to comply with applicable regulations and guidelines related to biometric data collection and usage.