FACE ATTENDANCE SYSTEM

The system depicted in the block diagram is designed to integrate multiple components for a compact, intelligent monitoring and identification setup using a Raspberry Pi 3B+. The core of the system is the Raspberry Pi, which acts as the central processing unit, managing communication between various peripheral devices. A 230V AC to 5V DC adapter is used to power the Raspberry Pi, ensuring a stable power supply for uninterrupted operation. The system includes an RFID reader to identify tags and a USB camera for visual input, allowing it to verify or capture real-time data based on the object or individual detected. A 32GB SD card is connected to the Raspberry Pi to serve as the primary storage medium for the operating system, data logging, and software necessary for system operation. Additionally, LEDs are used for indication purposes, providing visual feedback based on the system’s responses, such as successful authentication or error alerts. This configuration is suitable for various applications including automated attendance systems, access control, and surveillance, where both identification and visual confirmation are necessary. The Raspberry Pi’s capability to handle multiple interfaces and devices simultaneously makes it an ideal choice for such embedded applications. The system is cost-effective, scalable, and can be easily customized to suit different use cases by modifying the software or expanding hardware peripherals. The modular design allows for future enhancements, such as integrating Wi-Fi or cloud connectivity, to increase functionality and enable remote access or monitoring, making it a versatile platform for smart system development.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-01
DOI
https://doi.org/10.5281/zenodo.16889902
Primary Topic
Prenatal Screening and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
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article

FACE ATTENDANCE SYSTEM

Zenodo (CERN European Organization for Nuclear Research)
Prenatal Screening and Diagnostics
article

FACE ATTENDANCE SYSTEM

article en

Abstract

The system depicted in the block diagram is designed to integrate multiple components for a compact, intelligent monitoring and identification setup using a Raspberry Pi 3B+. The core of the system is the Raspberry Pi, which acts as the central processing unit, managing communication between various peripheral devices. A 230V AC to 5V DC adapter is used to power the Raspberry Pi, ensuring a stable power supply for uninterrupted operation. The system includes an RFID reader to identify tags and a USB camera for visual input, allowing it to verify or capture real-time data based on the object or individual detected. A 32GB SD card is connected to the Raspberry Pi to serve as the primary storage medium for the operating system, data logging, and software necessary for system operation. Additionally, LEDs are used for indication purposes, providing visual feedback based on the system’s responses, such as successful authentication or error alerts. This configuration is suitable for various applications including automated attendance systems, access control, and surveillance, where both identification and visual confirmation are necessary. The Raspberry Pi’s capability to handle multiple interfaces and devices simultaneously makes it an ideal choice for such embedded applications. The system is cost-effective, scalable, and can be easily customized to suit different use cases by modifying the software or expanding hardware peripherals. The modular design allows for future enhancements, such as integrating Wi-Fi or cloud connectivity, to increase functionality and enable remote access or monitoring, making it a versatile platform for smart system development.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 34%
Prenatal Screening and Diagnostics
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FACE ATTENDANCE SYSTEM · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS