Real-Time Secure Access Control Using AXI- Enabled Facial Recognition System.

Abstract—This paper presents a strong system where an Advanced extensible Interface, AXI4 bus protocol has been integrated with a facial recognition framework based on Python to produce a highly scalable biometric access control solution. The system captures the image of the user's face, which it then processes, in order to extract critical facial features using OpenCV and face recognition libraries. These attributes are converted into a 512-bit hexadecimal code that constitutes the user's biometric. The hex code is transmitted efficiently through AXI4 in burst mode such that the system may process big data with low latency. Using AXI4's multiple independent channels, low-latency, high- throughput data transfer is allowed, making it appropriate for real-time security applications. The integration of AXI4 protocol with Python permits hardware and software modules to work in synchronization across the transmission process in a way that guarantees integrity and security of data being transferred. This mechanism, based on results obtained from thorough testing and simulations, has been shown to provide a reliable, secure, and fast mechanism for facial recognition in real-world environments while further optimizing the performance of large-scale systems.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-10
DOI
https://doi.org/10.55041/ijsrem47361
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Real-Time Secure Access Control Using AXI- Enabled Facial Recognition System.

Yarra Nitin
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
IoT-based Smart Home Systems
article

Real-Time Secure Access Control Using AXI- Enabled Facial Recognition System.

Yarra Nitin
article en

Abstract

Abstract—This paper presents a strong system where an Advanced extensible Interface, AXI4 bus protocol has been integrated with a facial recognition framework based on Python to produce a highly scalable biometric access control solution. The system captures the image of the user's face, which it then processes, in order to extract critical facial features using OpenCV and face recognition libraries. These attributes are converted into a 512-bit hexadecimal code that constitutes the user's biometric. The hex code is transmitted efficiently through AXI4 in burst mode such that the system may process big data with low latency. Using AXI4's multiple independent channels, low-latency, high- throughput data transfer is allowed, making it appropriate for real-time security applications. The integration of AXI4 protocol with Python permits hardware and software modules to work in synchronization across the transmission process in a way that guarantees integrity and security of data being transferred. This mechanism, based on results obtained from thorough testing and simulations, has been shown to provide a reliable, secure, and fast mechanism for facial recognition in real-world environments while further optimizing the performance of large-scale systems.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Openalex Percentile: Top 92%
IoT-based Smart Home Systems
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