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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM36388

FACE RECOGNITION BASED OFFICE RESOURCE CONTROLLING

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM36388

Volume:

8 |

7 |

Jul 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM36388

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

YBR

YASHWANTH B R

SSL

SINDHU S L

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Abstract

In contemporary office environments, effective resource management and access control are essential for maintaining security and optimizing productivity. Traditional methods of resource management and access control, such as manual logging and key-based systems, are often cumbersome, prone to errors, and lack real-time monitoring capabilities. In this paper, we propose a Face Recognition-Based Office Resource Controlling (FROC) system that leverages the capabilities of facial recognition technology to automate resource management and access control processes. The FROC system utilizes advanced deep learning algorithms to accurately identify individuals based on facial biometrics, granting or restricting access to office resources accordingly. By integrating facial recognition technology with centralized resource management software, the FROC system enables seamless and efficient control over office facilities, equipment, and confidential information. Additionally, the system offers real-time monitoring and logging of resource usage, enhancing security and accountability within the office environment. Through a combination of hardware components, including surveillance cameras and access control devices, and software modules for facial recognition and resource tracking, the FROC system provides a comprehensive solution for modern office resource management. We evaluate the performance and effectiveness of the FROC system through extensive testing in simulated office environments, demonstrating its potential to streamline operations, improve security, and optimize resource utilization in office settings.

KEYWORDS

Convolutional Neural Networks image recognition Tensor Flow Deep Learning Teachable Machine

Cite This Article

YASHWANTH B R, SINDHU S L, "FACE RECOGNITION BASED OFFICE RESOURCE CONTROLLING," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 7, Jul 2024. https://doi.org/10.55041/IJSREM36388

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Publication Date

10/6/2024

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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Copyright Form (Office)

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The authors declare no conflict of interest related to this research work.

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