발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.6] Cloud Caching-Based Research for Real-Time Facial Recognition Access System |
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| 논문투고자 |
Cheol-Ju Ryu, In-Sik Hong |
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| 논문내용 |
In recent years, facial recognition technology has garnered significant attention across various fields,playing crucial roles in personal identification, security systems, and access control. Particularly, facialrecognition technology is widely used for smartphone unlocking and small-group access systems, owingto its stability and touchless convenience. However, deploying this technology in large-scaleenvironments like public transportation presents complex challenges in real-time data processing fornumerous simultaneous users. Addressing these challenges, this study proposes an innovative real-timecloud caching approach integrated with a facial recognition access system designed for new embeddedboards. The method involves pre-copying user data from the cloud server to a local cache server upondetecting the user's MAC address, effectively reducing data access times. This approach significantlyenhances the performance of real-time facial recognition systems, especially in scenarios with high datavolume and concurrent users. Implementation and validation of this approach in a university lectureroom setting, utilizing Raspberry Pi 3 Model B+, wireless AP, camera module, 'Dlib' library, and a32GB SD card, demonstrate its efficacy in overcoming challenges related to data capacity and real-timeprocessing, resulting in considerable time savings. These findings represent a noteworthy advancement inthe field of large-scale facial recognition technology. |
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