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Enhancing Low-Energy Facial Recognition Devices and Abilities To Improve Security: A Practical Study

As facial recognition (FR) continues to advance, so too has the need for its applications, especially in the realm of security. However, despite FR’s sophistication, issues remain: accuracy, the amount of energy needed to run FR technology, the need for FR on mobile devices, and the speed and efficiency of FR, especially when applied to the identification and tracking of cyber criminals and terrorists. In this paper, we address these concerns and present an approach to detect and identify a human face by tracking an image and comparing it with other image data. We used the adaptable, easy-to-use, and inexpensive Raspberry Pi Zero, a device that can scrape data off the web quickly and efficiently, and then identify a specifically targeted individual. We believe our approach can greatly enhance the effectiveness of FR for applications such as border security, providing on-the-ground agents with real-time data and mobile devices that are low cost, energy efficient, and convenient.