Despite the heightened interest in touch-free biometrics during the pandemic, the proven reliability of fingerprint-based access control systems remains undiminished on the global stage. These systems, celebrated for their unobtrusive nature and general familiarity, are a mainstay in security provisions.
Yet, in a dynamic market, standing still is not an option. The industry's thought leaders are actively infusing artificial intelligence into these systems, aiming to bolster both their accuracy and efficiency. With AI dramatically reshaping the landscape of the physical security domain, its foray into biometrics was a logical, if not inevitable, progression.
Along this line, the leading access control solutions provider Suprema recently launched BioStation 2a, the world’s first deep learning-based fingerprint recognition solution. Speaking to asmag.com recently, Suprema Inc. CEO, Hanchul Kim, explained that BioStation 2a leverages the power of an embedded neural processing unit to dramatically increase accuracy and speed.
“BioStation 2a is an advancement to Suprema’s previous model BioStation 2,” explained Suprema Inc. CEO, Hanchul Kim. “An AI processor, NPU (Neural Processing Unit), optimized for deep learning is embedded in BioStation 2a, so the fingerprint recognition performance is highly accurate and fast.”
The BioStation 2a is equipped with an AI processor that is specifically optimized for deep learning applications.
The evolution from BioStation 2 to the enhanced BioStation 2a showcases the blending of traditional fingerprint recognition with cutting-edge deep learning technologies to redefine security standards. Here are some of the key features that can be considered as an upgrade.
1. Deep learning integration: BioStation 2a stands out as the world's first fingerprint recognition solution powered by deep learning. This inclusion ensures heightened accuracy, particularly in recognizing low-quality or distorted prints.
2. Neural Processing Unit (NPU): BioStation 2a is equipped with an NPU that’s optimized for deep learning. This ensures a swift and precise fingerprint recognition performance, setting it apart from its predecessor and other offerings in the market.
“Typically, devices implementing AI algorithm require the expensive GPUs along with extensive memory capabilities,” Suprema Inc. CEO, Hanchul Kim, said. “However, Suprema's expertise in creating lightweight AI engine optimized for edge device ensures stable and high performance in running AI algorithm while preventing overheating and hardware slowdowns.”
3. User capacity: With a potent 1.5GHz Quad CPU and expansive memory, BioStation 2a supports up to 100,000 users, a significant increase from the capacity of BioStation 2.
“Through deep learning, the ability to extract templates from low-quality fingerprints, such as those that are noisy or distorted, has significantly improved, leading to higher accuracy rates,” explained Suprema Inc. CEO, Hanchul Kim. “With a high-performance 1.5GHz Quad CPU and a large-scale memory capacity, BioStation 2a holds up to 100,000 users, which is increased by five times compared to BioStation 2.”
4. Multi-credential options: While both models offer diverse authentication methods, BioStation 2a further elevates the user experience with its broader range of multi-credential options, supporting mobile access both BLE and NFC, blending security with convenience.
5. Performance: The latest iteration boasts superior speed and efficiency in processing requests, making it an ideal fit for high-traffic areas requiring rapid and reliable access control.
Deep learning, a subset of artificial intelligence, has been instrumental in transforming various industries, from healthcare diagnostics to autonomous vehicles. It allows machines to process and interpret vast amounts of data by mimicking human-like neural networks. But how exactly does it supercharge fingerprint recognition, a longstanding security system?
Accuracy enhancement: At the core of deep learning's prowess is its ability to discern intricate patterns and minute discrepancies. When applied to fingerprint recognition, deep learning algorithms can accurately identify even the most subtle variances in fingerprints, reducing the risk of false negatives and false positives.
Handling low-quality prints: One of the challenges in fingerprint recognition is interpreting smudged or partial prints. Thanks to deep learning algorithms, systems like Suprema's BioStation 2a can extract clear templates from such compromised inputs. This adaptability ensures a seamless authentication process, regardless of fingerprint quality.
“This algorithm, critical in enhancing the accuracy of fingerprint recognition, particularly for low-quality prints, was carefully developed,” Suprema Inc. CEO, Hanchul Kim, pointed out. “In practical tests, it exhibited over 30 percent improvement in accuracy compared to previous versions and other products available in the market for challenging fingerprint recognition scenarios.”
Adaptive learning: Traditional fingerprint systems operate based on a fixed database of saved prints. Deep learning-powered systems, however, continuously learn and adapt. They fine-tune their recognition parameters with each scan, becoming more refined and efficient over time.
Speed optimization: In today's fast-paced world, speed is of the essence. Deep learning ensures that the sophistication of fingerprint analysis doesn't come at the cost of speed. Even with the rigorous analysis that these systems undertake, users experience almost instantaneous results.
Versatility in application: Deep learning's robustness isn't just about identifying fingerprints. It allows systems to integrate and operate in tandem with other data, like RFID and mobile-credentials, creating a multi-faceted security system.
Edge devices are gaining a name for themselves in the cutting-edge field of biometric security thanks to their unmatched benefits. This relies heavily on local processing, which enables data to be processed locally and guarantees quicker response times while also removing any potential delays that can compromise security.
This approach also diminishes the dependency on external network bandwidth, guaranteeing speed and consistent operation, especially in areas with fluctuating network conditions.
Moreover, by processing and storing data locally, solutions like BioStation 2a can improve data privacy, significantly reducing breach risks from external threats. Complementing these benefits is its scalability and flexibility, enabling integration into existing infrastructures, simplifying upgrades, and system expansions.
BioStation 2a's enhanced capabilities open doors to an array of applications beyond traditional access control. High-traffic areas benefit immensely from its rapid and precise recognition, ensuring smooth flow while maintaining security.
“Suprema’s biometric and mobile credentials are highly beneficial because, unlike physical keys, RFID cards, and PIN, it is impossible for biometric data to be lost, forgotten or stolen,” Suprema Inc. CEO, Hanchul Kim, pointed out. “Suprema’s fingerprint recognition and mobile credential are now widely used for access control to ensure that only authorized personnel are permitted entry to restricted areas. BioStation 2a offers a range of credential options - fingerprint, RFID, and mobile access (BLE/NFC) - which not only enhances user experience but also elevates security to new levels with highly accurate fingerprint recognition technology.”
BioStation 2a is suitable for both outdoor and indoor settings, from small offices to large enterprise buildings. Its extended USB host facilitates effortless feature additions for users. With an IP65 rating and an operating temperature ranging from -20℃ to 60℃, it promises durability even in the harshest environments.
In short, the role of AI in biometric access control has become increasingly evident. As we navigate a world with growing security complexities and vast datasets, the need for swift and accurate recognition systems is paramount. AI aids in detecting subtle biometric differences efficiently.
Suprema's BioStation 2a is an excellent example to this integration, illustrating the practical applications of combining AI with biometrics. As we move forward, it's clear that the synergy of these technologies will be central to shaping the future of access control systems.