How Edge Computing and AI Will Benefit the Biometric Identification Technology Market


The advancement of cutting-edge AI hardware and software offers a significant opportunity to improve the accuracy and security of biometric identification technologies. How? ‘Or’ What? The simplest answer is that edge computing can help by processing data closer to where it is created.

Edge computing can improve the performance of video analytics applications and other services by reducing latency. For biometrics, data management and privacy are equally important reasons to use edge computing. The question then becomes where to deploy the application; although the answer increasingly lies “on the device itself”, it is still useful to understand how cameras, voice and hand recognition systems will interact with nearby systems to provide advanced functionality and improve the precision.

This white paper Biometric Update, written by editor Jim Davis, is designed as an introduction to understanding the basics of edge computing and where it will impact biometric identification systems.

The paper examines edge computing architecture (where edge computing is used) then applies this framework to contextualize biometrics and edge computing use cases such as:

  • Biometrics at the edge of smart devices and on-premises data centers
  • Retail
  • Warehouses/Manufacturing
  • Automotive/Transportation
  • On-access and regional edge biometrics
  • smart city

The paper also highlights some of the key trends in cutting-edge artificial intelligence processors and algorithms that will enable further advances in edge-powered biometrics.

Complete the form on this page for immediate access to “Biometrics at the Edge: How Edge Computing Should Benefit the Biometric Identification Technology Market”.

Article topics

biometric identification | biometrics | state-of-the-art biometrics | AI edge | advanced computing | retail biometrics | smart cities | transportation | white paper


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