Chapter 7
Edge AI
Chamitha de Alwis,
Quoc-Viet Pham, Madhusanka Liyanage,
Chamitha de Alwis
University of Bedfordshire, Luton, United Kingdom
Search for more papers by this authorBook Author(s):Chamitha de Alwis,
Quoc-Viet Pham, Madhusanka Liyanage,
Chamitha de Alwis
University of Bedfordshire, Luton, United Kingdom
Search for more papers by this authorFirst published: 25 November 2022
Summary
Edge AI, also known as edge intelligence, combines the capabilities of edge computing with Artificial Intelligence (AI) to facilitate sixth-generation applications and services. This chapter details the benefits of edge AI and explores building blocks for edge AI. Edge AI is the processing of AI algorithms on edge, that is, on users' devices. It has several benefits, as follows: reduced latency/higher speeds, further improvement to energy consumption, and so on. The list of edge AI applications is long. Current examples include facial recognition and real-time traffic updates on smartphones, as well as semiautonomous vehicles or smart devices. Several building blocks have been identified to fully reap the potential of edge AI: edge computing, support for advanced edge analytics, edge inference, and edge training. The chapter discusses the architectures in edge AI and covers a generic end-to-end architecture, decentralized edge intelligence architecture, and device-level edge AI architecture.
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