Edge AI: A Survey

Dr Sukhpal Singh Gill
2 min readMar 7, 2023

Highlights

•Present a future blueprint and comprehensive survey of edge computing & Edge AI.

•Investigate the prospects of Edge AI to deploy AI models on edge devices.

•Discuss the use of ML models for optimization for resource-constrained Edge AI.

•Examine the standardization & performance characteristics of Edge AI environments.

•Highlight trends & open challenges in the area of Edge Computing and Edge AI.

Abstract

Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI refers to the practice of doing AI computations near the users at the network’s edge, instead of centralised location like a cloud service provider’s data centre. With the latest innovations in AI efficiency, the proliferation of Internet of Things (IoT) devices, and the rise of edge computing, the potential of edge AI has now been unlocked. This study provides a thorough analysis of AI approaches and capabilities as they pertain to edge computing, or Edge AI. Further, a detailed survey of edge computing and its paradigms including transition to Edge AI is presented to explore the background of each variant proposed for implementing Edge Computing. Furthermore, we discussed the Edge AI approach to deploying AI algorithms and models on edge devices, which are typically resource-constrained devices located at the edge of the network. We also presented the technology used in various modern IoT applications, including autonomous vehicles, smart homes, industrial automation, healthcare, and surveillance. Moreover, the discussion of leveraging machine learning algorithms optimized for resource-constrained environments is presented. Finally, important open challenges and potential research directions in the field of edge computing and edge AI have been identified and investigated. We hope that this article will serve as a common goal for a future blueprint that will unite important stakeholders and facilitates to accelerate development in the field of Edge AI.

Edge AI: Reshaping the future of edge computing

Bibliography

  1. Raghubir Singh and Sukhpal Singh Gill, Edge AI: A Survey, Internet of Things and Cyber-Physical Systems, Volume 3, Elsevier, 2023. https://doi.org/10.1016/j.iotcps.2023.02.004 (Open Access)

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Dr Sukhpal Singh Gill

Dr. Gill is Assistant Professor in Queen Mary University of London. He is Associate Editor in Elsevier IoT, Wiley ETT & IET Networks. W: https://www.ssgill.me.