The term " Edge Artificial Intelligence (Edge AI)" refers to the part of a network where data is analysed and aggregated.
Dispersed networks, such as those found in the Internet of Things (IoT), have enormous ramifications when it comes to "Edge AI," or
"intelligence at the edge". Smartphone applications like real-time traffic data and facial recognition data, including semi-autonomous
smart devices and automobiles are integrated in this class. Edge AI products include wearable health monitors, security cameras, drones,
robots, smart speakers and video games. Edge AI was established due to the marriage of Artificial Intelligence with cutting Edge
Computing (EC) systems. Edge Intelligence (EI) is a terminology utilized to define the model learning or the inference processes, which
happen at the system edge by employing available computational resources and data from the edge nodes to the end devices under cloud
computing paradigm. This paper provides a light on "Edge AI" and the elements that contribute to it. In this paper, Edge AI's motivation,
definition, applications, and long-term prospects are examined.
Keywords
Artificial Intelligence (AI), Edge Artificial Intelligence (Edge AI), Edge Computing (EC), Internet of Things (IoT),
Machine Learning (ML).
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Acknowledgements
The authors would like to thank to the reviewers for nice comments on the manuscript.
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Corresponding author
Anandakumar Haldorai
Anandakumar Haldorai
Department of Computer Science and Engineering, Sri Eshwar College of Engineering, India.
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Cite this article
Anandakumar Haldorai, Shrinand Anandakumar, “Motivation, Definition, Application and the Future of Edge Artificial Intelligence", vol.2, no.3, pp. 077-087, July 2022. doi: 10.53759/181X/JCNS202202011.
