A Journey of Artificial Intelligence and Its Evolution to Edge Intelligence

Abstract

AbstractThe progressions in the innovations and the expansion in the computerized scaling down are making gadgets become more intelligent. The development of Internet of Things (IoT) and the cloud platform have made things stunningly better. Moving all information to the cloud for handling has steadily neglected to meet the continuous prerequisite of IoT benefits because of high network traffic and delay. The restrictions in cloud platform in resource allocation, service providing, and delay in transmission prompt us to move from cloud to edge. Edge computing (EC) moves the computation part from the cloud to the edge nodes (ENs). This will considerably improve the quality of service (QoS) of the IoT programs that demand less latency. With the forward leaps in deep learning, recent research has seen a blasting of artificial intelligence (AI) applications in various fields like suggestion systems, decision systems, and surveillance systems. The rise of the artificial intelligence in the edge computing has ended up being main focus as it boosts up the speed and number of the IOT applications. Edge computing that pushes processing and services from the network center to the network edge, widely accepted as a productive solution. The outcome is edge AI, or edge knowledge (EI) is starting to get a huge measure of interest. The research on edge intelligence is only in the starting stage. We do a comprehensive survey of the recent research efforts on evolution of EI, the security challenges encountered by distributed ENs as they are more defenseless against attacks for shortened computing equipment and storage. The incredible learning capacity of AI empowers the framework to recognize malignant assaults more precisely and effectively.KeywordsArtificial intelligenceEdge nodesEdge computingIoT