Exploring edge computing in artificial intelligence using service aggregation standards

Abstract

Edge computing is to support physical impairment evaluation, execution monitoring, alarm message filter based on an On-board artificial intelligence approach. Now a day a smart approach called Artificial Intelligence is being developed to pretend thinking and learning ability of human beings. Since Machine Learning is incorporated with an advanced tool it has several industrial applications such as manufacturing, petrochemical, and power plants. An artificial intelligence which is a development of edge computing (EC) in fifth-generation (5G) networks can be meet the needs of everything as a service in the networks edge. Since the theory of edge-artificial intelligence is much useful in fulfillment of AI service. Cloud computing has more computational complexity and delay, so edge computing will be preferred in terms of back-up & restore data and reliability in internet of things (IoT) based industrial applications. In industrial devices the computational speed and range of internet of things (IoT) at edge can be enhanced with aid of artificial intelligence. In this paper an AI-based service aggregation problem using edge computing in various industrial applications will be implemented. The energy efficiency, good duty cycle, storage capacity and reliability can be achieved by using Service Aggregation Edge Computing (SAEC).