Assessment of Innovative Architectures, Challenges and Solutions of Edge Intelligence

Abstract

Data collecting, caching, analysis, and processing in close proximity to where the data is collected is referred to as "edge intelligence," a group of linked devices and systems. Edge Intelligence aims to improve data processing quality and speed while also safeguarding the data's privacy and security. This area of study, which dates just from 2011, has shown tremendous development in the last five years, despite its relative youth. This paper provides a survey of the architectures of edge intelligence (Data Placement-Based Architectures to Reduce Latency; 2) Orchestration-Based ECAs- IoT. 3) Big Data Analysis-Based Architectures; and 4) Security-Based Architectures) as well as the challenges and solutions for innovative architectures in edge intelligence.