As IoT devices proliferate, we are inundated with data. These require real-time intelligence and lightning-fast answers, which are Beyond the abilities of traditional cloud-based configurations. With the Hard lifting of computation, storage, and intelligence done right next To the source of the data, edge computing changes the game. This solves Many problems, including system reliability, latency, bandwidth issues, And privacy issues. This survey will look in more depth at IoT edge Computing. Architectures, frameworks, and the latest approaches are All included. We will look at the different levels of these systems And see how it has evolved from cloud, to fog, to edge computing. There are different types, including lightweight machine learning, Network-wide analytics, and combinations of edge and cloud Computing. The areas where this information is relevant include smart cities, Hospitals, industries, self-driving cars, and environmental Monitoring, according to this report. Real-world examples and real-world Performance improvements, not just theory. Then there is the major Challenge and the way ahead: how to set standards, get different Systems to talk to each other, coordinate everything seamlessly, and Finally, make it all highly reliable edge intelligence.
Shafoon et al. (2026) studied this question.