This book divides edge intelligence into AI for edge (intelligence-enabled edge computing)
and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to …

Along with the rapid developments in communication technologies and the surge in the use
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …

Today Edge computing is witnessing an essential interest in new use cases, especially after
the introduction of 4G and 5G. Today's many applications/sectors are also heavily investing …

Recent years have witnessed the widespread popularity of Internet of things (IoT). By
providing sufficient data for model training and inference, IoT has promoted the development …

Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …

As an important enabler for changing people's lives, advances in artificial intelligence (AI)-
based applications and services are on the rise, despite being hindered by efficiency and …

In the current era, advancements in deep learning have seen the services and uses of
artificial intelligence (AI) flourish. From individual support and commendation structures to …

"" Traditionally, to develop these intelligent services and applications, big data are stored
and processed in a centralized model. However, with the proliferation of edge devices and …

The Internet of Things (IoT) has created a ubiquitously connected world powered by a
multitude of wired and wireless sensors generating a variety of heterogeneous data over …

This chapter covers the details of implementing AI/ML approaches on edge computing
environments. Before introducing the four key technical components (caching, training …