Edge Intelligence in the Making Organization, Deep Learning, and Applications

With the explosive growth of mobile computing and Internet of Things (IoT) applications, as exemplified by AR/VR, smart city, and video/audio surveillance, billions of mobile and IoT devices are being connected to the Internet, generating zillions of bytes of data at the network edge. Driven by this trend, there is an urgent need to push the frontiers of artificial intelligence (AI) to the network edge to fully unleash the potential of IoT big data.

Sen Lin, Arizona State University
Zhi Zhou, Sun Yat-sen University
Zhaofeng Zhang, Arizona State University
Xu Chen, Sun Yat-sen University
Junshan Zhang, Arizona State University

To facilitate the dissemination of the recent advances in edge
intelligence in both academia and industry, this book conducts a
comprehensive and detailed survey of the recent research efforts and
also showcases the authors’ own research progress on edge
Specifically, the book first reviews the background and present
motivation for AI
running at the network edge. Next, it provides an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning models toward training/inference at the network edge.
To illustrate the research problems for edge intelligence, the book also showcases four of the authors’ own research projects on edge
intelligence, ranging from rigorous theoretical analysis to studies basedon realistic implementation. Finally, it discusses the applications, marketplace, and future research opportunities of edge intelligence.
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