Edge AI:  Principles, Technologies, and Applications

Overview

Edge computing is a key emerging paradigm that enables data processing at or near where it is generated. This close proximity helps lower latency, network bandwidth, and costs, all while improving performance, privacy, and overall user experience. It also contributes to making the planet greener by saving significant amounts of energy necessary for transferring data to cloud-based data centers for processing and then back to clients for consumption. Edge artificial intelligence (AI) builds on this foundation by enabling developers to deploy and run machine learning (ML) models directly on edge devices, including edge gateways and servers, as well as small microcontrollers and constrained IoT devices, allowing inference to be done locally. Given that some estimates predict more than 60% of data will be processed at the edge by 2027, growing to nearly 80% by 2029, understanding this critical technology is essential for next-generation AI/ML applications. To this end, this book will be written for researchers and industry practitioners working in the areas of distributed computing, AI/ML, IoT, and embedded systems to help them understand and utilize this important technology and have some insights into its current challenges and future research directions.

Publisher

Wiley-IEEE Press

Indexing

The book is indexed by IEEE and its partners. The book and its individual chapters will be listed on IEEE Xplore.

Readership

This book targets students, educators, researchers, industry practitioners, policymakers, and government/smart infrastructure planners working in the fields of AI, edge computing, and IoT. 

Chapters of Interest

The editor is interested in quality, comprehensive review chapters on the following topics (non-exhaustive list):

Core Concepts

• Introduction to Edge AI

• AI Foundations for the Edge

• Edge AI Enabling Technologies

Key Technologies and Methodologies

• AI Model Compression and Optimization for the Edge

• Edge AI in Resource-Constrained Environments

• Edge AI Infrastructure and Hardware

• Edge AI Software and Frameworks

• Data Foundations for Edge AI

• Communication and Networking for Edge AI

• On-Device AI Models and Techniques

• Distributed AI across the Edge-Cloud Continuum

• Edge AI with Semantic Communications

• AI for Optimizing Edge Network Operations

• Generative AI at the Edge

• Security, Privacy, and Resilience in Edge AI Systems

• Maintenance, Updates, and Scalability in Edge AI Deployments

Application Domains

• • Edge AI in Smart Manufacturing and Automation

  • Edge AI in Smart Cities and Infrastructure

  • Edge AI in Smart Grids

  • Edge AI in Autonomous Vehicles/UAVs

  • Edge AI in Maritime

  • Edge AI in Healthcare

  • Edge AI in Agriculture

  • Edge AI in Supply Chain Management

  • Edge AI in Retail

  • Edge AI in Surveillance/Environmental Monitoring

  • Edge AI in Consumer Electronics/Smart Buildings

  • Edge AI in Robotics/Swarm Robotics

  • Edge AI in Defense and Mission-Critical Systems

  • AI-Enhanced Cybersecurity and Threat Detection for the Edge

Emerging Trends and Future Directions

• Open Challenges and Research Directions

• Standardization, Benchmarking, and Reproducibility in Edge AI Research

• Towards Fully Autonomous, Private Edge Intelligence

• Edge AI for 5G/6G and Beyond

• Edge AI and Digital Twins

• Edge AI and the Metaverse

• Green Edge AI and Sustainable Systems

Practical Projects and Tutorials

• Novel Applications, Implementations, and Solutions

• Tutorials on the Implementation of Edge AI Environments (e.g., edge-hosted LLMs)

• Tutorials on Deploying and Running Machine Learning Models on Microcontrollers and Edge Hardware

Submission Procedure

Experienced researchers and practitioners with a proven track record of academic publications are invited to submit their chapter proposals for an initial evaluation. A typical chapter proposal should be saved in Word format and include the following:

• 5-10 keywords.

• An extended abstract (350+ words) that clearly explains the topic and chapter contribution.

• A tentative table of contents (chapter's sections with brief descriptions).

• Authors' short bios, affiliations, emails, and Google Scholar links.

Important

• • • There are NO submission or processing fees.

    • Authors of accepted chapters will receive a free copy of the book after publishing.

    • Contributors may submit multiple proposals.

    • All manuscripts must be original and not concurrently under consideration by other books, journals, or conferences. The publisher will check accepted chapters for plagiarism (later in the process), and those with more than 10% plagiarism/self-plagiarism will be rejected.

    • Depth, coherence, and excellent language are key to accepting chapters for this book.

    • All manuscripts will be thoroughly reviewed (first by the editor and then by a reviewer). Accepted chapters will later be reviewed by the publisher.

    • Authors of accepted chapters may be asked to help in reviewing some of the received chapters.

    • Proposals, manuscripts, and inquiries should be sent to the editor at qusayfadhel@gmail.com.

Important Dates

• Proposal Submission: September, 22, 2025

• Proposal Review Notification:  September 29, 2025

• Full Chapter Submission: January 15, 2026

• Acceptance/Revision Notification: February 1, 2026

• Revised Chapter Submission: February 15, 2026

• Camera-Ready: February 30, 2026

• Publication Date: 2026 (Q4)

Manuscript Format

• • • Typically, a full chapter should have a minimum of 20 single-spaced pages (excluding references), an abstract (150 words max), 5–10 keywords, figures, references, a glossary (key terms and definitions), and a list of abbreviations.

    • Authors must proofread and polish their manuscripts before submission. 

    • Accepted chapters must be formatted in accordance with the publisher's guidelines (will be provided later). 

About the Editor

Qusay F. Hassan, Ph.D., is an independent researcher and technology evangelist with over 20 years of industry experience in information communication technology (ICT). Throughout his career, he has held various roles in software development, IT services, and teaching. He is currently an independent technical consultant, advising on emerging ICT trends and enterprise systems. In his previous position as a systems analyst at the U.S. Agency for International Development (USAID), he implemented and managed large-scale data management systems and actively contributed to digital transformation initiatives, helping to adopt new technologies and deliver innovative solutions across sectors. He received his PhD in computer and information sciences from Mansoura University, Egypt, in 2015. His technical experience and research interests are in the areas of distributed computing, software engineering, and big data engineering. He has authored and reviewed many publications in these areas. He is also the editor of several academic and research books, including Internet of Things A to Z: Technologies and Applications (Wiley-IEEE Press, 2018; 2025) and Advances in the Internet of Things: Challenges, Solutions, and Emerging Technologies (CRC Press, 2025). He is a Senior Member of IEEE.