Beyond Horizons - The Rise of the Edge AI Processing Paradigm

1. Auflage 2026
ISBN: 978-87-438-0863-3
Verlag: River Publishers

Buch, Englisch, 138 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: River Publishers Series in Communications and Networking

Welcome to the cutting edge of innovation, where intelligent processing is migrating to every device that interacts with the physical world. The convergence of edge computing, artificial intelligence (AI), and the Internet of Things (IoT) drives a shift in the computing continuum, giving rise to the dynamic and transformative field of edge AI.

This book, a curated collection of research work presented at the European Conference on EDGE AI Technologies and Applications (EEAI), serves as both a ledger and a beacon for this exciting new era of edge intelligence-driven technologies.
The EEAI stands as a vital European forum, bringing together interested minds from academia and industry to explore the entire edge AI technology stack. From silicon circuits, AI accelerators, and specialised hardware platforms to the complexities of advanced algorithms and the architecture of next-generation edge AI systems, the conference fosters a vibrant exchange of ideas that propel the field of edge AI forward.

The research presented in these pages captures the spirit of that collaboration, offering a panoramic view of the challenges being addressed and the groundbreaking solutions being developed.
The book is more than a collection of papers, it is a synopsis presenting the real-world impact of edge AI. It moves beyond theoretical discussions to showcase how these technologies are being applied to solve some of the most pressing challenges.

The chapters of the book navigate from the complex urban landscapes of last-mile delivery to the fertile fields of smart agriculture, discovering how intelligent systems are creating new efficiencies, enhancing security, and redefining what is possible at the network's edge.
We invite you to immerse yourself in these chapters, not just as a reader but as a participant in the ongoing dialogue that is shaping the future of edge intelligence.

Whether you are a curious and creative researcher, an innovative engineer, or a student eager to understand the next wave of edge AI processing, the insights shared here provide a comprehensive and deep understanding of the technologies and applications that are bringing intelligence to the edge.

Zielgruppe

Academic, Postgraduate, and Professional Practice & Development

Autoren/Hrsg.

Chersi, Fabian

Vermesan, Ovidiu

Coppola, Marcello

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

1. Edge AI Systems Verification and Validation 2. Pioneering the Hybridization of Federated Learning in Human Activity Recognition 3. Edge Intelligence Architecture for Distributed and Federated Learning Systems 4. Challenges and Performance of SLAM Algorithms on Resource-constrained Devices 5. Designing Accelerated Edge AI Systems with Model Based Methodology 6. EDGE AI Hardware Acceleration for Critical Systems: from FPGAs Automatic Hardware Generator to Versatile CGRAs Systems 7. Model Selection and Prompting Strategies in Resource Constrained Environments for LLM-based robotic system 8. Optimising ViT for Edge Deployment: Hybrid Token Reduction for Efficient Semantic Segmentation 9. Recent Trends in Edge AI: Efficient Design, Training and Deployment of Machine Learning Models 10. Scalable Sensor Fusion for Motion Localization in Large RF Sensing Networks 11. The Accountability Strikes Back: Decentralizing the Key Generation in CL-PKC with Traceable Ring Signatures 12. A TinyMLOps Framework for Real-world Applications 13. Transfer and Self-learning in Probabilistic Models 14. A novel hierarchical approach to perform on-device Energy Efficient Fault Classification 15. Discovering and Classifying Digital and Wooden Industries Products’ Defects at the Edge by a Yolo/ResNet-based Approach and Beyond 16. Conscious Agents Interaction Framework for Industrial Automation 17. Neuromorphic IoT Architecture for Efficient Water Management: A Smart Village Case Study 18. Online AI Benchmarking on Remote Board Farms 19. Enhancing Sustainability in Water Resource Management: Optimizing Neural Network Architectures for Accurate Prediction of Water Stress in European Countries 20. Multi-step Object Re-identification on Edge Devices: A Pipeline for Vehicle Re-identification

Über Autor(innen)

Dr. Ovidiu Vermesan holds a PhD degree in microelectronics and a Master of International Business (MIB) degree. He is Chief Scientist at SINTEF Digital, Oslo, Norway. His research interests are intelligent systems integration, mixed-signal embedded electronics, analogue neu-ral networks, edge artificial intelligence and cognitive communication systems. Dr. Ver-mesan received SINTEF’s 2003 award for research excellence for his work on implementing a biometric sensor system. He is currently working on projects addressing nanoelectronics, integrated sensor/actuator systems, communication, cyber-physical systems (CPSs) and the Industrial Internet of Things (IIoT), with applications in green mobility, energy, autonomous systems, and smart cities. He has authored or co-authored over 100 technical articles and conference papers. He is actively involved in the activities of the European partnership for Key Digital Technologies (KDT) Joint Undertaking (JU), now the Chips JU. He has coordinat-ed and managed various national, EU and other international projects related to smart sensor systems, integrated electronics, electromobility and intelligent autonomous systems such as E3Car, POLLUX, CASTOR, IoE, MIRANDELA, IoF2020, AUTOPILOT, AutoDrive, Archi-tectECA2030, AI4DI, AI4CSM. Dr. Vermesan actively participates in national, Horizon Eu-rope and other international initiatives by coordinating and managing various projects. He is a member of the Alliance for AI, IoT and Edge Continuum Innovation (AIOTI) board. He is currently the coordinator of the Edge AI Technologies for Optimised Performance Embedded Processing (EdgeAI) project.