Buch, Englisch, 448 Seiten, Format (B × H): 156 mm x 234 mm
Reihe: River Publishers Series in Communications and Networking
Buch, Englisch, 448 Seiten, Format (B × H): 156 mm x 234 mm
Reihe: River Publishers Series in Communications and Networking
ISBN: 978-87-438-0884-8
Verlag: River Publishers
We are witnessing a fundamental shift in the computing landscape, a paradigm shift where intelligence is rapidly migrating to the very edges of the network. This is the era of edge AI, which embeds decision-making, perception, and control directly into devices that shape our physical world.
This book is a selected collection of the presented work from the European Conference on EDGE AI Technologies and Applications (EEAI) held on 21–23 October 2024 in Cagliari, Sardinia, Italy.
The conference is part of a series of annual conferences that delve into the expanding continuum of micro-, deep-, and meta-edge architectures, which form the backbone of emerging intelligent autonomous systems across numerous sectors. From the complexities of advanced algorithms and the design of novel edge AI hardware accelerators to the architecture of next-generation communication networks, AI frameworks and software systems, the EEAI fosters a vibrant exchange of ideas that are following the future and actively defining it.
From industrial automation to environmental monitoring, from manufacturing to smart mobility, the expansion of micro-, deep-, and meta-edge AI processing is propelling a new class of autonomous systems. These systems thrive on distributed intelligence, leveraging advancements in edge AI hardware architectures, accelerators, performant algorithms, and advanced software frameworks.
The chapters in this volume celebrate this paradigm shift and offer a glimpse into the vibrant ecosystem shaping the future of edge AI technologies and applications. The numerous chapters describe novel solutions and rigorous investigations spanning verification and validation, federated learning, neuromorphic design, scalable architectures, sensor fusion, and human–machine collaboration, each chapter demonstrating the innovation wave fuelling Europe's edge AI landscape.
Together, these twenty chapters provide a rich, multi-layered, and deeply insightful perspective on the state of edge AI. Each chapter documents the achievements made and highlights the path forward, offering a compelling vision of a future where intelligence is seamlessly and securely integrated into the fabric of the real world.
This book is an essential guide for navigating, understanding, and contributing to the dynamic and rapidly evolving field of edge AI.
The real value of this book lies in its innovative, forward-looking perspective, offering a guided exploration of the latest scientific breakthroughs and practical advancements shaping intelligent systems at the edge.
For researchers, students, practitioners, and visionaries, this book provides a comprehensive roadmap for the next stage in the evolution of intelligent, connected systems at the edge.
Zielgruppe
Academic, Postgraduate, and Professional Practice & Development
Autoren/Hrsg.
Weitere Infos & Material
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
