Charting the Intelligence Frontiers Edge AI Systems Nexus

Charting the Intelligence Frontiers Edge AI Systems Nexus

Communications and Networking

Charting the Intelligence Frontiers Edge AI Systems Nexus

Editors:
Ovidiu Vermesan, SINTEF, Norway
Alain Pagani, German Research Center for Artificial Intelligence, Germany
Paolo Meloni, University of Cagliari, Italy

ISBN: 9788743808848 (Hardback) e-ISBN: 9788743808831

Available: October 2025

doi: https://doi.org/10.13052/rp-9788743808831


This book is the result of the rich exchanges of ideas and presentations at the European Conference on EDGE AI Technologies and Applications (EEAI) held on 21-23 October 2024 in Cagliari, Sardinia, Italy, offering a panoramic snapshot and a technical deep dive into the contemporary landscape of edge AI. With twenty selected chapters, it encapsulates the convergence of fundamental concepts, technical advancements, and real-world deployments that define the edge AI continuum.

Collectively, the book serves as a reference for the field, capturing the current state-of-the-art and anticipating future trends in hyperautomation, generative AI, connectivity, autonomy, and security mesh architectures. Whether you are seeking in-depth technical knowledge, inspiration for novel applications, or a strategic overview of the edge AI landscape, you will find invaluable insights from thought researchers and practitioners at the forefront of the field of edge AI.

A brief overview of each of the twenty chapters is provided below, highlighting the research and applications of edge AI that underscore the book’s commitment to both technological and societal impact.

Edge AI Systems Verification and Validation: This chapter explores the challenges of verifying and validating complex edge AI systems, which integrate hardware, software, and data. It proposes a structured framework that combines model- and data-driven engineering to ensure these systems are reliable, robust, and meet regulatory standards.
Edge AI technologies, edge AI technology stack, micro-edge, deep-edge, and meta-edge, neuromorphic computing, artificial intelligence (AI), edge AI accelerators, deep learning (DL), machine learning (ML), federated learning (FL), Internet of Things (IoT), system-on-chip (SoC), autonomous systems, edge AI trustworthiness, AI explainability (XAI), AI interpretability (IAI).

Chapter 1: Edge AI Systems Verification and Validation
by Ovidiu Vermesan, Alain Pagani, Roy Bahr, Marcello Antonio Coppola, Giulio Urlini


38

Chapter 2: Pioneering the Hybridization of Federated Learning in Human Activity Recognition
by Alfonso Esposito, Yasamin Moghbelan, Ivan Zyrianoff, Leonardo Ciabattini, Federico Montori, Marco Di Felice


41

Chapter 3: Edge Intelligence Architecture for Distributed and Federated Learning Systems
by Pierluigi Dell’Acqua, Lorenzo Carnevale, Massimo Villari


37

Chapter 4: Challenges and Performance of SLAM Algorithms on Resource-constrained Devices
by Calvin Galagain, Martyna Poreba, François Goulette


281

Chapter 5: Designing Accelerated Edge AI Systems with Model Based Methodology
by Petri Solanti, Russell Klein


47

Chapter 6: Edge AI Acceleration for Critical Systems: from FPGA Hardware to CGRA Technology
by Pietro Nannipieri, Luca Zulberti, Tommaso Pacini, Matteo Monopoli, Tommaso Bocchi, Luca Fanucci


197

Chapter 7: Model Selection and Prompting Strategies in Resource Constrained Environments for LLM-based Robotic System
by Toms Eduards Zinars, Oskars Vismanis, Peteris Racinskis, Janis Arents, Modris Greitans


89

Chapter 8: Optimising ViT for Edge Deployment: Hybrid Token Reduction for Efficient Semantic Segmentation
by Mathilde Proust, Martyna Poreba, Calvin Galagain, Michal Szczepanski, Karim Haroun


38

Chapter 9: Recent Trends in Edge AI: Efficient Design, Training and Deployment of Machine Learning Models
by Mark Deutel, Maen Mallah, Julio Wissing, Stephan Scheele


121

Chapter 11: Multi-Step Object Re-Identification on Edge Devices: A Pipeline for Vehicle Re-Identification
by Tomass Zutis, Peteris Racinskis, Anzelika Bureka, Janis Judvaitis, Janis Arents, Modris Greitans


38

Chapter 12: A TinyMLOps Framework for Real-world Applications
by Mattia Antonini, Massimo Vecchio, Fabio Antonelli


69

Chapter 14: A Novel Hierarchical Approach to Perform On-device Energy Efficient Fault Classification
by Devesh Vashishth, Julio Wissing, Marco Wagner


43

Chapter 16: Conscious Agents Interaction Framework for Industrial Automation
by Polina Ovsiannikova, Valeriy Vyatkin


38

Chapter 17: Neuromorphic IoT Architecture for Efficient Water Management
by Mugdim Bublin, Heimo Hirner, Antoine-Martin Lanners, Radu Grosu


42

Chapter 18: Online AI Benchmarking on Remote Board Farms
by Maïck Huguenin, Baptiste Dupertuis, Robin Frund, Margaux Divernois, Nuria Pazos


66

Chapter 19: Optimising Neural Networks for Water Stress Prediction in Europe: A Sustainable Approach
by Laura Sanz-Martín, Manal Jammal, Javier Parra-Domínguez


37