This book presents a comprehensive exploration of the functional and non-functional requirements that define edge AI systems, including technical, ethical, legal, and regulatory dimensions. It offers a holistic perspective that spans hardware, software, the AI technology stack, and the data pipelines supporting applications across the micro-, deep-, and meta-edge continuum.
Edge AI systems are evaluated through their key properties—functionality, performance, cost, dependability, and trustworthiness. The book closely interlinks these requirements with the concepts of system dependability and trust. Dependability is presented as the backbone of real-time edge AI performance, where services must be delivered reliably within strict timeframes. Trustworthiness is defined as the system’s ability to meet both functional and non-functional requirements in a verifiable manner—ensuring transparency, correctness, and alignment with human oversight.
The chapters emphasize how building trust in edge AI is not merely a technical task, but a collaborative process across technical, ethical, and legal/regulatory domains. Establishing trustworthiness requires the careful definition of requirements, measurement of key performance indicators (KPIs), continuous monitoring, transparent processes, and alignment with broader societal values.
Written for researchers, engineers, and students eager to understand the next frontier of edge intelligence, the book invites readers to engage with cutting-edge discussions on performance, accountability, and responsibility in AI at the edge. It is both an academic resource and a practical guide for those seeking to design, validate, and deploy edge AI systems that are not only high-performing but also dependable, trustworthy, and socially aligned.
Table of Contents:
1. Introduction and Background 2. Taxonomy and Terminology 3. Edge AI System Engineering 4. Edge AI Non-functional Requirements 5. Edge AI Functional Requirements 6. Legal Requirements for Design and Development of Edge AI Systems 7. Standards 8. Conclusion
About the Author :
Ovidiu Vermesan holds a Ph.D. 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.
Dr. Alain Pagani is Principal Researcher and deputy director of the Augmented Vision research department at the German Research Center for Artificial Intelligence (DFKI). His research interests include artificial intelligence, computer vision, image understanding, and extended reality. He is the coordinator of the Network of Excellence dAIEDGE about distributed AI at the edge, and the coordinator of the Horizon Europe project CORTEX2 about remote cooperation using extended reality. He is lecturer at the University of Kaiserslautern-Landau, and he has published over 100 articles in conferences and journals. His research finds applications in extended reality for tele cooperation (project CORTEX2), artificial intelligence and computer vision for human–robot cooperation (project FLUENTLY), and artificial intelligence and augmented reality for analysis of extremely large data (project ExtremeXP). Since 2023, he has been a Research Fellow at DFKI, which is a recognition for outstanding scientific achievements and special achievements in technology transfer.
