Architecting framework edge functional (7 résultats)

Etat : New.

Etat : New. 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 .

Hardcover. Etat : Brand New. 166 pages. 6.14x0.50x9.21 inches. In Stock.

Buch. Etat : Neu. Neuware - 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.…

Hardcover. Etat : new. Hardcover. 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 propertiesfunctionality, 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 systems ability to meet both functional and non-functional requirements in a verifiable mannerensuring 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. Architecting a Framework for Edge AI Functional and Non-functional Requirements explores performance, dependability, and trust in edge AI. Covering hardware, software, ethics, law, and KPIs, it offers a holistic framework for building reliable, transparent, and socially aligned edge intelligence systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Etat : new. Hardcover. 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 propertiesfunctionality, 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 systems ability to meet both functional and non-functional requirements in a verifiable mannerensuring 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. Architecting a Framework for Edge AI Functional and Non-functional Requirements explores performance, dependability, and trust in edge AI. Covering hardware, software, ethics, law, and KPIs, it offers a holistic framework for building reliable, transparent, and socially aligned edge intelligence systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Etat : new. Hardcover. 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 propertiesfunctionality, 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 systems ability to meet both functional and non-functional requirements in a verifiable mannerensuring 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. Architecting a Framework for Edge AI Functional and Non-functional Requirements explores performance, dependability, and trust in edge AI. Covering hardware, software, ethics, law, and KPIs, it offers a holistic framework for building reliable, transparent, and socially aligned edge intelligence systems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…