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Networks in Motion: Electric Vehicle Intelligence
Networks in Motion: Electric Vehicle Intelligence
Knygos.lt klubas Knygos.lt nariams
321,46 €
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Įprastai
378,19 €
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This book presents a 'Network of Networks' analogy to conceptualise autonomous electric vehicle (AEV) systems, integrating wireless sensor networks (WSNs), autonomous driving systems, cybersecurity, machine learning architectures, and urban systems as interdependent components within a cohesive model. It formulates a system-level architecture that captures the interactions across these domains, reflecting the operational realities of AEVs within complex, connected environments. Drawing on compl…

Networks in Motion: Electric Vehicle Intelligence (el. knyga) (skaityta knyga) | knygos.lt

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This book presents a 'Network of Networks' analogy to conceptualise autonomous electric vehicle (AEV) systems, integrating wireless sensor networks (WSNs), autonomous driving systems, cybersecurity, machine learning architectures, and urban systems as interdependent components within a cohesive model. It formulates a system-level architecture that captures the interactions across these domains, reflecting the operational realities of AEVs within complex, connected environments. Drawing on complex systems theory, it conceptualises the AEV-WSN relationship as a coupled system, situates urban environments as adaptive systems, and examines key architectural considerations and trade-offs in the design of reliable autonomous mobility platforms. It further introduces the e-drive stack as an architectural extension of conventional autonomous driving frameworks, embedding cybersecurity, energy efficiency, and privacy as primary design parameters. This book is intended for researchers in transportation systems, urban studies, computer science, electrical and electronic engineering, and artificial intelligence.

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This book presents a 'Network of Networks' analogy to conceptualise autonomous electric vehicle (AEV) systems, integrating wireless sensor networks (WSNs), autonomous driving systems, cybersecurity, machine learning architectures, and urban systems as interdependent components within a cohesive model. It formulates a system-level architecture that captures the interactions across these domains, reflecting the operational realities of AEVs within complex, connected environments. Drawing on complex systems theory, it conceptualises the AEV-WSN relationship as a coupled system, situates urban environments as adaptive systems, and examines key architectural considerations and trade-offs in the design of reliable autonomous mobility platforms. It further introduces the e-drive stack as an architectural extension of conventional autonomous driving frameworks, embedding cybersecurity, energy efficiency, and privacy as primary design parameters. This book is intended for researchers in transportation systems, urban studies, computer science, electrical and electronic engineering, and artificial intelligence.

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