Nagarajan Ramalingam – författare

This book brings together a set of research contributions that demonstrate how network edge intelligence is transforming the real-time decision-making across multiple domains. The book covers advanced applications in smart cities, intelligent transportation, healthcare, agriculture, finance, and assistive technologies, highlighting the integration of machine learning, deep learning, IoT, and large language models into resource-constrained and latency-sensitive environments. The individual chapters address real-time challenges such as scalability, robustness, data heterogeneity, and ethical considerations, highlighting the solutions that enable faster analytics, enhanced accuracy and context-aware intelligence.This book also presented the research contributions on applied and deployable edge intelligence, including privacy-preserving forensics, explainable and trustworthy healthcare AI, wearable and embedded systems, and edge-optimized computer vision and NLP models. Intended for researchers, practitioners, and advanced students, this book serves as a comprehensive reference that bridges theoretical advancements with real-world implementations, offering valuable insights into the design of efficient, secure, and socially responsible edge-enabled systems.

This book brings together a set of research contributions that demonstrate how network edge intelligence is transforming the real-time decision-making across multiple domains. The book covers advanced applications in smart cities, intelligent transportation, healthcare, agriculture, finance, and assistive technologies, highlighting the integration of machine learning, deep learning, IoT, and large language models into resource-constrained and latency-sensitive environments. The individual chapters address real-time challenges such as scalability, robustness, data heterogeneity, and ethical considerations, highlighting the solutions that enable faster analytics, enhanced accuracy and context-aware intelligence.This book also presented the research contributions on applied and deployable edge intelligence, including privacy-preserving forensics, explainable and trustworthy healthcare AI, wearable and embedded systems, and edge-optimized computer vision and NLP models. Intended for researchers, practitioners, and advanced students, this book serves as a comprehensive reference that bridges theoretical advancements with real-world implementations, offering valuable insights into the design of efficient, secure, and socially responsible edge-enabled systems.

This book provides a comprehensive overview of edge computing technologies, architectures and applications designed for efficient and high-speed data processing within local areas. It explores key areas of edge computing such as device management, information security privacy, scalability, energy efficiency and the ways to create smarter networks through Artificial Intelligence and edge computing. With the compilation of various chapters, this book shows how edge computing is incorporated in practical applications within the Internet of Things (IoT), smart cities, healthcare, industrial automation, and future communication. Overall, this book will serve as a valuable resource for those interested in designing, building, and managing edge computing systems to discover new ways to enhance their services.