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.