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Full Description
This book provides an in-depth exploration of the integration of cloud and edge computing in artificial intelligence, addressing critical topics such as hybrid architectures, real-time data processing, security, and practical artificial intelligence applications.
Offers a detailed exploration of foundational concepts and practical applications of edge artificial intelligence, making it a comprehensive resource for understanding this emerging technology.
Featuring real-world case studies from various sectors such as smart cities, industrial applications, healthcare, and agriculture, it provides practical insights into how edge artificial intelligence is being applied.
Discusses the latest trends and future directions in edge artificial intelligence, including advancements in edge hardware and software, federated learning, and the potential impact of blockchain technology.
Addresses critical issues like security threats, privacy-preserving techniques, and the importance of explainable artificial intelligence.
Highlights case studies and real-world examples to illustrate the tangible benefits of edge artificial intelligence.
This book is primarily written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
Contents
Part 1: Foundations
Theme 1: Introduction - The Rise of Edge AI
Chapter 1: Edge AI: Transforming Computing from Cloud to Edge
Theme 2: Fundamentals of Edge Computing
Chapter 2: Edge Computing Fundamentals
Part 2: Applications
Theme 3: Smart Cities and Edge AI: Applications and Case Studies
Chapter 3: Smart Cities and Edge AI: Applications and Case Studies
Chapter 4: The Rise of Smart Cities: AI‑Driven Urban Evolution
Chapter 5: Edge AI in Smart Cities: A Conceptual Framework for Intelligent Urban Infrastructure
Theme 4: Industrial Applications of Edge AI: Transforming Manufacturing
Chapter 6: Innovating Industry 4.0: A Deep Dive into Technological Trends, Cyber‑Security Solutions, and Their Industrial Effects
Theme 5: Beyond Industry and Cities - Exploring Edge AI Applications in Diverse Fields
Chapter 7: Healthcare on the Edge: Innovations with Cloud and Edge Computing
Chapter 8: COVID‑19 Pandemic Prediction Model in India: Data Analysis and Forecasting
Chapter 9: Leveraging Machine Learning for Proactive Credit Card Fraud Detection
Chapter 10: Systematic Study of Machine Learning Algorithms for Botnet Detection
Chapter 11: Integrating DEA with Edge Computing for Evaluating Healthcare System Efficiency
Chapter 12: Big Data Sentiment Analysis of Twitter Data Using Hadoop & Python
Part 3: The Future and Its Applications with Case Studies
Theme 6: Emerging Trends in Cloud‑to‑Edge Computing for AI
Chapter 13: Deep Transfer Learning in Edge Computing: Enhancing Intelligence at the Network Edge
Chapter 14: A Unified Framework for Trustworthy and Explainable Edge AI (TE2AI): Enhancing Transparency, Security, and Reliability in Decentralized Intelligence
Theme 9: Security and Privacy Considerations in Edge AI
Chapter 15: Security and Privacy Considerations in Edge AI
Theme 10: The Road Ahead - The Impact of Edge AI on the Future of Computing
Chapter 16: Safeguarding the Edge: Critical Security and Privacy Considerations in Edge AI Deployments
