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.
Table of Contents:
Chapter 1: Edge AI: Transforming Computing from Cloud to Edge
Chapter 2: Edge Computing Fundamentals
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
Chapter 6: Innovating Industry 4.0: A Deep Dive into Technological Trends, Cyber-Security Solutions, and Their Industrial Effects
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
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
Chapter 15: Security and Privacy Considerations in Edge AI
Chapter 16: Safeguarding the Edge: Critical Security and Privacy Considerations in Edge AI Deployments
About the Author :
Manju Khari serves as Professor in the School of Computer and Systems Sciences at Jawaharlal Nehru University in New Delhi, India. She contributed to information security, Software Security Testing, Computer Networks, the Internet of Things, Cyber Forensics, and Deep Learning. Before joining JNU, she worked with Netaji Subhas University of Technology, East Campus, under the auspices of the Government of NCT Delhi. Dr. Khari is a PhD holder in Computer Science and Engineering from the prestigious National Institute of Technology Patna. She also holds a master’s in information security from Guru Gobind Singh Indraprastha University in Delhi, India. Her prolific research portfolio includes over 100+ published papers in premier refereed National and International Journals and Conferences, including highly regarded publishers such as IEEE, ACM, Springer, Inderscience, and Elsevier. Dr. Khari has also co-authored two books published by NCERT and co-edited 10 edited books, further solidifying her status as a leading scholar in her field. Dr. Khari is serving as a reviewer/technical program committee member for various international conferences. Dr. Khari's reputation as a rigorous and meticulous scholar has earned her positions as Associate Editor/Guest Editor for Springer, Wiley, and Elsevier books and a reviewer for several leading international journals. Dr. Khari's expertise is not limited to academia, as she is also a highly valued member and research consultant of several noteworthy projects in collaboration with prominent institutions such as AIMS, the Department of Biotechnology (DBT), DST, and the CSIR-NPL under the Ministry of Consumer and Legal Affairs in India. These projects are invaluable to advancing research and development in her field, further underscoring her reputation as a trailblazer in Computer Science and Engineering.
Priya Gupta is presently working as an Associate Professor at the Atal Bihari Vajpayee School of Management and Entrepreneurship at Jawaharlal Nehru University (JNU), New Delhi, India. Specializing in business analytics, data visualization, and various programming languages, she has made 20 plus years significant contributions through her teaching and research. Dr. Gupta holds a Ph.D. from BIT Mesra, India, focusing on customer relationship management systems in banking, and has a strong educational background, including an M.Phil. in Computer Science, an MCA, a PGDITM (Gold Medalist). Her career includes roles in both academia and industry, starting as an Assistant Software Engineer at the Center for Railway Information System (CRIS), and later teaching at institutions like Maharaja Agrasen College, Vivekanand College, and Shaheed Sukhdev College of Business Studies before joining JNU. Dr. Gupta’s research covers a wide range of topics, including business analytics, compiler design, and AI applications in finance and healthcare. She has published extensively in reputable journals and authored several books. Her projects include empirical research on the National Education Policy 2020 and the Skill India Mission, and she has been involved in innovation projects funded by the University of Delhi. Her patents include a smart grid network for electricity supply in smart cities and an IoT-based electric vehicle charging system. Dr. Gupta has also chaired sessions and organized committees for numerous international conferences, reflecting her leadership in the academic community.
Chandan Pal Singh is distinguished educator, accomplished book editor, and internationally certified Global Citizenship Education (GCED) and Digital Citizenship trainer with over 18 years of international teaching experience in Computer Science and Information Technology across Kazakhstan, India, Indonesia, China, and Singapore. Renowned for his expertise in integrating educational technology, AI, and machine learning into teaching practices, Chandan has co-authored and edited numerous influential books and published over 50 research papers in leading international journals. As an active member of various educational societies and a certified trainer under APCEIU, UNESCO, Chandan is committed to advancing innovative instructional methods, fostering global citizenship, and promoting academic excellence.
