EDGE AI

"Edge AI" stands at the confluence of two of the most transformative technologies of our era: Artificial Intelligence (AI) and Edge Computing. As the digital world expands, generating vast amounts of data at its periphery, the need to process this data intelligently, swiftly, and securely at its source has become paramount. This book is meticulously crafted to serve as a comprehensive, contemporary, and practical guide for B.Tech and M.Tech students, as well as researchers and industry professionals, seeking to master the principles, techniques, and applications of Edge AI.

Key Features of this Book:

1. Comprehensive Coverage: Spanning ten logically structured chapters, the book covers the entire spectrum of Edge AI, from fundamentals and core technologies to advanced topics and future trends.
2. NEP 2020 and AICTE Aligned: The content and approach are harmonized with the latest educational guidelines, emphasizing skill development, interdisciplinary understanding, and practical application.

3. Globally Relevant: Incorporates topics and perspectives from leading international university curricula, making it suitable for a global audience of B.Tech and M.Tech students.
4. Latest Content and Technologies: Meticulously updated to include the most recent advancements in Edge AI hardware (NPUs, MCUs with AI), software frameworks (TensorFlow Lite, PyTorch Mobile, Edge Impulse), model optimization techniques, and MLOps practices.
5. Practical Focus: While grounded in theory, the book emphasizes practical implementation, with discussions on deployment strategies, real-world case studies, and tools used in the industry.
6. Clear and Accessible Language: Complex concepts are explained in a clear, concise, and student-friendly manner, aided by illustrative examples and diagrams (to be included in the actual book).
7. Focus on Optimization: Dedicated coverage of model compression and optimization techniques (quantization, pruning, knowledge distillation) critical for resource-constrained edge devices.
8. Security and Ethics Emphasis: In-depth exploration of security vulnerabilities, privacy-preserving techniques, and the ethical considerations paramount in Edge AI deployment.
9. Future-Oriented: Discusses emerging trends like TinyML, neuromorphic computing, and the impact of 5G/6G, preparing readers for the next wave of Edge AI innovations.
10. Holistic Learning: Encourages readers to understand not just the "what" and "how," but also the "why" and "what if," fostering critical thinking and problem-solving skills.
11. Balanced Perspective: Provides a balanced view of Edge AI's capabilities, challenges, benefits, and risks, fostering a responsible approach to its development and deployment.


I believe that "Edge AI" will empower its readers with the essential knowledge and insights to navigate and contribute meaningfully to the exciting and ever-evolving landscape of intelligent edge systems. It is my hope that this book will not only serve as an academic resource but also as a catalyst for innovation, inspiring the next generation of engineers and scientists to build a smarter, more efficient, and more equitable future powered by Edge AI.