About this ebook
Edge AI has the potential to bring the computational power of AI algorithms closer to where data is generated, processed, and utilized. Traditionally, AI models are deployed in centralized cloud environments, leading to latency issues, bandwidth constraints, and privacy concerns. Edge AI addresses these limitations by enabling AI inference and decision-making directly on edge devices, such as smartphones, IoT sensors, and edge servers. Despite its challenges, edge AI presents numerous opportunities across various domains. From real-time health monitoring and predictive maintenance in industrial IoT to personalized recommendations in retail and immersive experiences in augmented reality, edge AI has the potential to revolutionize how we interact with technology. This book aims to provide a comprehensive exploration of edge AI, covering its foundational concepts, development frameworks, deployment strategies, security considerations, ethical implications, emerging trends, and real-world applications. This guide is essential for anyone pushing the boundaries to leverage edge computing for enhanced performance and efficiency.
Readers will find this volume:
- Dives deep into the world of edge AI with a comprehensive exploration covering foundational concepts, development frameworks, deployment strategies, security considerations, ethical implications, governance frameworks, optimization techniques, and real-world applications;
- Offers practical guidance on implementing edge AI solutions effectively in various domains, including architecture design, development frameworks, deployment strategies, and optimization techniques;
- Explores concrete examples of edge AI applications across diverse domains such as healthcare, industrial IoT, smart cities, and autonomous systems, providing insights into how edge AI is revolutionizing industries and everyday life;
- Provides insights into emerging trends and technologies in the field of edge AI, including convergence with blockchain, augmented reality, virtual reality, autonomous systems, personalized experiences, and cybersecurity.
Audience
Researchers, AI experts, and industry professionals in the field of computer science, IT, and business management.
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About the author
Preeti Agarwal, PhD is an assistant professor in the School of Technology Management and Engineering at the Narsee Monjee Institute of Management Studies with more than 13 years of experience. She has extensive publications in international journals and conferences. Her research focuses on optimizing edge-based frameworks for human activity recognition.
Anchit Bijalwan, PhD an Associate Professor in the School of Computing and Innovative Technologies at the British University Vietnam, Hanoi, Vietnam. He has authored two books and published more than fifty research papers in reputed international journals and conferences. His specialization is in privacy and security.
