Edge AI Devices

"From Al Architectures and Algorithms to Deployment on Resource-Constrained Devices
Artificial Intelligence is transforming the way intelligent systems perceive, analyze, and interact with the physical world. As computation shifts from centralized cloud platforms to intelligent edge devices, the ability to execute Al models efficiently on resource-constrained hardware has become a defining capability across modern engineering applications.
AI EDGE DEVICES provides a comprehensive and practice-oriented introduction to the rapidly evolving field of Edge Al. The book bridges the gap between artificial intelligence, embedded systems, edge computing, and the Internet of Things (IoT), guiding readers from fundamental concepts to real-world deployment. It covers Al architecture, machine learning and deep learning algorithms, embedded hardware platforms, TinyML, model optimization, communication protocols, sensor integration, and deployment strategies for intelligent edge systems.
Designed as a textbook for undergraduate and postgraduate engineering students, the book also serves as a valuable reference for researchers, educators, and industry professionals. Richly supported with illustrations, practical examples, case studies, engineering insights, and hands-on discussions, it enables readers to develop efficient, scalable, and intelligent solutions for resource-constrained devices.
In an era where intelligence is increasingly moving closer to the source of data, this book equips readers with the knowledge and practical skills required to design, optimize, and deploy the next generation of Al-powered edge technologies."