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Embedded Artificial Intelligence : Real-Life Applications and Case Studies - Arpita Nath Boruah

Embedded Artificial Intelligence

Real-Life Applications and Case Studies

By: Arpita Nath Boruah (Editor), Mrinal Goswami (Editor), Manoj Kumar (Editor), Octavio Loyola-González (Editor)

Paperback | 22 June 2026 | Edition Number 1

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This book explores the role of embedded AI in revolutionizing industries such as healthcare, transportation, manufacturing, and retail. It begins by introducing the fundamentals of AI and embedded systems and specific challenges and opportunities. A key focus of this book is developing efficient and effective algorithms and models for embedded AI systems, as embedded systems have limited processing power, memory, and storage. It discusses a variety of techniques for optimizing algorithms and models for embedded systems, including hardware acceleration, model compression, and quantization.

Key features:

  • Explores security experiments in emerging postâ'CMOS technologies using AI, including side channel attackâ'resistant embedded systems
  • Discusses different hardware and software platforms available for developing embedded AI applications, as well as the various techniques used to design and implement these systems
  • Considers ethical and societal implications of embedded AI visâ'aâ'vis the need for responsible development and deployment of embedded AI systems
  • Focuses on applicationâ'based research and case studies to develop embedded AI systems for realâ'life applications
  • Examines highâ'end parallel systems to run complex AI algorithms and comprehensive functionality while maintaining portability and power efficiency

This reference book is for students, researchers, and professionals interested in embedded AI and relevant branches of computer science, electrical engineering, or artificial intelligence.

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