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Book synopsis

AI Will Transform Embedded Systems. Quantum Computing Will Redefine Their Limits.
This definitive engineering guide reveals how to integrate Artificial Intelligence, Quantum Computing, and Real-Time RTOS architecture to build secure, deterministic, and certifiable mission-critical systems for aerospace, defense, automotive, robotics, and industrial automation.

As embedded systems evolve from deterministic controllers into intelligent, autonomous decision-making platforms, engineers face an unprecedented challenge: integrating AI and emerging quantum technologies without compromising real-time determinism, reliability, functional safety, or certification. This book provides the engineering roadmap to meet that challenge.

Practical AI-Driven Quantum Embedded Systems is a comprehensive, industry-focused guide for designing, developing, optimizing, securing, and validating next-generation embedded platforms for mission-critical applications. Written from a systems engineering perspective, it bridges the gap between theory and real-world implementation by combining AI, quantum computing concepts, and production-grade RTOS architecture using VxWorks as the primary reference platform.

Unlike books that discuss AI, RTOS, or quantum computing in isolation, this volume integrates all three disciplines into a unified engineering framework. Beginning with RTOS fundamentals and VxWorks kernel architecture, it progresses through embedded AI inference, quantum-inspired algorithms, hybrid AI-quantum architectures, multicore scheduling, deterministic execution, BSP development, memory optimization, interrupt handling, fault tolerance, cybersecurity, certification, testing, and deployment strategies.

The book also presents practical implementation patterns, performance optimization techniques, verification methodologies, and extensive case studies drawn from aerospace, defense, autonomous vehicles, radar systems, satellites, avionics, UAVs, C4ISR, electronic warfare, and industrial safety systems. Emerging topics-including neuromorphic computing, embedded large language models, digital twins, photonic computing, and multi-agent embedded intelligence..

Inside You'll Learn

• Real-Time RTOS architecture for AI-enabled mission-critical systems
• Deep understanding of VxWorks kernel internals and deterministic execution
• AI model deployment, optimization, and inference on resource-constrained embedded platforms
• Quantum computing fundamentals and practical quantum-inspired embedded algorithms
• Hybrid AI-Quantum-RTOS architectural patterns
• Scheduling, multicore resource management, WCET analysis, and latency optimization
• Memory architecture, BSP development, hardware accelerators, FPGA integration, and quantum co-processors
• Functional safety, cybersecurity, fault tolerance, redundancy, and resilience engineering
• Certification guidance covering DO-178C, DO-254, ISO 26262, IEC 61508, MIL-STD-882, and related standards
• Testing, verification, validation, deployment, migration, and lifecycle engineering best practices
• Real-world case studies and industry-proven design methodologies for production systems

Who Should Read This Book?

• Embedded Software Engineers
• RTOS and VxWorks Developers
• Aerospace and Defense Engineers
• Automotive ADAS and Autonomous Systems Engineers
• Safety-Critical Software Architects
• AI and Edge AI Developers
• FPGA and Hardware Design Engineers
• Systems Engineers and Technical Leads
• Graduate Students and Researchers in Embedded Systems and AI
• Engineering Managers leading advanced embedded technology programs

Build the intelligent real-time systems that tomorrow's mission-critical world will depend upon.

Book details

• Full title: PRACTICAL AI-DRIVEN QUANTUM EMBEDDED SYSTEMS
• Subtitle: : Real Time RTOS Architecture for Aerospace, Defense, Safety, and Mission-Critical Applications
• Author: AJAI KUMAR MEDHAVI
• Language: English
• Binding: Paperback
• Number of pages: 436
• EAN: 9798184667218
• ID: 53037365
• Publisher: Independently published
• Weight: 1006 g
• Dimensions: 280 × 216 × 22 mm
• Date of publishing: 28. June 2026

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