The Autonomous Edge – Intelligence Embedded in Industrial Applications
eBook - ePub

The Autonomous Edge – Intelligence Embedded in Industrial Applications

  1. 270 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

The Autonomous Edge – Intelligence Embedded in Industrial Applications

About this book

The Autonomous Edge – Intelligence Embedded in Industrial Applications explores the technological transformation taking place at the intersection of artificial intelligence, edge computing, autonomous systems, and industrial applications. Bringing together contributions from researchers and practitioners across multiple disciplines, the book presents a comprehensive perspective on how intelligence is increasingly moving from centralised cloud infrastructures directly into vehicles, robots, manufacturing systems, smart cities, critical infrastructures, and embedded devices.

The chapters examine how next-generation edge AI systems are being designed to operate under strict constraints involving latency, energy consumption, privacy, safety, reliability, and real-time responsiveness. The book covers a wide spectrum of technologies, including AI-defined vehicles, continual learning, lightweight neural networks, vision transformers, graph neural networks, digital twins, semantic mapping, multimodal perception, and distributed AI pipelines optimised for deployment on edge hardware.

A central theme throughout the book is the transition from isolated edge AI models toward integrated, adaptive, and autonomous edge intelligence architectures. The presented solutions combine advances in hardware acceleration, embedded edge AI optimisation, communication infrastructures, explainable edge AI, and real-time processing to enable practical deployment in demanding industrial environments. Applications range from autonomous systems, mobility and smart manufacturing to cybersecurity, environmental monitoring, urban safety, and hydrogen infrastructure management.

The book addresses broader challenges associated with autonomous systems, including transparency, liability, ethical decision-making, robustness, and trustworthiness. By combining theoretical foundations with implementation experiences and experimental validations, the chapters provide both scientific insight and practical guidance for researchers, engineers, architects, and decision-makers working on the next generation of intelligent industrial systems at the edge.

Positioned at the convergence of edge AI, autonomous systems, and industrial digitalisation, the book offers a forward-looking view of how distributed intelligence is reshaping the physical world and enabling a new generation of adaptive, efficient, and edge autonomous industrial applications.

Information

Year
2026
Print ISBN
9788743815259
Edition
1
eBook ISBN
9788743815303

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication Page
  7. Acknowledgement
  8. Table of Contents
  9. Preface
  10. List of Figures
  11. List of Tables
  12. List of Contributors
  13. List of Abbreviations
  14. 1 The AI-Defined Vehicle: Navigating the Convergence of AI and Autonomous Systems
  15. 2 From Complexity to Efficiency: Pruning Vision Transformers in Practice
  16. 3 GStreamer Plugin for RDMA Offload on BlueField-3 for Edge Applications
  17. 4 On-Device Continual Learning for Unsupervised Visual Anomaly Detection in Dynamic Manufacturing
  18. 5 In-GPU GNN-based Intrusion Detection System
  19. 6 Vision-language Embeddings in Large Scale LiDAR SLAM for Terrain Segmentation
  20. 7 Investigating Target Class Influence on Neural Network Compressibility for Energy-Autonomous Avian Monitoring
  21. 8 When a model is not Enough: A Complementary AI Pipeline for Ultra-Safe PCBA Defect Detection
  22. 9 Towards Automated Liability Determination for Autonomous Vehicles in Road Accidents
  23. 10 Edge-Optimized Modular Architecture for Real-Time Vehicle Re-Identification
  24. 11 Edge Deployment of Multi-Task Vision Models for Smart City Infrastructures
  25. 12 Experiences in Deploying a Weapon Detector in a Smart City
  26. 13 A 3D Simulation Framework for Behavior Cloning on Edge AI-Enabled E-Scooters in Smart Cities
  27. 14 Edge-AI Ready Lightweight Digital Twin for Anomaly Prediction: A Case Study on Hydrogen Refueling Station Data
  28. Index
  29. About the Editors

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Yes, you can access The Autonomous Edge – Intelligence Embedded in Industrial Applications by Ovidiu Vermesan,Fetze Pijlman in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over 1.5 million books available in our catalogue for you to explore.