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TinyML for Edge Intelligence in IoT and LPWAN Networks

Paperback Engels 2024 9780443222023
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Samenvatting

TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to the Internet of Things (IoT) and low-power wide area networks (LPWANs). It starts by providing the foundations of IoT/LPWANs, low-power embedded systems and hardware, the role of AI and machine learning in communication networks in general, and cloud/edge intelligence. It then presents the concepts, methods, algorithms, and tools of TinyML. Practical applications of TinyML are given from the healthcare and industrial sectors, providing practical guidance on the design of applications and the selection of appropriate technologies.

Specificaties

ISBN13:9780443222023
Taal:Engels
Bindwijze:Paperback

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Inhoudsopgave

1. TinyML for Ultra Low Power Internet of Things<br>2. Embedded Systems for Ultra Low Power Applications<br>3. Cloud and Edge Intelligence<br>4. TinyML: Principles and Algorithms<br>5. TinyML using Neural Networks for Resource Constraint Devices<br>6. Reinforcement Learning for LoRaWANs<br>7. Software Frameworks for TinyML<br>8. Extensive Energy Modeling for LoRaWANs<br>9. TinyML for 5G Networks<br>10. Non-Static TinyML for Ad hoc Networked Devices<br>11. Bayesian-Driven Optimizations of TinyML for Efficient Edge Intelligence in LPWAN Networks<br>12. 6TiSCH Adaptive Scheduling for Industrial Internet of Things<br>13. Securing TinyML in a Connected World<br>14. TinyML Applications and Use Cases for Healthcare<br>15. Machine Learning Techniques for Indoor Localization on Edge Devices<br>16. Embedded Intelligence in Internet of Things Scenarios: TinyML Meets eBPF<br>17. A Real-Time Price Recognition System using Lightweight Deep Neural Networks on Mobile Devices<br>18. TinyML Network Applications for Smart Cities<br>19. Emerging Application Use Cases and Future Directions

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        TinyML for Edge Intelligence in IoT and LPWAN Networks