Learning Techniques for the Internet of Things [E-Book] / edited by Praveen Kumar Donta, Abhishek Hazra, Lauri Lovén.
The book is structured into thirteen chapters; each comes with its own dedicated contributions and future research directions. Chapter 1 introduces IoT and the use of Edge computing, particularly cloud computing, and mobile edge computing. This chapter also mentions the use of edge computing in vari...
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Personal Name(s): | Donta, Praveen Kumar, editor |
Hazra, Abhishek, editor / Lovén, Lauri, editor | |
Edition: |
1st edition 2024. |
Imprint: |
Cham :
Springer,
2024
|
Physical Description: |
XXII, 322 pages 72 illustrations, 67 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9783031505140 |
DOI: |
10.1007/978-3-031-50514-0 |
Subject (LOC): |
- Chapter. 1. Edge Computing for IoT
- Chapter. 2. Federated Learning Systems: Mathematical modelling and Internet of Things
- Chapter. 3. Federated Learning for Internet of Things
- Chapter. 4. Machine Learning Techniques for Industrial Internet of Things
- Chapter. 5. Exploring IoT Communication Technologies and Data-Driven Solutions
- Chapter. 6. Towards Large-Scale IoT Deployments in Smart Cities: Requirements and Challenges
- Chapter. 7. Digital Twin and IoT for Smart City Monitoring
- Chapter. 8. Multiobjective and Constrained Reinforcement Learning for IoT
- Chapter. 9. Intelligence Inference on IoT Devices
- Chapter. 10. Applications of Deep Learning models in diverse streams of IoT
- Chapter. 11. Quantum Key Distribution in Internet of Things
- Chapter. 12. Quantum Internet of Things for Smart Healthcare
- Chapter. 13. Enhancing Security in Intelligent Transport Systems: A Blockchain-Based Approach for IoT Data Management
- Index.