Название: Fog-Enabled Intelligent IoT Systems
Автор: Yang Yang, Xiliang Luo
Издательство: Springer
Год: 2019 (2020 Edition)
Страниц: 230
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book first provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services. The authors give in-depth analyses of fog computing architecture and key technologies that fulfill the challenging requirements of enabling computing services anywhere along the cloud-to-thing continuum. Further, in order to make IoT systems more intelligent and more efficient, a fog-enabled service architecture is proposed to address the latency requirements, bandwidth limitations, and computing power issues in realistic cross-domain application scenarios with limited priori domain knowledge, i.e. physical laws, system statuses, operation principles and execution rules.

Based on this fog-enabled architecture, a series of data-driven self-learning applications in different industrial sectors and public services are investigated and discussed, such as robot SLAM and formation control, wireless network self-optimization, intelligent transportation system, smart home and user behavior recognition. Finally, the advantages and future directions of fog-enabled intelligent IoT systems are summarized.

- Provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services
- Presents a fog-enabled service architecture with detailed technical approaches for realistic cross-domain application scenarios with limited prior domain knowledge
- Outlines a series of data-driven self-learning applications (with new algorithms) in different industrial sectors and public services

Contents:
1. IoT Technologies and Applications
2. Fog Computing Architecture and Technologies
3. Analytical Framework for Multi-Task Multi-Helper Fog Networks
4. Fog-Enabled Multi-Robot System
5. Fog-Enabled Wireless Communication Networks
6. Fog-Enabled Intelligent Transportation System
7. Fog-Enabled Smart Home and User Behavior Recognition
8. Conclusions
9. Idex