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Fog-Enabled Intelligent IoT Systems. 2020 ed.
・ISBN 978-3-030-23184-2 hard EUR 129.99
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| 著者・編者 | Yang, Yang / Luo, Xiliang / Chu, Xiaoli / Zhou, Ming-Tuo, |
|---|---|
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2019 |
| ページ数 | 217 pp. |
| 言語 | ENG |
| ニュース番号 | <A03-38149> |
解説
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