Fog-Enabled Intelligent IoT Systems
- Indbinding:
- Hardback
- Sideantal:
- 217
- Udgivet:
- 28. oktober 2019
- Udgave:
- 12020
- Vægt:
- 524 g.
- 8-11 hverdage.
- 21. november 2024
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Fog-Enabled Intelligent IoT Systems
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
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
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