152,89 €
Fog-Enabled Intelligent IoT Systems
Fog-Enabled Intelligent IoT Systems
  • Sold out
Fog-Enabled Intelligent IoT Systems
Fog-Enabled Intelligent IoT Systems
El. knyga:
152,89 €
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 lat…
0

Fog-Enabled Intelligent IoT Systems (e-book) (used book) | bookbook.eu

Reviews

Description

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
152,89 €
Log in and for this item
you will receive
1,53 Book Euros! ?

Electronic book:
Delivery after ordering is instant! Intended for reading only on a computer, tablet or other electronic device.

Lowest price in 30 days: 152,89 €

Lowest price recorded: Price has not changed


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

Reviews

  • No reviews
0 customers have rated this item.
5
0%
4
0%
3
0%
2
0%
1
0%
(will not be displayed)