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Fog-Enabled Intelligent IoT Systems

-15% su kodu: ENG15
187,17 
Įprasta kaina: 220,20 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
187,17 
Įprasta kaina: 220,20 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 220.2000 InStock
Nemokamas pristatymas į paštomatus per 11-15 darbo dienų užsakymams nuo 20,00 

Knygos aprašymas

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

Informacija

Autorius: Yang Yang, Ming-Tuo Zhou, Xiaoli Chu, Xiliang Luo,
Leidėjas: Springer Nature Switzerland
Išleidimo metai: 2019
Knygos puslapių skaičius: 236
ISBN-10: 3030231844
ISBN-13: 9783030231842
Formatas: 241 x 160 x 19 mm. Knyga kietu viršeliu
Kalba: Anglų

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