語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Fog-Enabled Intelligent IoT Systems
~
Zhou, Ming-Tuo.
Fog-Enabled Intelligent IoT Systems
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Fog-Enabled Intelligent IoT Systems/ by Yang Yang, Xiliang Luo, Xiaoli Chu, Ming-Tuo Zhou.
作者:
Yang, Yang.
其他作者:
Zhou, Ming-Tuo.
面頁冊數:
XVIII, 217 p. 72 illus., 58 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Information Systems Applications (incl. Internet). -
電子資源:
https://doi.org/10.1007/978-3-030-23185-9
ISBN:
9783030231859
Fog-Enabled Intelligent IoT Systems
Yang, Yang.
Fog-Enabled Intelligent IoT Systems
[electronic resource] /by Yang Yang, Xiliang Luo, Xiaoli Chu, Ming-Tuo Zhou. - 1st ed. 2020. - XVIII, 217 p. 72 illus., 58 illus. in color.online resource.
Introduction -- IoT technologies and applications -- Fog computing architecture and technologies -- Challenges and solutions for cross-domain applications -- Fog-enabled intelligent transportation system -- Fog-enabled smart home and user behavior recognition -- Fog-enabled industrial 4.0 -- Fog-enabled wireless network self-optimization -- Conclusion.
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, two fog-enabled frameworks with detailed technical approaches are proposed for realistic application scenarios with no or limited priori domain knowledge, i.e. physical laws, system statuses, operation principles and execution rules. Based on these fog-enabled frameworks, a series of data-driven self-learning applications in different industrial sectors and public services are investigated and discussed, such as Intelligent Transportation System, Smart Home, Industrial 4.0, Wireless Network Self-Optimization, and User Behavior Recognition. Finally, the advantages and future directions of fog-enabled intelligent IoT systems are summarized in terms of service flexibility, scalability, quality, maintainability, cost efficiency, as well as latency. 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.
ISBN: 9783030231859
Standard No.: 10.1007/978-3-030-23185-9doiSubjects--Topical Terms:
881699
Information Systems Applications (incl. Internet).
LC Class. No.: TK1-9971
Dewey Class. No.: 621.382
Fog-Enabled Intelligent IoT Systems
LDR
:03329nam a22003975i 4500
001
1018835
003
DE-He213
005
20200706165940.0
007
cr nn 008mamaa
008
210318s2020 gw | s |||| 0|eng d
020
$a
9783030231859
$9
978-3-030-23185-9
024
7
$a
10.1007/978-3-030-23185-9
$2
doi
035
$a
978-3-030-23185-9
050
4
$a
TK1-9971
072
7
$a
TJK
$2
bicssc
072
7
$a
TEC041000
$2
bisacsh
072
7
$a
TJK
$2
thema
082
0 4
$a
621.382
$2
23
100
1
$a
Yang, Yang.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1066835
245
1 0
$a
Fog-Enabled Intelligent IoT Systems
$h
[electronic resource] /
$c
by Yang Yang, Xiliang Luo, Xiaoli Chu, Ming-Tuo Zhou.
250
$a
1st ed. 2020.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2020.
300
$a
XVIII, 217 p. 72 illus., 58 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
Introduction -- IoT technologies and applications -- Fog computing architecture and technologies -- Challenges and solutions for cross-domain applications -- Fog-enabled intelligent transportation system -- Fog-enabled smart home and user behavior recognition -- Fog-enabled industrial 4.0 -- Fog-enabled wireless network self-optimization -- Conclusion.
520
$a
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, two fog-enabled frameworks with detailed technical approaches are proposed for realistic application scenarios with no or limited priori domain knowledge, i.e. physical laws, system statuses, operation principles and execution rules. Based on these fog-enabled frameworks, a series of data-driven self-learning applications in different industrial sectors and public services are investigated and discussed, such as Intelligent Transportation System, Smart Home, Industrial 4.0, Wireless Network Self-Optimization, and User Behavior Recognition. Finally, the advantages and future directions of fog-enabled intelligent IoT systems are summarized in terms of service flexibility, scalability, quality, maintainability, cost efficiency, as well as latency. 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.
650
2 4
$a
Information Systems Applications (incl. Internet).
$3
881699
650
2 4
$a
Signal, Image and Speech Processing.
$3
670837
650
1 4
$a
Communications Engineering, Networks.
$3
669809
650
0
$a
Application software.
$3
528147
650
0
$a
Speech processing systems.
$3
564428
650
0
$a
Image processing.
$3
557495
650
0
$a
Signal processing.
$3
561459
650
0
$a
Electrical engineering.
$3
596380
700
1
$a
Zhou, Ming-Tuo.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
970826
700
1
$a
Chu, Xiaoli.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1078816
700
1
$a
Luo, Xiliang.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1313930
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783030231842
776
0 8
$i
Printed edition:
$z
9783030231866
776
0 8
$i
Printed edition:
$z
9783030231873
856
4 0
$u
https://doi.org/10.1007/978-3-030-23185-9
912
$a
ZDB-2-ENG
912
$a
ZDB-2-SXE
950
$a
Engineering (SpringerNature-11647)
950
$a
Engineering (R0) (SpringerNature-43712)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入