國立高雄大學圖資館 |

Language: English

Back

Fog data analytics for IoT applicati...

SpringerLink (Online service)

Fog data analytics for IoT applicationsnext generation process model with state of the art technologies /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fog data analytics for IoT applicationsedited by Sudeep Tanwar.
Reminder of title:	next generation process model with state of the art technologies /
other author:	Tanwar, Sudeep.
Published:	Singapore :Springer Singapore :2020.
Description:	xv, 497 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Internet of things.
Online resource:	https://doi.org/10.1007/978-981-15-6044-6
ISBN:	9789811560446$q(electronic bk.)

Fog data analytics for IoT applicationsnext generation process model with state of the art technologies /
Fog data analytics for IoT applicationsnext generation process model with state of the art technologies /[electronic resource] :edited by Sudeep Tanwar. - Singapore :Springer Singapore :2020. - xv, 497 p. :ill., digital ;24 cm. - Studies in big data,v.762197-6503 ;. - Studies in big data ;v.1..

Introduction -- Introduction to Fog data analytics for IoT applications -- Fog Data Analytics: Systematic Computational Classification and Procedural Paradigm -- Fog Computing: Building a Road to IoT with Fog Analytics -- Data Collection in Fog Data Analytics -- Mobile FOG Architecture Assisted Continuous Acquisition of Fetal ECG Data for Efficient Prediction -- Proposed Framework for Fog Computing to Improve Quality-of-Service in IoT applications -- Fog Data Based Statistical Analysis to Check Effects of Yajna and Mantra Science: Next Generation Health Practices -- Process Model for Fog Data Analytics for IoT Applications -- Medical Analytics Based on Artificial Neural Networks Using Cognitive Internet of Things.

This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA) This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDA in IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy.

ISBN: 9789811560446$q(electronic bk.)

Standard No.: 10.1007/978-981-15-6044-6doiSubjects--Topical Terms:

670954
Internet of things.

LC Class. No.: TK5105.8857 / .F64 2020

Dewey Class. No.: 004.678

Fog data analytics for IoT applicationsnext generation process model with state of the art technologies /
LDR:03004nmm a2200337 a 4500 001 585128
003 DE-He213
005 20200825094902.0
006 m d
007 cr nn 008maaau
008 210311s2020 si s 0 eng d
020 $a 9789811560446$q(electronic bk.)
020 $a 9789811560439$q(paper)
024 7 $a 10.1007/978-981-15-6044-6 $2 doi
035 $a 978-981-15-6044-6
040 $a GP $c GP
041 0 $a eng
050 4 $a TK5105.8857 $b .F64 2020
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 004.678 $2 23
090 $a TK5105.8857 $b .F655 2020
245 0 0 $a Fog data analytics for IoT applications $h [electronic resource] : $b next generation process model with state of the art technologies / $c edited by Sudeep Tanwar.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xv, 497 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6503 ; $v v.76
505 0 $a Introduction -- Introduction to Fog data analytics for IoT applications -- Fog Data Analytics: Systematic Computational Classification and Procedural Paradigm -- Fog Computing: Building a Road to IoT with Fog Analytics -- Data Collection in Fog Data Analytics -- Mobile FOG Architecture Assisted Continuous Acquisition of Fetal ECG Data for Efficient Prediction -- Proposed Framework for Fog Computing to Improve Quality-of-Service in IoT applications -- Fog Data Based Statistical Analysis to Check Effects of Yajna and Mantra Science: Next Generation Health Practices -- Process Model for Fog Data Analytics for IoT Applications -- Medical Analytics Based on Artificial Neural Networks Using Cognitive Internet of Things.
520 $a This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA) This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDA in IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy.
650 0 $a Internet of things. $3 670954
650 0 $a Big data. $3 609582
650 0 $a Cloud computing. $3 378527
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Big Data. $3 760530
650 2 4 $a Big Data/Analytics. $3 742047
650 2 4 $a Information Systems Applications (incl. Internet) $3 530743
700 1 $a Tanwar, Sudeep. $3 865638
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Studies in big data ; $v v.1. $3 675357
856 4 0 $u https://doi.org/10.1007/978-981-15-6044-6
950 $a Computer Science (SpringerNature-11645)