Fog Data Analytics for IoT Applications : Next Generation Process Model with State of the Art Technologies / edited by Sudeep Tanwar.

Format:

Book

Contributor:

Tanwar, Sudeep, editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Studies in big data 2197-6503 ; 76.

Studies in Big Data, 2197-6503 ; 76

Language:

English

Subjects (All):

Computational intelligence.

Big data.

Application software.

Computational Intelligence.

Big Data.

Big Data/Analytics.

Information Systems Applications (incl. Internet).

Local Subjects:

Computational Intelligence.

Big Data.

Big Data/Analytics.

Information Systems Applications (incl. Internet).

Physical Description:

1 online resource (XV, 497 pages) : 209 illustrations, 172 illustrations in color.

Edition:

First edition 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Singapore : Springer Singapore : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-981-15-6044-6

9789811560446

Access Restriction:

Restricted for use by site license.