The internet of things and big data analytics integrated platforms and industry use cases /

This book comprehensively conveys the theoretical and practical aspects of IoT and big data analytics with the solid contributions from practitioners as well as academicians. This book examines and expounds the unique capabilities of the big data analytics platforms in capturing, cleansing and crunc...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Raj, Pethuru (Editor ), Poongodi, T. (Editor ), Balusamy, Balamurugan (Editor ), Khari, Manju (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton : Auerbach, 2020.
Temas:
Internet of things.
Big data.
Internet des objets.
Données volumineuses.
COMPUTERS / Networking / Intranets & Extranets
COMPUTERS / Data Transmission Systems / Wireless
Big data
Internet of things
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover
  • Half Title
  • Title Page
  • Copyright Page
  • Table of Contents
  • Preface
  • Author Biography
  • Contributors
  • 1 Taxonomy of Big Data and Analytics Solutions for Internet of Things
  • 1.1 Introduction
  • 1.1.1 IoT Emergence
  • 1.1.2 IoT Architecture
  • 1.1.2.1 Three Layers of IoT
  • 1.1.2.2 IoT Devices
  • 1.1.2.3 Cloud Server
  • 1.1.2.4 End User
  • 1.1.3 IoT Challenges
  • 1.1.4 IoT Opportunities
  • 1.1.4.1 IoT and the Cloud
  • 1.1.4.2 IoT and Security
  • 1.1.4.3 IoT at the Edge
  • 1.1.4.4 IoT and Integration
  • 1.1.5 IoT Applications
  • 1.1.5.1 Real-Time Applications of IoT
  • 1.1.6 Big Data and Analytics Solutions for IoT
  • 1.1.6.1 Big Data in IoT
  • 1.1.6.2 Big Data Challenges
  • 1.1.6.3 Different Patterns of Data
  • 1.7 Big Data Sources
  • 1.7.1 Media
  • 1.7.2 Business Data
  • 1.7.2.1 Customer's Details
  • 1.7.2.2 Transaction Details
  • 1.7.2.3 Interactions
  • 1.7.3 IoT Data
  • 1.8 Big Data System Components
  • 1.8.1 Data Acquisition (DAQ)
  • 1.8.2 Data Retention
  • 1.8.3 Data Transportation
  • 1.8.4 Data Processing
  • 1.8.5 Data Leverage
  • 1.9 Big Data Analytics Types
  • 1.9.1 Predictive Analytics
  • 1.9.1.1 What Will Happen If ...?
  • 1.9.2 Descriptive Analytics
  • 1.9.2.1 What Has Happened?
  • 1.9.3 Diagnostic Analytics
  • 1.9.3.1 Why Did It Happen?
  • 1.9.3.2 Real-Time Example
  • 1.9.4 Prescriptive Analytics
  • 1.9.4.1 What Should We Do about This?
  • 1.10 Big Data Analytics Tools
  • 1.10.1 Hadoop
  • 1.10.1.1 Features of Hadoop
  • 1.10.2 Apache Spark
  • 1.10.3 Apache Storm
  • 1.10.4 NoSQL Databases
  • 1.10.5 Cassandra
  • 1.10.6 RapidMiner
  • 1.11 Conclusion
  • References
  • 2 Big Data Preparation and Exploration
  • 2.1 Understanding Original Data Analysis
  • 2.2 Benefits of Big Data Pre-Processing
  • 2.3 Data Pre-Processing and Data Wrangling Techniques for IoT
  • 2.3.1 Data Pre-Processing
  • 2.3.2 Steps Involved in Data Pre-Processing
  • 2.3.3 Typical Use of Data Wrangling
  • 2.3.4 Data Wrangling versus ETL
  • 2.3.5 Data Wrangling versus Data Pre-Processing
  • 2.3.6 Major Challenges in Data Cleansing
  • 2.4 Challenges in Big Data Processing
  • 2.4.1 Data Analysis
  • 2.4.2 Countermeasures for Big-Data-Related Issues
  • 2.4.2.1 Increasing Collection Coverage
  • 2.4.2.2 Dimension Reduction and Processing Algorithms
  • 2.5 Opportunities of Big Data
  • 2.5.1 Big Data in Biomedical Image Processing
  • 2.5.2 Big Data Opportunity for Genome
  • References
  • 3 Emerging IoT-Big Data Platform Oriented Technologies
  • 3.1 Introduction
  • 3.2 Ubiquitous Wireless Communication
  • 3.2.1 Ubiquitous Computing
  • 3.2.1.1 Ubiquitous Architecture
  • 3.2.1.2 Communication Technologies
  • 3.2.1.3 Applications
  • 3.3 Real-Time Analytics: Overview
  • 3.3.1 Challenges in Real-Time Analytics
  • 3.3.2 Real-Time Analytics Platforms
  • 3.4 Cloud Computing
  • 3.4.1 Cloud Computing Era
  • 3.4.2 Relationship between IoT and Cloud

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