Cognitive Computing for Big Data Systems Over IoT

Frameworks, Tools and Applications

  • Arun Kumar Sangaiah
  • Arunkumar Thangavelu
  • Venkatesan Meenakshi Sundaram

Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 14)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Pijush Kanti Dutta Pramanik, Saurabh Pal, Prasenjit Choudhury
    Pages 1-37
  3. Chinu Singla, Nitish Mahajan, Sakshi Kaushal, Amandeep Verma, Arun Kumar Sangaiah
    Pages 63-77
  4. P. Sarwesh, N. Shekar V. Shet, K. Chandrasekaran
    Pages 97-113
  5. Binara N. B. Ekanayake, Malka N. Halgamuge, Ali Syed
    Pages 139-174
  6. Manbir Singh, Malka N. Halgamuge, Gullu Ekici, Charitha S. Jayasekara
    Pages 175-200
  7. K. Balaji, K. Lavanya
    Pages 201-222
  8. Prabha Susy Mathew, Anitha S. Pillai, Vasile Palade
    Pages 263-288
  9. Sumod Sundar, S. Sumathy
    Pages 289-306
  10. Chiranjivi Bashya, Malka N. Halgamuge, Azeem Mohammad
    Pages 337-353
  11. Amardeep Das, Prasant Dash, Brojo Kishore Mishra
    Pages 355-370
  12. Back Matter
    Pages 371-375

About this book


This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT). It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge

The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective.

Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice.

This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches.


Cognitive Computing Big Data Analysis Internet of Things Data Analytics Data Technologies Cognitive Models

Editors and affiliations

  • Arun Kumar Sangaiah
    • 1
  • Arunkumar Thangavelu
    • 2
  • Venkatesan Meenakshi Sundaram
    • 3
  1. 1.School of Computing Science and EngineeringVIT UniversityVelloreIndia
  2. 2.School of Computing Science and EngineeringVIT UniversityVelloreIndia
  3. 3.Department of Computer Science and EngineeringNational Institute of Technology, SurathkalMangaloreIndia

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-70687-0
  • Online ISBN 978-3-319-70688-7
  • Series Print ISSN 2367-4512
  • Series Online ISSN 2367-4520
  • Buy this book on publisher's site
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