Cognitive Computing for Big Data Systems Over IoT: Frameworks, Tools and Applications

✍ Scribed by Arun Kumar Sangaiah,Arunkumar Thangavelu,Venkatesan Meenakshi Sundaram (eds.)

• Publisher: Springer International Publishing
• Year: 2018
• Tongue: English
• Leaves: 383
• Series: Lecture Notes on Data Engineering and Communications Technologies 14
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-xvi
Beyond Automation: The Cognitive IoT. Artificial Intelligence Brings Sense to the Internet of Things (Pijush Kanti Dutta Pramanik, Saurabh Pal, Prasenjit Choudhury)....Pages 1-37
Cybercrimes Investigation and Intrusion Detection in Internet of Things Based on Data Science Methods (Ezz El-Din Hemdan, D. H. Manjaiah)....Pages 39-62
Modelling and Analysis of Multi-objective Service Selection Scheme in IoT-Cloud Environment (Chinu Singla, Nitish Mahajan, Sakshi Kaushal, Amandeep Verma, Arun Kumar Sangaiah)....Pages 63-77
Cognitive Data Science Automatic Fraud Detection Solution, Based on Benford’S Law, Fuzzy Logic with Elements of Machine Learning (Goran Klepac)....Pages 79-95
Reliable Cross Layer Design for E-Health Applications—IoT Perspective (P. Sarwesh, N. Shekar V. Shet, K. Chandrasekaran)....Pages 97-113
Erasure Codes for Reliable Communication in Internet of Things (IoT) Embedded with Wireless Sensors (C. Pavan Kumar, R. Selvakumar)....Pages 115-137
Review: Security and Privacy Issues of Fog Computing for the Internet of Things (IoT) (Binara N. B. Ekanayake, Malka N. Halgamuge, Ali Syed)....Pages 139-174
A Review on Security and Privacy Challenges of Big Data (Manbir Singh, Malka N. Halgamuge, Gullu Ekici, Charitha S. Jayasekara)....Pages 175-200
Recent Trends in Deep Learning with Applications (K. Balaji, K. Lavanya)....Pages 201-222
High-Level Knowledge Representation and Reasoning in a Cognitive IoT/WoT Context (Gian Piero Zarri)....Pages 223-262
Applications of IoT in Healthcare (Prabha Susy Mathew, Anitha S. Pillai, Vasile Palade)....Pages 263-288
Security Stipulations on IoT Networks (Sumod Sundar, S. Sumathy)....Pages 289-306
A Hyper Heuristic Localization Based Cloned Node Detection Technique Using GSA Based Simulated Annealing in Sensor Networks (D Rajesh Kumar, A Shanmugam)....Pages 307-335
Review on Analysis of the Application Areas and Algorithms used in Data Wrangling in Big Data (Chiranjivi Bashya, Malka N. Halgamuge, Azeem Mohammad)....Pages 337-353
An Innovation Model for Smart Traffic Management System Using Internet of Things (IoT) (Amardeep Das, Prasant Dash, Brojo Kishore Mishra)....Pages 355-370
Back Matter ....Pages 371-375

✦ Subjects

Computational Intelligence