Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today’s modern world.

New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Big Data Analytics
Cloud Computing
Cyber Twins
Deep Learning
Digital Twins
Digital Worlds
Edge Computing
Edge Networks
Intelligent Data Analytics
Internet of Things
Knowledge Discovery

Reviews & Statements

“A digital twin is a digital representation of an intended or actual real-world physical product, system, or process (a physical twin) that serves as the effectively indistinguishable digital counterpart of it for practical purposes, such as simulation, integration, testing, monitoring, and maintenance. Since a digital twin can and does often exist before a physical entity, it can be used to improve different kinds of systems, from healthcare to space systems. Now and because of the availability of data, increased usage of sensors, processing ability, software, and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks, digital twin are more relevant and can be used in real-time and regularly synchronized with the corresponding physical system as well as system of systems.”

– Polinpapilinho Katina, University of South Carolina Upstate

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Editor/Author Biographies

Dr P.Karthikeyan obtained his the Bachelor of Engineering (B.E.,) in Computer Science and Engineering from Anna University, Chennai, and Tamil nadu, India in 2005 and received his Master of Engineering (M.E,) in Computer Science and Engineering from Anna University, Coimbatore India in 2009. He has completed Ph.D. degree in Anna University, Chennai in 2018. Skilled in developing projects and carrying out research in the area of Cloud computing and Data science with the programming skill in Java, Python, R and C. He published more than 20 International journals with good impact factor and presented more than 10 International conferences. He was the reviewer of Elsevier, Springer, Inderscience and reputed Scopus indexed journals. He is acting as editorial board members in EAI Endorsed Transactions on Energy Web, The International Arab Journal of Information Technology and Blue Eyes Intelligence Engineering and Sciences Publication journal.

Polinpapilinho F. Katina is an Assistant Professor in the Department of Informatics and Engineering Systems at the University of South Carolina Upstate (Spartanburg, South Carolina, USA). He has served in various capacities at the National Centers for System of Systems Engineering (Norfolk, Virginia, USA), Old Dominion University (Norfolk, Virginia, USA), Politecnico di Milano (Milan, Italy), and The University of Alabama in Huntsville (Huntsville, Alabama, USA). He holds B.S. in Engineering Technology, M.Eng. in Systems Engineering, and Ph.D. in Engineering Management and Systems Engineering (Old Dominion University, Norfolk, Virginia, USA). He received additional training at the Politecnico di Milano (Milan, Italy). Dr. Katina’s profile includes nearly 200 scholarly outputs of peer-reviewed journal articles, conference papers, book chapters, and technical reports. He has also co-authored six (6) books. He focuses on teaching and research in the areas of Complex System Governance, Critical Infrastructure Systems, Decision Making and Analysis, Emerging Technologies (e.g., IoT), Energy Systems (Smart Grids), Engineering Management, Infranomics, Manufacturing Systems, System of Systems, Systems Engineering, Systems Pathology, Systems Theory, and Systems Thinking. He has demonstrable experience leading large-scale research projects and has achieved many established research outcomes.

Dr. S. P. Anandaraj received B.E (CSE) degree from Madras University, Chennai in the year 2004, M.Tech (CSE) with Gold Medal from Dr. MGR Educational and Research Institute, University in the year 2007 (Distinction with Honor) and Ph.d in August 2014.He is presently working as Associate Professor CSE in Presidency University,Bangalore. He has 15+ Years of Teaching Experience. His areas of interest include Information security, Data Science, Machine Learning and Networks. He wrote two book chapters in IGI Global Publications USA. He filled the 4 patents for the growth of research. He has published 50+ papers in various national and International Journals, national and International Conferences. He serving as an Editorial members for reputed journals. He also attended many National Workshops/FDP/Seminars etc. He is a member of ISTE, CSI, Member of IACSIT and Member of IAENG.

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