Book Title:  

Digital Twins for Digital Transformation and Innovation in Industry: applications and future perspectives  

Publication: Studies in Computational Intelligence by Springer                     https://www.springer.com/series/7092 

with h-index = 62 (Indexing to Web of Science, EI-Compendex, DBLP, SCOPUS, Google Scholar and Springerlink)  

Digital transformation initiatives through the smart and intelligent application of is leading to both tactical as well as strategical accomplishments across industry. Governments across the world are precisely and strategizing planning to have digital transformation as a beneficial measure for their citizens. Nowadays, there are a number of pioneering digital emerging technologies to speed up and streamline the activities to meet up digital transformation objectives. Digital twins is one of the widely digital intelligence technologies for the forthcoming era of people-centric services, mission-critical and knowledge-filled.  

With the faster stability and maturity of communication, information, sensing, perception and actuation technologies, digital twins paradigm is acquiring a lot of interest of researchers and scholars. Pioneering digital technologies such as digital twins, machine and deep learning, big data analytics, distributed and decentralized Internet of Things architectures, fog or edge data analytics and 5G communication, leads to a variety of digital transformation and innovation for the nations across the globe.  

The digital twins is the virtual representation of a physical system or object across its unique lifecycle. It uses real-time data from multiple sources to enable learning, reasoning, and contributing for extracting actionable insights. Therefore, digital twins facilitate data-driven insights and insights-driven decisions and actions. Digital twins can create a competent and assistive digital representation for all kinds of physical objects or systems such as vehicles, aircraft engines, satellites and launchers, drones and robots. In the future, there are recommendations to have digital twins for people and processes. 

This book aims to present dominant applications and use cases of the fast-evolving digital twins. Also, this book aims to determine vital Industry 4.0 technologies for building digital twins.  

Submitted manuscripts should conform to the standard guidelines of the Springer book chapter format. Manuscripts must be prepared using Latex, or MS Word. Prospective authors should submit their manuscripts electronically through email through this email: [aboitcairo@cu.edu.eg, ashraf.darwish.eg@ieee.org] Submitted manuscripts will be refereed by at least two independent and expert reviewers for quality, correctness, originality, and relevance before being accepted for publication. 

a. Submitted manuscripts should conform to the standard guidelines of the Springer book chapter format. Manuscripts must be prepared using Latex, or Word, and according to the Springer svmlt template that can be downloaded from the (link) and the Chapter should contain in between 20-25 pages. Manuscripts that do not follow the formatting rules will be ignored.  

b. There is no submission or publication fee 

c. Conference paper may be extended to be a chapter provided extension is more than 40% from the original conference paper 

d. Chapters not conforming to the above-mentioned guidelines shall not be considered for review purpose 

The accepted contributions will be published in Studies in Computational Intelligence by Springer. 

The readers are expected to gain know-how on state-of-the-art research challenges, results, architecture, applications, and other achievements in the following topics, but not limited to: 

The topics of this book are not limited to: 

1. Digital twins for the aerospace industry 
2. Digital twins for the intelligent Internet of Things era 
3. Digital twins for industrial applications 
4. Digital twins for the healthcare sector 
5. Digital twins for industrial enterprises 
6. Digital twins for smart cities 
7. Digital twins in manufacturing 
8. Digital twins in space industry 
9. Digital twins for smart transportation 
10. Digital twins for retail 
11. Digital twins for  clothing industry 
12. Challenges and potentials of digital twins and Industry 4.0 
13. Machine learning based digital twins for industrial applications 

The book publication schedule is as follows: 

Deadline for paper submission:     January 30, 2021 

First round notification                : February 15, 2021 

Camera-ready submission               : March 25, 2021 

Publication date                          : 3rd quarter of 2021 

All questions about submissions should be emailed to the Volume Editors as given below: 

• Aboul Ella Hassanien, Cairo Univesrity, Egypt  

E-mail: aboitcairo@cu.edu.eg 

• Ashraf Darwish, Helwan University, Cairo, Egypt 

Email: ashraf.darwish.eg@ieee.org