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Futuristic Trends in Sensing Technologies of Digital Twin Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 806

Special Issue Editors

Department of Computer Science, Delhi-NCR Campus, KIET Group of Institutions, Ghaziabad 201206, India
Interests: Internet of Things (IoT); WSNs; data science technologies; multimedia systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Digital twins are intricate digital replicas of real-world systems that are connected to their corresponding real-world counterparts by sensors and other Internet of Things (IoT) gadgets. It is one of most demanding areas of research, especially in the area of Industry 4.0. The transformation from Industry 4.0 to 5.0 makes it more popular among researchers.

This Special Issue primarily aims to invite researchers from different domains of network and communication technologies at a single platform to submit their research ideas.

This Special Issue will cover the novel ideas from network technologies, algorithms, surveys, communication challenges, and future research aspects. The extended papers with 80% new content from the fifth version of Futuristic Trends in Computing and Communication (FTNCT) may also be considered for submission in this Special Issue. The extended research papers have to pass through a blind peer review by at least two reviewers, as per the MDPI Guidelines.

Original unpublished articles on the following topics are invited for submission:

  • Digital twin sensors;
  • Digital twin in Industry 4.0/5.0;
  • Smart grids, smart cities, IoT systems, and digital twins;
  • Digital twins for network and computing technologies;
  • Internet of Things (IoT) and fog-computing-enabled digital twin systems for sustainable industries and cities;
  • Futuristic digital twin technologies for digital healthcare and precision agriculture;
  • Security and privacy issues in digital-twin-enabled systems.

Prof. Dr. Pradeep Kumar Singh
Prof. Dr. Wei-Chiang Hong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital twin sensors
  • Industry 4.0/ 5.0
  • smart grids
  • smart cities
  • Internet of Things (IoT)

Published Papers (1 paper)

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Review

23 pages, 2016 KiB  
Review
Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis
Sensors 2024, 24(4), 1202; https://doi.org/10.3390/s24041202 - 12 Feb 2024
Viewed by 438
Abstract
Digital twin technology has become increasingly popular and has revolutionized data integration and system modeling across various industries, such as manufacturing, energy, and healthcare. This study aims to explore the evolving research landscape of digital twins using Keyword Co-occurrence Network (KCN) analysis. We [...] Read more.
Digital twin technology has become increasingly popular and has revolutionized data integration and system modeling across various industries, such as manufacturing, energy, and healthcare. This study aims to explore the evolving research landscape of digital twins using Keyword Co-occurrence Network (KCN) analysis. We analyze metadata from 9639 peer-reviewed articles published between 2000 and 2023. The results unfold in two parts. The first part examines trends and keyword interconnection over time, and the second part maps sensing technology keywords to six application areas. This study reveals that research on digital twins is rapidly diversifying, with focused themes such as predictive and decision-making functions. Additionally, there is an emphasis on real-time data and point cloud technologies. The advent of federated learning and edge computing also highlights a shift toward distributed computation, prioritizing data privacy. This study confirms that digital twins have evolved into complex systems that can conduct predictive operations through advanced sensing technologies. The discussion also identifies challenges in sensor selection and empirical knowledge integration. Full article
(This article belongs to the Special Issue Futuristic Trends in Sensing Technologies of Digital Twin Systems)
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