Digital Twin Technologies for Industrial Monitoring and Control Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 15 March 2026 | Viewed by 64
Special Issue Editor
Interests: additive manufacturing of conformal electronics; intelligent manufacturing technologies and systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Digital Twin (DT) technologies are revolutionizing industrial ecosystems by creating dynamic, real-time virtual replicas of physical systems, enabling unprecedented precision in monitoring, control, and decision-making. As industries embrace Industry 4.0 and smart manufacturing, DTs bridge the gap between physical and digital realms, potentially enhancing predictive maintenance, operations, and sustainable practices. This Special Issue seeks to explore the advancements, challenges, and applications associated with DT technologies tailored to industrial environments, fostering innovation in automation, efficiency, and resilience.
This Special Issue aims to collate interdisciplinary research that addresses the integration, scalability, and security of DT frameworks within industrial monitoring and control systems. It welcomes contributions that tackle technical hurdles—such as modeling and model fidelity, data synchronization, and computational demands—while highlighting synergies with emerging technologies such as AI, IoT, and edge computing. By curating both theoretical and practical insights, this Special Issue will serve as a roadmap for deploying DTs in complex industrial settings.
Topics of Interest
- Modeling and Fidelity: Developing high-accuracy virtual models of industrial monitoring and control systems that mirror physical behavior under varying conditions.
- Real-Time Data Integration: Ensuring seamless synchronization between physical and digital systems using IoT/IIoT.
- AI/ML Applications: Predictive maintenance, anomaly detection, and adaptive control using machine learning.
- Cybersecurity: Safeguarding DT architectures against evolving threats in interconnected systems.
- Edge/Cloud Computing: Optimizing computational workflows for latency-sensitive industrial operations.
- Interoperability: Standardizing data protocols and middleware for cross-platform DT ecosystems.
- Human-Machine Interaction: Improving interfaces for operator decision-making and system transparency.
- Sustainability: Leveraging DTs for energy efficiency and reduced environmental impact.
- Case Studies: Sector-specific implementations in manufacturing, energy, transportation, and smart cities.
Target Audience
Researchers, engineers, and industry practitioners in fields such as automation, computer science, mechanical engineering, and data analytics will benefit from this Special Issue. It encourages the submission of articles that present novel methodologies, empirical validations, or scalable solutions that aim to advance both academic discourse and industrial adoption.
We welcome original research, reviews, and visionary perspectives. Submissions should align with the theme and adhere to the journal’s guidelines. Join us in shaping the future of industrial innovation through the lens of Digital Twin technologies.
Prof. Dr. Jin Huang
Guest Editor
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. Electronics 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 2400 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
- industrial monitoring
- control systems
- predictive maintenance
- real-time data integration
- IoT/IIoT
- machine learning
- cybersecurity
- edge/cloud computing
- smart manufacturing
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