IDETWIN 2027 Workshop

About

IDETWIN 2027 is an international workshop on Industrial Digital Twins and Emerging Technologies: Bridging the Physical and Digital Worlds, in conjunction with the 2027 IEEE Consumer Communications & Networking Conference (CCNC 2027), Las Vegas, NV, USA, 9-12 January 2027 . The workshop focuses on the growing convergence of Digital Twin technologies with industrial IoT, edge intelligence, networking, and secure communication systems.

Scope & Motivation

Digital Twins are reshaping the industrial landscape by creating dynamic, data-driven replicas of physical systems. When combined with IoT, Artificial Intelligence, edge computing, and secure communications, they enable real-time monitoring, simulation, and optimization of assets, improving efficiency, reducing downtime, and supporting smarter decision-making across manufacturing, energy, logistics, smart cities, autonomous mobility, and other industrial sectors.

The IDETWIN 2027 workshop aims to bring together researchers, practitioners, and industry experts to discuss novel architectures, applications, and enabling technologies for Industrial Digital Twins. It promotes interdisciplinary dialogue on 5G/6G connectivity, private industrial networks, network slicing, edge-to-cloud orchestration, secure communication protocols, low-latency middleware, trusted data sharing, decentralized AI, and resilient cyber-physical infrastructures.

Key Technical Topics

• Design, implementation, and evaluation of Industrial Digital Twins
• Digital Twin architectures for cyber-physical and production systems
• Integration of IoT, sensor networks, and sensor fusion in Digital Twin frameworks
• Communication and networking architectures for Industrial Digital Twins
• 5G/6G, private networks, and network slicing for DT-enabled industrial systems
• Time-sensitive networking, deterministic communication, and low-latency protocols
• MQTT, OPC UA, DDS, and middleware solutions for real-time DT data exchange
• Edge-to-cloud and cloud-continuum orchestration for DT and CPS applications
• Network-aware Digital Twins for monitoring, optimization, and resilience
• QoS/QoE, latency, reliability, and bandwidth management in DT ecosystems
• Secure and resilient communication infrastructures for industrial CPS
• Edge intelligence and real-time data analytics for DTs
• Cybersecurity, trust, and resilience in Digital Twin and CPS environments
• Blockchain and distributed ledgers for data integrity, certification, and traceability
• Federated learning, gossip learning, and decentralized AI for Digital Twins
• Edge AI and real-time analytics in industrial operations
• Predictive maintenance, fault diagnosis, and risk assessment
• DT-based process optimization in manufacturing and production lines
• DTs for smart factories, logistics, supply chains, and autonomous mobility
• DTs for AGVs, AMRs, and industrial robotic systems
• DTs in energy communities, smart grids, and smart energy systems
• DTs for smart cities, urban infrastructures, and mission-critical environments
• Human-in-the-loop, hybrid intelligence, and operator-aware Digital Twins
• Interoperability, standardization, and lifecycle management of DTs
• Real-world deployments, prototypes, and experimental testbeds

Organizers

• Dr. Carsten Ellwein (Institute for Control Engineering of Machine Tools and Manufacturing Units, University of Stuttgart, Germany)
  Research group leader at ISW. He studied Software Engineering and Management at Heilbronn University of Applied Sciences, joined ISW in 2016, became head of the Software and Engineering Methods research group in 2018, and received his Ph.D. in 2024. His research focuses on control architecture and data-driven engineering for cyber-physical production systems, with particular interest in Digital Twins, Cloud Manufacturing and Distributed Manufacturing.
  Email: name.surname@isw.uni-stuttgart.de
• Dr. Marco Savarese (University of Modena and Reggio Emilia, Italy)
  PhD student at the Department of Engineering "Enzo Ferrari". His research focuses on intelligent transportation systems, IoT-enabled mobility services, vehicular data integration, and optimization methods for sustainable mobility. He has contributed to research on fuel-refilling itinerary optimization, Digital Twin-based human-machine interfaces, and next-generation vehicular networking applications.
  Email: name.surname@unimore.it
• Dr. Antonio Solida (University of Modena and Reggio Emilia, Italy)
  Research fellow whose activity focuses on vehicular communications, cooperative intelligent transportation systems, and networking solutions for connected mobility. His recent work includes performance evaluation of decentralized congestion control in IEEE 802.11p networks and low-cost C-ITS stations based on open-source software platforms.
  Email: name.surname@unimore.it
• Dr. Marcello Pietri (University of Modena and Reggio Emilia, Italy)
  Researcher and professor for Advanced Programming and Python at the Department of Sciences and Methods for Engineering (DISMI). His research focuses on Digital Twins, IoT, edge computing and cyber-physical systems security, with applications to smart cities, Industry 5.0 and 5G/6G networks. He has contributed to international work on federated learning, industrial blockchain, distributed monitoring and edge-to-cloud architectures for scalable and resilient industrial and urban solutions.
  Email: name.surname@unimore.it

Technical Program Committee

• Prof. Andreas Wortmann, ISW - University of Stuttgart, Germany
• Prof. Marco Picone, University of Modena and Reggio Emilia, Italy
• Prof. Marco Mamei, University of Modena and Reggio Emilia, Italy
• Prof. Antonio Virdis, University of Pisa, Italy
• Prof. Carlo Giannelli, University of Ferrara, Italy
• Prof. Judith Michael, University of Regensburg, Germany
• Prof. Loek Cleophas, TU Eindhoven, Netherlands
• Prof. Alessio Bucaioni, Mälardalen University, Sweden
• Prof. Jennifer McArthur, Toronto Metropolitan University, Canada
• Prof. Cristian Martín Fernández, University of Málaga, Spain
• Prof. Cláudio Gomes, Aarhus University, Denmark

Important Dates

• Workshop Papers Due: 4 October 2026
• Acceptance Notification: 10 November 2026
• Final Camera Ready: 23 November 2026
• Workshop date: [to be defined], during CCNC 2027, 9-12 January 2027

Call for Papers

The IDETWIN 2027 workshop invites high-quality, original research contributions and application-oriented case studies that explore how Digital Twins integrate with IoT, AI, edge computing, and secure communication to deliver innovative and resilient industrial systems.

Topics of interest include but are not limited to:

• Design and implementation of industrial DTs
• IoT integration and sensor fusion in DT frameworks
• Edge intelligence and real-time data analytics for DTs
• Cybersecurity and data integrity in DT-based systems
• Blockchain and distributed ledgers for secure industrial operations
• Federated, gossip, and decentralized learning in DT ecosystems
• Predictive maintenance and fault diagnosis using DTs
• DTs in energy systems, smart grids, and energy communities
• DTs for autonomous mobility and industrial logistics (AGVs, AMRs, etc.)
• Supply chain optimization through DT-driven platforms
• Human-in-the-loop and hybrid intelligence approaches in industrial DTs
• Risk analysis and resilience modeling in smart manufacturing

Accepted and presented papers will be published in the IEEE CCNC 2027 Workshop Proceedings and included in IEEE Xplore. Selected high-quality papers presented at the workshop will be invited to submit extended versions to a forthcoming Special Issue on "Industrial Digital Twins and Emerging Technologies" in a top-tier journal, subject to additional peer review.

Accepted Papers

Accepted papers will be announced after the peer-review process.

1. To be announced, Accepted papers for IDETWIN 2027 will be listed here once the selection process is complete. (Industrial Digital Twins; IoT; AI; edge intelligence; secure communications)

All submitted papers will undergo peer review by the workshop's Program Committee.

Program Outline

The workshop is planned as a full-day workshop featuring 8-10 peer-reviewed paper presentations and 2 invited keynote talks.

Morning Program: Industrial Digital Twins, IoT & edge intelligence session

Afternoon Program: Networking, secure communications & resilient cyber-physical systems

Submission and Format

Submissions must follow the same formatting and submission guidelines as the main track of IEEE CCNC 2027:

• All submissions should be written in English with a maximum paper length of six (6) pages, IEEE 10pt format
• Accepted papers may include up to two (2) extra pages in the camera-ready version, with an over length page charge of USD100 per page
• All submitted papers will undergo peer review by the workshop's Program Committee
• Double-column IEEE format, 10pt font, US letter size. More information about the accepted format here. Download standard IEEE conference templates (LaTeX format) here
• Single-blind peer-review process
• Submission via the IEEE CCNC 2027 paper submission system. Call for workshop papers is available here. Link to the EDAS system for the paper submission will be made available once confirmed.

Accepted and presented papers will be published in the IEEE CCNC 2027 Workshop Proceedings and included in IEEE Xplore. Please consult the CCNC 2027 website for further submission details. Selected high-quality papers presented at the workshop will be invited to submit extended versions to a forthcoming Special Issue on "Industrial Digital Twins and Emerging Technologies", subject to additional peer review.

Registration

Registration information will follow the IEEE CCNC 2027 workshop registration rules. At least one author of each accepted paper must register for the conference and present the paper for inclusion in the workshop proceedings.

Contact & Website

For questions and correspondence, please write to the IDETWIN 2027 workshop organizers: name.surname [@-AT] unimore.it or name.surname [@-AT] isw.uni-stuttgart.de

Official workshop website: https://idetwin.dipi.unimore.it
Also visit: https://dipi.unimore.it