Digital Twin Consortium Adds Eight New Testbeds

BOSTON, MA, Sept. 16, 2025 (GLOBE NEWSWIRE) -- Today, the Digital Twin Consortium® (DTC) announced it added eight new testbeds to its Digital Twin Testbed Program, bringing the total to 16. Members can model, simulate, integrate, verify, deploy, and optimize digital twin solutions by providing unprecedented access to early-stage testbed development.

“We’re excited to announce these innovative digital twin testbeds,” said Dan Isaacs, GM & CTO of the DTC. “We’re seeing strong interest from members worldwide in participating in our collaborative testbed program. Our members already utilize this program to develop and adopt AI-powered intelligent digital twins, generative AI digital twins, and other enabling technologies, advancing the core technologies that drive tomorrow's digital transformation.”

DTC’s eight new member-led testbeds include: 

• TWINSENSE: AI-based Virtual Sensing for Enhanced Real-time Understanding and Learning Systems Enhancement - shows how digital twin technology can perform real-time virtual measurements of critical variables across diverse industrial assets. It addresses the challenge of measuring inaccessible or costly-to-monitor variables, leveraging digital twins for continuous virtual sensing. The testbed also calibrates AI-based novelty detection systems using transfer learning techniques that combine virtual and real-world data, enabling AI-driven proactive maintenance and improving maintenance accuracy by 40%.  Lead Developer: Aingura IIoT,  Co-Developer: XMPro.
• AEGIS: Agent-Empowered Guidance for Improving Student Outcomes  - The testbed shows that multi-agent systems, trained on survey data from high-risk students, can identify cognitive-emotional triggers that impact learning efficacy. The testbed simulates intervention scenarios and demonstrates how students can be trained to respond more effectively to these triggers, leading to improved engagement and reduced dropout rates. It validates AI-powered interventions for personalized learning and dropout prevention in education.  Lead Developer: My Performance Learning, Co-Developer: Crysp. 
• FAB - Factory-in-a-Box for Rapid Disaster Manufacturing - The testbed is a mobile, modular digital twin-enabled manufacturing unit that can produce critical energy components in disaster-struck zones. It reduces transport costs and logistics burden, minimizes downtime of essential systems and infrastructure, and provides localized, resilient production with minimal setup. It also enables remote coordination through a digital twin interface. Field-deployable, these production systems improve community resilience and demonstrate the feasibility of digital twin-enabled micro-manufacturing in high-stress scenarios. Lead Developers: DRG Solutions and Oak Ridge High School,  Contributing Technology Providers: Oak Ridge National Laboratory.
• Q-Smart: Quantum Secure Data Exchange for Resilient Smart Home Cognitive Networks - The Q-Smart testbed validates a cognitive, secure, self-learning platform-independent intelligent home system built on decentralized open-source components. It creates a personal cognitive hub using wireless mesh networks, dynamic live 3D models (digital twins), multi-agentic AI frameworks, and XR interfaces for energy optimization and indoor air quality management. The system emphasizes edge-native processing, ensuring all data remains within the home while leveraging quantum-safe (PQC-ready) protocols for future-proof security. By focusing on self-learning algorithms, it predicts and controls home aspects like HVAC and ventilation, reducing energy consumption by up to 25% and enhancing occupant comfort. Lead Developer: WINNIO.
• TRANSFORM - The TRANSFORM testbed is an application framework that systematically converts static 2D data schemas into dynamic 4D geospatial representations with real-time updates. The testbed uses digital twins to create dynamic live 3D models of homes, which serve as virtual representations of the physical environment. The digital twins are integrated with wireless mesh networks, sensors, and self-learning AI frameworks to monitor and predict home conditions. They enable seamless human-system AI interactions through XR interfaces, allowing for intuitive control and feedback for energy optimization and indoor air quality management. The testbed can be used for various applications, such as smart city infrastructure, transportation, utilities, and emergency services. Lead Developer: EDX Technologies, Co-Developer: Crysp.
• SAFESME: Smart Asset Fast Enablement for SME Equipment—The testbed demonstrates digital twin–driven commissioning and digital service enablement for SME manufacturing equipment, specifically injection molding machines and packaging machines. It validates that SME-scale manufacturing equipment can achieve cost-effective digital twin onboarding and digital service transformation. The testbed enables rapid, automated onboarding and commissioning in under 5 minutes per asset, reduces setup time and operator effort, and maintains high model alignment and API performance, all without requiring expensive PLC upgrades or high development overhead.   Lead Developer: HS Soft.
• Early Notification & Guidance for Academic Growth & Engagement (ENGAGE) – The testbed is focused on determining whether a digital twin can be used to identify and support at-risk students. The testbed will create a comprehensive digital twin system that integrates academic scores, class participation, extracurricular involvement, behavioral indicators, and sentiment analysis to surface previously unmeasured emotional and engagement signals critical for student retention but currently invisible in traditional monitoring systems. Lead Developer: Austin Community College District.
• Synthetic Healthcare Pathway Digital Twin (SYNTHEKID) – The testbed transforms regional healthcare delivery through an innovative synthetic digital twin that models chronic kidney disease (CKD) pathways across Yorkshire, UK. It validates how privacy-preserving digital twins can optimize healthcare systems, enabling scenario planning and demand forecasting without compromising patient confidentiality. The platform validates critical intervention points that can improve outcomes and system efficiency by simulating patient journeys from early detection to clinical progression. Lead Developer: Health Innovation Network Yorkshire and Humber; Co-Developers: Nexus, Counterpoint Technologies,  Crysp. 

The Digital Twin Testbed Program implements DTC's Composability Framework—utilizing the Business Maturity Model, Platform Stack Architecture, and Capabilities Periodic Table—alongside a capabilities-focused maturity assessment framework that incorporates the evaluation of Generative AI, multi-agent systems, and other advanced technologies.

Learn more about the DTC Digital Twin Testbed Program. Become a DTC member and join the global leaders in driving digital twin evolution and enabling technology.

About the Digital Twin Consortium
Digital Twin Consortium® (DTC) is Accelerating Digital Twin Innovation™.  DTC executes the promise of digital twins and associated technologies by working closely with our members to accelerate the market. We do this by fostering development, raising awareness, increasing adoption, and improving the interoperability of digital engineering projects propelled by digital twins across many industries.  DTC is a program of Object Management Group®. For more information, visit https://www.digitaltwinconsortium.org.

Note to editors: Digital Twin Consortium is a registered trademark of OMG. See the listing of all OMG trademarks. All other trademarks are the property of their respective owners.

Digital Twin Testbed Program Quote Sheet

• TRANSFORM Testbed - "With the TRANSFORM testbed, we demonstrate digital twin technology for validating an application framework architected for ongoing, real-time conversion of diverse 2D data schemas into dynamic 4D geospatial representations of up to global reach.  We directly address the challenge of standardized data interoperability by demonstrating a framework for seamless data transformation across diverse application spaces.  The approach enables systematic validation of conversion accuracy, multisource data aggregation, and streaming content integration across thousands of data sources.  This innovation has the potential for rapid prototyping and construction of 4D digital twins of any scale,” said Dr. Roger Skidmore, EDX Technologies, Inc.
• Early Notification & Guidance for Academic Growth & Engagement (ENGAGE)Testbed - "This collaboration positions ACC at the forefront of innovation, connecting education with real-world applications in one of the most transformative technologies of our time.  Together with the Digital Twin Consortium and Object Management Group, Inc., we are building pathways for the future that ensure students, businesses, and communities thrive in a rapidly changing world," said Dr. Lowery-Hart, Austin Community College Chancellor.
• Synthetic Healthcare Pathway Digital Twin (SYNTHEKID)Testbed -

• • Amy Lochtie, Director, West Yorkshire Innovation Hub, said, “This testbed is the UK’s first health-innovation-accelerator digital twin consortium testbed, turning privacy-safe digital twins into faster CKD solutions. We look forward to working with leading clinicians and our partners within the NHS, Nexus Leeds, and Crysp.”
  • Dr. David McKee, Crysp CTO, said, “FOAK for the UK: This project shows digital twins can rewire CKD pathways at system scale—Nexus and Crysp help turn insight into action, radically improving outcomes and cutting costs.”
  • Nathan Berry, Head of Collaboration Nexus, “The testbed is a unique way of working between Nexus, Health Innovation Yorkshire and Humber, and the West Yorkshire Integrated Care Board – as well as Crysp as an industry partner -  to deliver a UK first, impactful solution that will benefit patients and the NHS. We are excited to work in this partnership as the testbed develops.”

• FAB (Factory-in-a-Box for Rapid Disaster Manufacturing) Testbed - "Our testbed demonstrates how digital twins and additive manufacturing can deliver critical energy components in off-grid and resource-constrained environments. The FAB testbed validates performance and reliability before deployment by integrating high-fidelity simulation, real-time data exchange, and standards-based interoperability. We’re proud to be part of the Digital Twin Consortium. FAB shows that multi-stakeholder collaboration can keep mission-critical energy systems reliable, flexible, and ready in the toughest conditions,” said Mike Marshall, Vice President, DRG Tech Solutions.
• TWINSENSE: AI-based Virtual Sensing for Enhanced Real-time Understanding and Learning Systems Enhancements Testbed - "Digital twin–enabled virtual sensing opens the door to creating richer and more valuable features that enhance AI algorithms for asset maintenance. By leveraging these virtual measurements, we improve predictive accuracy and enable proactive maintenance strategies, as algorithms continually refine their performance with this new information. A core focus of the testbed is validating transfer learning frameworks that align virtual and real-world data, setting new standards for accuracy and scalability in industrial environments. In collaboration with XMPro, Aingura IIoT is proud to lead this testbed within the Digital Twin Consortium, and we look forward to welcoming more member companies to test and explore this wide range of opportunities. Our efforts will be validated across diverse industrial scenarios, including water pumps, gearboxes, turbines, generators, air compressors, conveyor belts, and beyond, demonstrating the broad impact of AI-based virtual sensing on real-world operations," said Dr. Javier Diaz-Rozo, CTO, Aingura IIoT.
• AEGIS: Agent-Empowered Guidance for Improving Student Outcomes - "Our testbed demonstrates how Agentic AI can transform education systems worldwide by offering personalized, real-time feedback that empowers learners and educators alike. Having already impacted over 75,000 students, we combine behavioral science with intelligent automation to tackle global attainment, engagement, and equity challenges. This innovation can reshape how the world learns, unlocking opportunity, improving outcomes, and making high-impact education accessible to all,” said Dr. Tej Samani, CEO, Performance Learning Technologies.
• Q-Smart: Quantum Secure Data Exchange for Resilient Smart Home Cognitive Networks - “Q-SMART turns every home into an edge native, quantum-secure, self-learning organism—where energy, comfort, and security evolve together at the speed of intelligence.” With algorithms trained and developed in smart building conditions for 10,000s of hours, we combine cutting-edge technology with explainable AI to make buildings aware of what they need to be aware of. This innovation makes it possible for true resiliency at scale, where data stays local, and secure, anonymized insights go global. This is made for a world where humans are in control and AI is in the loop,” said Nicholas Waern, CEO & Founder at Winniio.

Karen QuatromoniDigital Twin [email protected]