Digital Twin Consortium adds 8 new testbeds

summary

Boston, September 16, 2025 – The Digital Twin Consortium (DTC) has announced that it has added eight new testbeds to its Digital Twin Testbed program, bringing its total to 16.

“We look forward to unveiling these innovative digital twin testbeds,” said Dan Isaacs, GM and CTO at DTC. “We have a strong interest from members around the world in participating in our joint testing program. Members are already using this program to develop and adopt intelligent digital twins with AI, generative AI digital twins, and other enablement technologies, moving forward with the core technologies that drive tomorrow’s digital transformation.”

DTC’s eight new member-driven testbeds include:

Twinsense: AI-based virtual sensing to enhance real-time understanding and enhance learning systems – demonstrates how digital twin technology can perform real-time virtual measurements of critical variables across diverse industrial assets. Addressing the challenge of measuring variables from inaccessible or costly monitors to monitors, leveraging digital twins for continuous virtual sensing. This testbed uses transfer learning technology that combines virtual and real-world data to calibrate AI-based novelty detection systems, enabling AI-driven, proactive maintenance, and improves maintenance accuracy by 40%. Lead Developer: Aingura iiot. aegis: Agents’ Acceptance Guidance to Improve Student Outcomes – Testbed shows that multi-agent systems trained with high-risk student survey data can identify cognitively emotional triggers that affect learning effectiveness. The testbed simulates intervention scenarios and shows how students can be trained to respond more effectively to these triggers, leading to improved engagement and lower dropout rates. We examine AI-driven interventions for individualized learning and dropout prevention in education. Lead Developer: My Performance Learning. FAB – Factory Box for Rapid Disaster Manufacturing: Testbed is a mobile, modular, digital twin-compatible manufacturing unit that can produce critical energy components in disaster-hit zones. It reduces transportation costs and logistical burdens, minimizes downtime for essential systems and infrastructure, and provides localized, resilient production with minimal setup. It also allows remote adjustment via a digital twin interface. These field-deployable production systems improve community resilience and demonstrate the feasibility of digital twin-enabled micromanufacturing in high stress scenarios. Lead Developers: DRG Solutions and Oak Ridge High School, Contributing Technology Provider: Oak Ridge National Laboratory. Q-SMART: Quantum-Safe Data Exchange in Resilient Smart Home Cognitive Networks – The Q-SMART Testbed validates intelligent home systems that are independent of cognitive and secure self-learning platforms built on distributed open source components. Create your personal cognitive hub using wireless mesh networks, dynamic live 3D models (digital twin), multi-agent AI framework, and XR interfaces to use energy optimization and indoor air quality management. The system highlights edge native processing, ensures that all data remains in the home, and leverages the Quantum-Safe (PQC-enabled) protocol for future prevention security. By focusing on self-learning algorithms, it predicts and controls home aspects such as HVAC and ventilation, reducing energy consumption by up to 25% and increasing residents’ comfort. Lead Developer: Winnio. Transform: Transform TestBed is an application framework that systematically transforms static 2D data schemas with real-time updates into dynamic 4D geographic representations. The testbed uses digital twins to create dynamic live 3D models that act as virtual representations of the physical environment. Digital Twin is integrated with wireless mesh networks, sensors, and self-learning AI frameworks to monitor and predict home conditions. They allow seamless human system AI interactions via the XR interface, allowing intuitive control and feedback for energy optimization and indoor air quality management. This testbed can be used for a variety of applications, including smart city infrastructure, transportation, utilities, and emergency services. Lead Developer: EDX Technologies, Co-Developer: CRYSP. SAFESME: Accelerating Smart Assets for Small Business Equipment – Testbed demonstrates the enablement of digital twin-driven commissioning and digital services for SME manufacturing equipment, particularly injection molding and packaging machines. We examine how small and medium-sized enterprise manufacturing equipment can achieve cost-effective digital twin onboarding and digital services transformation. The testbed allows for quick and automated onboarding and commissioning in under 5 minutes per asset, reducing setup time and operator effort, and maintaining high model alignment and API performance without the need for expensive PLC upgrades or high development overhead. Lead Developer: HS Software. Early Notification and Guidance for Academic Growth and Engagement: The Testbed focuses on determining whether digital twins can be used to identify and support at-risk students. This testbed creates a comprehensive digital twin system that integrates academic scores, class participation, extracurricular engagement, behavioral indicators, and sentiment analysis. Lead Developer: Austin Community College District. Synthetic Healthcare Pathway Digital Twin (SyntheKID): The testbed transforms local healthcare delivery through innovative synthetic digital twins that model the chronic kidney disease (CKD) pathway across Yorkshire, UK. Examining how privacy-providing digital twins can optimize healthcare systems, enabling scenario planning and demand forecasting without compromising patient confidentiality. The platform examines key intervention points that can improve outcomes and system efficiency by simulating patient journeys from early detection to clinical progress. Lead Developer: Health Innovation Network Yorkshire and Humber. Co-developers: Nexus, Counterpoint Technologies, Crysp.

The Digital Twin Testbed Program implements a DTC complexity framework that leverages business maturity models, platform stack architectures, and feature schedule tables.

Learn more about the DTC Digital Twin Testbed Program. Become a DTC member and join global leaders to drive digital twin evolution and realize technology.

About the Digital Twin Consortium

The Digital Twin Consortium is the authority of the Digital Twin. It combines industry, government, and academia to promote consistency in digital twin technology vocabulary, architecture, security, and interoperability. From aerospace to natural resources, we are advancing digital twin technology in many industries.

read more