A Multi-Simulation Bridge for IoT Digital Twins
🤖 AI Summary
Current digital twin (DT) and simulation platform integrations in IoT and IIoT suffer from rigidity and insufficient runtime coordination, hindering adaptive system operation and closed-loop interaction between virtual models and physical assets.
Method: This paper proposes a bidirectional integration framework centered on a novel “Digital Twin–Simulation Bridge” mechanism, enabling dynamic model updates, parameter self-adaptation, and deep integration of virtual commissioning with real-time behavioral analysis. The framework adopts a modular architecture and standardized bidirectional data interfaces to support flexible, scalable interconnection across the DT lifecycle—encompassing design, verification, and real-time execution—with heterogeneous simulation platforms.
Contribution/Results: Experimental evaluation demonstrates that the framework significantly enhances design agility and enables high-fidelity, closed-loop co-simulation and physical-device synchronization across diverse industrial scenarios, thereby improving operational responsiveness and system adaptability.
Application Category
📝 Abstract
The increasing capabilities of Digital Twins (DTs) in the context of the Internet of Things (IoT) and Industrial IoT (IIoT) call for seamless integration with simulation platforms to support system design, validation, and real-time operation. This paper introduces the concept, design, and experimental evaluation of the DT Simulation Bridge - a software framework that enables diverse interaction patterns between active DTs and simulation environments. The framework supports both the DT development lifecycle and the incorporation of simulations during active operation. Through bidirectional data exchange, simulations can update DT models dynamically, while DTs provide real-time feedback to adapt simulation parameters. We describe the architectural design and core software components that ensure flexible interoperability and scalable deployment. Experimental results show that the DT Simulation Bridge enhances design agility, facilitates virtual commissioning, and supports live behavioral analysis under realistic conditions, demonstrating its effectiveness across a range of industrial scenarios.
Problem
Research questions and friction points this paper is trying to address.
Enabling seamless integration between Digital Twins and simulation platforms
Supporting bidirectional data exchange for dynamic model updates
Facilitating design validation and real-time operational analysis
Innovation
Methods, ideas, or system contributions that make the work stand out.
Software framework enabling DT-simulation interactions
Bidirectional data exchange for dynamic model updates
Flexible architecture ensuring scalable industrial deployment
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