Digital twin visualization combining BIM, IoT data and GIS mapping for relocatable modular buildings.
Ansan, South Korea, August 19, 2025
A research team at Hanyang University ERICA developed a digital twin–enabled facility management system (DT-FMS) to improve tracking, management and reuse of relocatable modular buildings. The platform integrates BIM, IoT sensors and GIS to create a real-time virtual model that supports monitoring, logistics and decision support across three layers: physical, digital and service. Tested on a relocatable modular school in South Korea, the framework improved module distribution, reuse and operational efficiency. Researchers say the approach can support circular construction by extending component life, though wider adoption needs data standards, sensor investment and manager training.
The research team from Hanyang University ERICA in South Korea introduced a digital twin–enabled facility management framework designed to support the lifecycle management and circularity of relocatable modular buildings (RMBs). This framework links physical assets with real-time virtual models to support planning, operation, and reuse across sites, aiming to strengthen the modular construction sector and its asset management practices.
The framework is intended to assist the growing modular building industry by improving how RMB assets are tracked and managed throughout their life cycle. RMBs are described as structures built from prefabricated modules that can be assembled, dismantled, and transported to multiple sites. By integrating digital technologies, the framework seeks to reduce both cost and environmental impacts associated with traditional construction while promoting reuse and reconfiguration where feasible.
The framework combines BIM, IoT, and GIS to enable 3D modelling, sensor-based monitoring, and location-driven logistics planning. The resulting platform is organized into three layers: physical, digital, and service. In the physical layer, tracking and communication cover real-world components and the people involved, including engineers and other stakeholders. The digital layer encompasses modelling, data integration, and analytics. The service layer provides ongoing monitoring and control, enabling decision-making across a building’s life cycle.
The research was led by Associate Professor Yonghan Ahn, with participation from a co-author, and the work was published in a peer journal dedicated to automation and construction. The study notes that digital twins can play a significant role in promoting a circular economy in construction by enabling the reuse, reconfiguration, and optimal relocation of modular units, thereby reducing waste and preserving value across multiple lifecycles. While digital twin concepts are advanced in various fields, the article highlights that their application in modular construction has been more limited to date.
The framework addresses a persistent challenge in modular construction: tracking modular assets across several lifecycles and sites. By linking physical components with a digital representation and a service-oriented layer for decision-making, the approach supports better planning, asset management, and lifecycle optimization. The emphasis on a circular economy perspective aligns modular construction with broader goals of waste reduction, material reuse, and value retention through strategic relocation and reconfiguration of RMB modules.
The framework appeared in the current issue of Automation in Construction, with dissemination focused on the integration of BIM, IoT, and GIS to deliver a cohesive platform capable of 3D modelling, sensor data analysis, and logistics planning for RMB lifecycles. The multi-layer design aims to simplify user interaction: operators, engineers, and stakeholders can monitor and control system behavior and make decisions that affect an entire building life cycle.
It is a digital twin–enabled system that links physical assets with real-time virtual models to support lifecycle management and circularity for relocatable modular buildings.
RMBs are structures built from prefabricated modules that can be assembled, dismantled, and transported to different sites, supporting flexible use and reuse across projects.
The framework combines BIM, IoT, and GIS to enable 3D modelling, sensor-based monitoring, and location-driven logistics planning.
The layers are physical, digital, and service. The physical layer tracks real-world components and people, the digital layer handles modelling and data analytics, and the service layer supports monitoring, control, and decision-making.
The case study indicated improvements in module distribution, reuse, and management efficiency for RMBs, with associated reductions in operating costs and improvements in energy efficiency.
The work was led by a research associate professor and published in a construction-focused journal, highlighting the potential for digital twins to support circular economy practices in modular construction.
The framework aims to promote circular economy practices by enabling reuse, reconfiguration, and optimal relocation of modular units, thereby minimizing waste and maximizing value across their lifecycles.
Feature | Description |
---|---|
Framework name | Digital twin–enabled facility management framework for relocatable modular buildings (RMBs) lifecycle |
Core technologies | BIM, IoT, GIS enabling 3D modelling, sensor data monitoring, and location-driven logistics planning |
Target and scope | Lifecycle management and circularity for RMBs, including planning, operation, and reuse across sites |
Architecture | Three-layer platform: physical, digital, service |
Case study | Relocatable modular school system in South Korea evaluating distribution, reuse, and management efficiency |
Lead researchers | Lead by Associate Professor Yonghan Ahn with co-author Dr. Dennis Nguyen |
Publication | Published in the journal Automation in Construction earlier in the month |
Potential impact | Supports circular economy practices by enabling reuse, reconfiguration, and relocation of modular units to minimize waste and maximize value |
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