Relocatable modular buildings (RMBs) offer flexibility, mobility, and scalability, making them ideal for dynamic environments. However, managing the allocation of increasing RMB modules poses logistical challenges, with inefficiencies in manual methods leading to delays and higher costs.

This study, titled: ‘Integrated Digital-Twin-based Decision Support System for Relocatable Module Allocation Plan: Case Study of Relocatable Modular School System’, introduces a Digital Twin (DT)-based decision support system integrating Building Information Modeling (BIM), Internet of Things (IoT), and Geographic Information Systems (GIS).

The system uses real-time data to optimise module allocation, reduce costs, and improve lifecycle management.

Validated through a South Korean school project, it provides a data-driven approach for efficient, sustainable resource utilisation and maintenance.