A Digital Twin Applications in Rail Systems: A Real-Time Monitoring Framework Based on BIM–GIS–IoT Integration

Abstract

Digital twin applications have gained increasing attention in rail systems; however, existing studies predominantly focus on signaling, rolling stock, or predictive maintenance, while station scale implementations integrating spatial models with real time sensor data remain limited. This study addresses this gap by developing an integrated framework that combines Building Information Modeling, Geographic Information Systems, and Internet of Things sensor data to support real time monitoring and operational visibility in metro stations. Within the proposed approach, environmental and equipment related sensor measurements, including temperature, humidity, air quality, vibration, and acoustic data, are associated with spatially referenced BIM and GIS models and presented through a web based three dimensional dashboard. A case study conducted at a selected metro station operated by Metro Istanbul is used to demonstrate the practical applicability of the framework in an operational environment. The results indicate that the integrated structure improves situational awareness, enhances the visibility of station equipment conditions, and establishes a reliable data integration infrastructure for station level monitoring. The main contribution of this study is the implementation of a monitoring level digital twin architecture that connects spatial information models with continuous sensor data streams in an active metro operation context.