The adoption of Industry 4.0 technologies beyond manufacturing is gammg traction in construction engineering, particularly through the use of digital twin technology for infrastructure monitoring and maintenance. Digital twins, originally developed for industrial systems, offer real-time digital representations of physical assets by integrating static data, such as design specifications, with dynamic data streams from embedded sensors. This paper presents a digital twin solution which integrates sensor data tailored for bridge monitoring, using the Asset Administration Shell (AAS) to enable interoperability and structured data management. By consolidating diverse data sources - from planning, construction, and operation phases, the system facilitates continuous structural health assessment and assists structural aging by means of predictive maintenance strategies. Central to this solution is the BBox toolset, sensor configuration, data ingestion, visualisation, and centralised knowledge management for network infrastructure such as bridges. The architecture enables both static data imports (e.g., CAB files, IFC models) and dynamic data acquisition (e.g., MQTT-based sensor readings) via a time-series database. Moreover, the architecture can be integrated with existing tools such as Bridge Management Systems (BMS) and Building Information Modelling (BIM), promoting a unified, data-driven approach to infrastructure management without displacing current engineering workflows.     «

The adoption of Industry 4.0 technologies beyond manufacturing is gammg traction in construction engineering, particularly through the use of digital twin technology for infrastructure monitoring and maintenance. Digital twins, originally developed for industrial systems, offer real-time digital representations of physical assets by integrating static data, such as design specifications, with dynamic data streams from embedded sensors. This paper presents a digital twin solution which integrates...     »