A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Knowledge graph-based data integration system for digital twins of built assets
Abstract The emergence of digital twin technologies offers a promising avenue for improving decision-making through the integrated use of up-to-date physical or synthetically simulated data. Nevertheless, the practical implementation of digital twins in the built environment remains a significant challenge. This paper describes a system that seamlessly integrates data into digital twins of built assets. The system uses a knowledge graph to achieve data integration, which is designed to be modular, flexible, and interoperable. The graph includes BIM models, metadata from an external IoT platform, and process-related information. The system is microservice-based and revolves around a graph database housing the knowledge graph. It employs dynamic operations to update the knowledge graph and is tested using civil engineering infrastructure examples. Results from this work can be used to create pipelines that extract and operate with data connecting computational agents integrated into the system as microservices or connected through the system API.
Highlights Digital twin requirements for built assets in the built environment. Conversion from IFC model to equivalent property graph model. Ontology-based integration of digitized processes stored in local databases. Ontology-based integration of sensor data from an external IoT platform. A cloud-based event-driven microservice-based digital twin system architecture.
Knowledge graph-based data integration system for digital twins of built assets
Abstract The emergence of digital twin technologies offers a promising avenue for improving decision-making through the integrated use of up-to-date physical or synthetically simulated data. Nevertheless, the practical implementation of digital twins in the built environment remains a significant challenge. This paper describes a system that seamlessly integrates data into digital twins of built assets. The system uses a knowledge graph to achieve data integration, which is designed to be modular, flexible, and interoperable. The graph includes BIM models, metadata from an external IoT platform, and process-related information. The system is microservice-based and revolves around a graph database housing the knowledge graph. It employs dynamic operations to update the knowledge graph and is tested using civil engineering infrastructure examples. Results from this work can be used to create pipelines that extract and operate with data connecting computational agents integrated into the system as microservices or connected through the system API.
Highlights Digital twin requirements for built assets in the built environment. Conversion from IFC model to equivalent property graph model. Ontology-based integration of digitized processes stored in local databases. Ontology-based integration of sensor data from an external IoT platform. A cloud-based event-driven microservice-based digital twin system architecture.
Knowledge graph-based data integration system for digital twins of built assets
Ramonell, Carlos (author) / Chacón, Rolando (author) / Posada, Héctor (author)
2023-09-25
Article (Journal)
Electronic Resource
English
Developing a Federated Data Model for Built Environment Digital Twins
| British Library Conference Proceedings | 2021