BIM2TWIN aims to build a Digital Building Twin (DBT) platform for construction management that implements lean principles to reduce operational waste of all kinds, shortening schedules, reducing costs, enhancing quality and safety and reducing carbon footprint. BIM2TWIN proposes a comprehensive, holistic approach. It consists of a (DBT) platform that provides full situational awareness and an extensible set of construction management applications. It supports a closed loop Plan-Do-Check-Act mode of construction. Its key features are:
1> Grounded conceptual analysis of data, information and knowledge in the context of DBTs, which underpins a robust system architecture
2> A common platform for data acquisition and complex event processing to interpret multiple monitored data streams from construction site and supply chain to establish real-time project status in a Project Status Model (PSM)
3> Exposure of the PSM to a suite of construction management applications through an easily accessible application programming interface (API) and directly to users through a visual information dashboard
4> Applications include monitoring of schedule, quantities & budget, quality, safety, and environmental impact.
5> PSM representation based on property graph semanticaly linked to the Building Information Model (BIM) and all project management data. The property graph enables flexible, scalable storage of raw monitoring data in different formats, as well as storage of interpreted information. It enables smooth transition from construction to operation.
BIM2TWIN is a broad, multidisciplinary consortium with hand-picked partners who together provide an optimal combination of knowledge, expertise and experience in a variety of monitoring technologies, artificial intelligence, computer vision, information schema and graph databases, construction management, equipment automation and occupational safety. The DBT platform will be experimented on 3 demo sites (SP, FR, FI).
Field of science
- /natural sciences/computer and information sciences/artificial intelligence/computer vision
Call for proposal
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Funding SchemeRIA - Research and Innovation action