BIM-based information modeling for semantic description of intelligent structural health monitoring systems
Intelligent structural health monitoring systems, which play a crucial role in digitalization processes within the construction industry, are composed of sensor nodes possessing so called "on-chip intelligence". Structural health monitoring (SHM) based on sensor nodes with on-chip intelligence, referred to as "intelligent SHM", advances automated, pro-active real-time analyses of measured data directly on board the sensor nodes. Although intelligent SHM is continuously gaining importance, there are no standards available to regulate design and implementation of intelligent SHM systems. Furthermore, there is a lack of well-defined formalisms supporting digital representations of life-cycle information about the inherent logics of intelligent sensor nodes, about the SHM strategies implemented, about the overall SHM system and about the system dynamics ("monitoring-related information"). The proposed research project aims at developing a semantic model to digitally represent monitoring-related information based on a consistent formalism. In order to ensure correct semantics on a sound mathematical basis, the semantic model builds upon an ontology-driven conceptual approach. A major research question addresses the representation of system dynamics, which is to be solved through ontology temporalization using temporal logics as well as temporal-logical model structures based on modal logics. It is proposed to integrate the semantic model into the methods of building information modeling (BIM). Therefore, a "parametric" BIM concept (as opposed to "parameterized" BIM concepts) for intelligent SHM systems will be proposed. For validation, the concept will be materialized in a logical schema that builds upon open BIM standards. A main benefit of this project is a novel methodology for coherent integration of monitoring-related information (even in the planning phase of a building) into standardized building information models widely used in civil engineering. All monitoring-related information will be digitally available and can be updated throughout the life time of buildings. Finally, holistic analyses of structural, environmental, and operational data will be possible in a new context, which may serve as a reliable basis for decision making with respect to operation, maintenance and repair, facilitating infrastructure sustainability and resilience.