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.

Climate change is evident. There is an urgent need to ensure resilience of civil infrastructure against impacts of a changing climate. Making civil infrastructure resilient requires precise insights into the infrastructure condition, taking into account structural and environmental information and, increasingly, socio-economic phenomena. Modern civil infrastructure is able to both analyze its condition and to adapt to the environment, e.g. through (semi-)active dampers or sensor-based actuators. However, although frequently termed "smart", current infrastructure is unable to learn or to anticipate from structural and environmental factors, or to utilize the Internet of Things (IoT) for integrating socio-economic phenomena. This project aims to take advantage of the emerging paradigm of "cognitive buildings" to develop a novel scientific basis towards resilient infrastructure. Cognitive buildings are able to sense environmental conditions, to learn from external (or user-related) factors, and to integrate IoT devices to optimize performance. However, cognitive buildings, typically focusing on reducing energy consumption and carbon footprint, lack the ability of seamlessly integrating structural information relevant to resilience. The proposed project therefore aims to extend the cognitive buildings paradigm towards infrastructure resilience. As a point of departure, structural health monitoring and structural control (SHM/SC) strategies, relevant to resilient infrastructure, will be considered. For several years, SHM/SC practice has been mainly relying on data-driven modeling for extracting information on the structural condition. However informative, data-driven modeling lacks physical background and fails to provide the information necessary for SHM/SC to produce reliable predictions on future structural behavior. As a consequence, the proposed extension to the cognitive buildings paradigm will involve integrating decentralized, physics-based modeling into wireless SHM/SC. This research is proposed out of a DFG-funded German-Greek joint research project conducted to initiate an international collaboration. The expected outcome of the proposed research is a methodology for efficiently embedding decentralized physics-based models into wireless SHM/SC systems to advance infrastructure resilience. It is further expected that this project will contribute to enhancing the performance of wireless SHM/SC systems and to integrating infrastructure systems into the concepts of "Industry 4.0", "Smart City", and the "Internet of Everything". This research project marks a shift towards an entirely new paradigm in embedded computing for wireless SHM/SC in accordance with ongoing developments facilitating resilient infrastructure in the light of climate change.