Resilient infrastructure based on cognitive buildings

Motivation and research problem

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.

Research objectives

The goal of this project it to take advantage of the emerging paradigm of “cognitive buildings” to develop a novel scientific basis towards resilient infrastructure (Figure 1). 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 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.

Expected results

The expected outcome of this 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 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.

Mercator Fellow

Professor Manolis has been awarded the title “Mercator Fellow” in recognition of his dedication to this project. Adding significant value to this project, Professor Manolis will bring international expertise and increase the visibility of this project. It is expected that DFG’s Mercator Fellowship will facilitate a long-term project-based German-Greek cooperation. Contact information are provided below.


Professor Dr. Kay Smarsly
Hamburg University of Technology
Institute of Digital and Autonomous Construction
Blohmstraße 15
21079 Hamburg
Email: kay.smarsly(at)

Professor George D. Manolis, PhD.
Aristotle University of Thessaloniki
Department of Civil Engineering
Division of Structures
Thessaloniki GR-54124
Email: gdm(at)