Research and development for the use of distributed fiber optic sensors for condition monitoring of bridges, Investigation and evaluation of the usability and limitations of various methods of distributed fiber optic sensing based on Rayleigh, Brillouin and Raman scattering for condition monitoring of bridges, Development of suitable test setups and laboratory experiments, execution and evaluation of test series in the laboratory and on relevant test specimens, Planning, execution and evaluation of fiber optic measurement campaigns on various real structures as part of business trips, Investigation of the influence of sensor geometry, measurement parameters, installation method and location of the fiber optic sensors and of external influences on the measurement results and the measurement data quality as well as development of best practices for the instrumentation of bridge structures, Development and implementation of methods and algorithms to compensate for the influences of disturbance variables to increase the quality of measurement data and for data reduction, in particular based on machine learning (ML), Development and implementation of ML-based algorithms for the automated detection, localization and classification of damages and traffic influences, Derivation of holistic case-related monitoring concepts for bridge structures from the collected findings together with the partners, Responsibility for creating and continuously updating/expanding a document describing the current state of the art, the findings collected in the project and the derived best practices, Publishing results by writing scientific articles for publication in recognized peer-reviewed journals, preparing conference contributions and giving talks and presentations, Creating project reports