Measurement Science


  1. Measurement foundations
    Underlying mathematical, statistical and information theory, Signal processing and data analysis, Dynamic quantities and state estimation, Measurement data and information fusion, Evaluation of measurement uncertainty, Measurement of nonquantitative properties

  2. Advanced Measurement Methods
    Smart sensor applications, Condition monitoring, Virtual and quantum-based system references, Digital twins, "Self-X" strategies, Numerical simulation approaches, Parametric and data-driven modelling approaches

  3. Networked and IoT-related measurement systems
    Aggregated sensor and measurement systems, “Soft Sensors” and practical information fusion, Autonomous measurement systems, Synchronization and dynamic modelling of aggregated systems

  4. AI approaches in measurement
    Intelligent and learning systems in measurement, Explainable and transparent AI, Objective quality assessment of data-driven and learning systems

  5. Education for Measurement and Measurement for Education 

  6. Applications
    Production processes and Robotics, Energy supply, Environmental monitoring, Mobility, Safety and security, Health and socio-technical systems

Supporting Institutions