In addition to the regular contributions submitted to the IMEKO Technical Committees, authors will have the opportunity to present their work in a number of Special Sessions focusing on specific topics and emerging areas of interest. Below you can find the list of Special Sessions currently planned for the Congress. If your contribution fits the scope of one of these sessions, you are welcome to submit it directly to the relevant Special Session.
Wearable and non-invasive technologies are reshaping healthcare, occupational safety, and environmental monitoring. By enabling continuous acquisition of physiological, biomechanical, chemical, and environmental parameters, these systems support applications ranging from heart rate, respiration, oxygen saturation, temperature, and motion monitoring to personal exposure assessment, air-quality sensing, and the evaluation of plant elongation, sap flow, and hydration status.
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Non-destructive testing and evaluation (NDT&E) is a key enabling technology for ensuring the integrity, safety, and durability of materials, components, and structures across industrial, energy, and cultural heritage applications, where non-invasive and reliable diagnostics are essential. The increasing complexity of systems and the demand for higher reliability standards require continuous advances in sensor technologies, measurement methodologies, and data analysis techniques.
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During the last few decades, health monitoring technologies have evolved from isolated wearable devices toward integrated sensor ecosystems combining ambient sensing, smart objects, and non-invasive monitoring solutions. While these technologies are gaining increasing consensus for continuous health monitoring across the entire human lifespan, transitioning them from “consumer gadgets” to “clinical-grade tools” requires a rigorous metrological approach, to ensure stakeholders can appropriately interpret and exploit measurement results. This Special Session focuses on the metrological challenges and opportunities associated with heterogeneous sensor networks for lifelong health monitoring.
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Measurement science can play a driving role in addressing scientific and technological challenges shaping the near future, including artificial intelligence (AI), space exploration, climate change, energy transition, smart agriculture, quantum technologies, robotics, cybersecurity, and equitable healthcare for all. These domains call for fresh multidisciplinary metrological perspectives and strategies, such as distributed and pervasive sensing, sensor fusion, digital twins, advanced methods for data analysis and uncertainty quantification, explainable and trustworthy AI for measurement, and digital metrology infrastructures.
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Quantum technologies and metrology share a two-way relationship. On one side, quantum effects underpin the most accurate measurements we can make – the Josephson and quantum Hall effects realise the electrical units, optical clocks are driving the imminent redefinition of the second, and entanglement and squeezing push sensing beyond the standard quantum limit (“quantum for metrology”). On the other side, the emerging quantum industry increasingly needs measurement science itself: quantum computers, sensors and communication systems must be characterised, benchmarked, tested and standardised before they can be trusted, compared and deployed (“metrology for quantum”).
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The rapid evolution of optical metrology-including camera-based systems, confocal sensing, interferometry, and tomography—has significantly improved the precision, flexibility, and applicability of modern measurement systems. These technologies are widely used in advanced manufacturing, biomedical imaging, and scientific research, enabling high-resolution, multidimensional, non-contact measurements, and establishing optical metrology as a key tool for industrial inspection and experimental analysis. However, real-world measurement scenarios introduce substantial challenges. Optical data are affected by multiple noise sources, such as photon shot noise, electronic interference, environmental disturbances, and optical aberrations, which degrade signal quality.
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Sensor networks are critical enablers of digital transformation across Industry 4.0 & 5.0, smart cities, environmental monitoring, and energy systems. As sensing systems evolve from individual instruments to complex, interconnected and intelligent networks, ensuring measurement traceability, uncertainty evaluation, and data trustworthiness becomes increasingly challenging. This special session addresses the emerging field of sensor network metrology, focusing on the development of metrological frameworks for distributed and heterogeneous sensing systems.
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Measurement science is becoming increasingly relevant to veterinary and animal sciences as sensing, imaging, wearable devices, Internet of Things (IoT), omics and genomic technologies, and artificial intelligence (AI) enable the quantitative assessment of animal health, physiology, behaviour, welfare, performance, genetic and molecular characteristics, and interactions with the environment. Despite these advances, important measurement challenges remain. These include the definition of measurands, establishment of reliable reference values and ground truth, sensor calibration and validation, measurement uncertainty, repeatability and reproducibility, data quality, and comparability of results across animals, systems, environments, and experimental conditions.
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Advances in ophthalmic diagnosis, treatment, and vision assessment increasingly rely on highly accurate optical measurement technologies. Modern ophthalmic systems, including optical coherence tomography (OCT), corneal topographers, wavefront aberrometers, ocular biometers, retinal imaging systems, intraocular pressure measurement systems, surgical guidance systems, and treatment monitoring devices, require rigorous metrological characterization and validation to ensure measurement accuracy, traceability, repeatability, and comparability across clinical centers.
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Advanced nondestructive measurement and imaging are increasingly important for quantitative evaluation and structural integrity assessment of advanced engineering systems. Emerging applications involving complex geometries, multilayered structures, composites, coatings and safety-critical components require measurement methods that offer higher sensitivity, resolution, adaptability and interpretability.
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The global transition toward clean and low-carbon energy systems is driving demand for batteries with higher energy density, enhanced safety, longer service life, and reduced cost. Meeting these requirements depends increasingly on accurate, reliable, and real-time measurements of battery performance, degradation, and safety throughout the entire lifecycle. Battery sensing is undergoing a fundamental transformation-from external to internal sensing, from physical to chemical measurements, and from single-parameter acquisition to coordinated multi-parameter monitoring.
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Process tomography is a typical non-intrusive visual sensing technique for industrial process perception. It overcomes the limitations of traditional point measurement methods by enabling real-time, undisturbed spatial visualization of internal flow fields, effectively addressing common industrial monitoring challenges such as invisible process states and unmeasurable transient flow behaviors. Long-term systematic research in this field has formed a complete technical system covering multi-modal sensing, high-speed data acquisition and intelligent image reconstruction, supporting robust industrial monitoring applications. With the rapid development of industrial intelligence, traditional tomographic technologies are constrained by limited imaging resolution and poor adaptability to complex operating conditions.
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Writing in 1984, O. D. Duncan, in his book, Notes on Social Measurement, called for closer ties across the social sciences and metrology. Duncan argued that the advances in measurement modeling made between the 1920s and the 1960s in the works of Thurstone and Rasch called for intensified dialogues across the sciences. He held “that social measurement should be brought within the scope of historical metrology, while that discipline learns to take advantage of sociological perspectives.” At the time of his passing almost 20 years ago, a colleague referred to Duncan in an obituary as “the most important quantitative sociologist in the world in the latter half of the twentieth century.” The exchange of views desired by Duncan began in earnest in 2008 at an IMEKO TC1-TC7-TC13 Joint Symposium in Annecy, France, and at another held in 2010 in London.
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Dynamic measurement is becoming a key enabling capability as industry moves toward intelligent, digital and highly automated systems. In advanced manufacturing, intelligent transportation, robotics, renewable energy, aerospace and next-generation infrastructure, critical physical quantities often change rapidly under complex operating conditions. Accurate, traceable and reliable measurement of these changes is essential for technological innovation, real-time decision-making, system safety, operational efficiency and product quality.
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Reliable measurements are essential for addressing societal challenges related to climate change, environmental protection, energy transition, industrial competitiveness, digitalization and public health. Metrology provides the foundation for trustworthy and comparable measurement results, supporting scientific research, innovation, regulation, and evidence-based decision-making. The European Metrology Networks (EMNs), established under EURAMET, strengthen collaboration across Europe by bringing together National Metrology Institutes, Designated Institutes, academia, industry, regulators, and other stakeholders. Through coordinated activities, EMNs identify emerging measurement needs, promote best practices, foster harmonization, and support the uptake of metrological knowledge and infrastructure.
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Vision-based measurement is already widely used across scientific and industrial applications, but recent progress in computer vision, machine learning, and artificial intelligence is changing how these systems are designed. In many emerging approaches, useful measurement information is learned directly from data rather than relying only on predefined physical models or handcrafted processing pipelines.
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Ultrasonic wave propagation serves as a fundamental physical basis for both medical diagnostics and industrial non-destructive testing (NDT). Despite their distinct application scenarios, both fields share common theoretical foundations - including wave-matic scattering, acoustic attenuation, and inverse problems - and face similar technical challenges such as high-resolution imaging in complex media and quantitative characterization under noisy conditions. This special session aims to foster interdisciplinary exchange between medical and industrial ultrasonic communities.
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Wind and photovoltaic plants are distributed renewable energy conversion systems generating large amounts of operational data, but the indicators and forecasts derived from them are not always automatically trustworthy. Their meaning depends on what is being measured, how data are acquired and processed, whether the measurements remain valid under changing operating conditions, and how uncertainty affects their interpretation.
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Quantitative spectroscopy is a key enabling technology in modern measurement science, enabling precise determination of chemical composition, temperature, pressure, velocity and other physical quantities through light-matter interaction across the ultraviolet, visible, infrared and terahertz spectral regions. Emission, absorption and scattering spectroscopic methods have become indispensable in industrial process control, energy systems, environmental monitoring, biomedicine, agriculture, security, and extreme environments. Recent advances in laser sources, optoelectronic devices, integrated photonics, and quantum technologies are redefining how spectroscopic measurements are conceived, implemented and applied.
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Low-frequency vibrations are measured in the air as infrasound, in water and as ground motion for a wide range of purposes: from earthquake detection, through exploration and structural design of buildings, to the detection of nuclear weapon explosions – all these fields are of great significance in the context of ‘metrology for humanity’, the title of the World Congress.
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Parameter measurement in multiphase flow environments has a wide range of applications in energy and power, petrochemicals and environmental engineering. However, due to the cost of deploying a large number of sensors, traditional physical measurements can only obtain local or cross-sectional average information of measured parameter, making it difficult to restore parameter information of the entire space in real time.
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Even though different meanings could be attributed to environmental enginering, a large number of scientists and engineers agree that it is the ensemble of studies, design and experimental techniques, data processing procedures and applications, where the focus is on the interaction between the environment and the performance of products and engineering systems with reference to their entire life-cycle.
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This “Modeling Measures” symposium will follow and expand upon the “New Metrological Horizons” special session immediately preceding it. As established in the prior session, over the course of several decades, measurement researchers in the human sciences (psychology and the social sciences) developed what have recently been recognized by metrologists as belonging to the same class of concepts, theories, models, and results “that metrologists consider paradigmatic of measurement” (Mari & Wilson, 2014, p. 326).
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Conformity assessment underpins consequential decisions in calibration, testing, inspection, certification, regulation, production control and reference-material characterization. Yet measurement uncertainty is often treated as a reporting requirement rather than a central component of decisionmaking. This creates a gap between uncertainty evaluation and the actual risks borne by producers, consumers, laboratories, regulators and end users when items, processes, materials or batches are accepted, rejected or certified.
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Medical electrical devices play a critical role in modern healthcare, supporting diagnosis, therapy, monitoring, and personalised treatment. However, the complexity of these devices, together with the growing use of non-stationary electrical signals, bioimpedance-dependent parameters, and AI-assisted analysis, poses new metrological challenges in traceability, calibration, uncertainty evaluation, and regulatory compliance.
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Biomedical and human-centered measurement is undergoing a profound transformation driven by the convergence of advanced sensing technologies, intelligent instrumentation, artificial intelligence, robotics, and computational methods. These developments are enabling increasingly comprehensive assessment of physiological quantities, human movement, and human-system interaction through heterogeneous sensing technologies, including photonic and fiber-optic sensors, thermal and hyperspectral imaging, wearable and inertial devices, and contactless motion capture, supported by data driven approaches.
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Accurate measurements and reliable calibration are crucial for industry, healthcare, environmental monitoring, and regulation. However, many emerging economies encounter substantial obstacles: inadequate funding, insufficient calibration infrastructure, a lack of trained personnel, and inconsistent access to traceable standards. The special section “Low-Cost Metrology and Calibration Strategies for Emerging Economies” emphasizes practical, economical, and traceable methods to bridge existing gaps and enhance local capacity development.
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The digital transformation of agriculture and food systems increasingly relies on accurate, reliable, and timely measurements. Emerging sensor technologies, intelligent instrumentation, connected measurement systems, and advanced data-processing methods are enabling new approaches for monitoring crops, soil, water, livestock, food products, processing operations, and supply chains.
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Dataspaces and the digital product passport (DPP) are changing rapidly how companies ensure quality and disclose product information – from manually researching requirements, filling out forms, and sending documents, to automatically discovering all relevant product requirements and providing requested product data to authorized parties. The ultimate goal is for data consumers (users, service providers, recyclers, authorities) to be able to instantly retrieve granular product information from available business data via a global data ecosystem.
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The development of advanced materials is a major driver of progress in next-generation measurement technologies, sensors, and instrumentation. Materials ranging from nanostructured to polymers, composites, and superconducting or quantum materials offer unique physical properties that can enable new measurement principles and improved device performance.
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The built environment is a complex system involving materials, components, buildings, infrastructures, construction processes, indoor and outdoor environments, and their interactions with users throughout the entire life cycle. Its transformation towards safer, healthier, more resilient, resource-efficient and low-carbon solutions increasingly depends on the availability of reliable, accurate and interoperable measurement data.
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Consumer safety, fair trade, and industrial competitiveness heavily rely on the seamless integration of legal metrology, accredited testing, and robust market surveillance. As global supply chains evolve, modern regulators face unprecedented challenges driven by cross-border e-commerce, complex digital products, and chemical or material safety compliance. This special session addresses the critical nexus between metrology and product safety, focusing on how harmonized measurement science, chemical analysis, and standardized conformity assessment serve as the backbone for consumer protection and a level playing field in global markets.
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The Special Session on “Metrology for Sustainability in the Indo-Pacific Area” will highlight the critical role of measurement science, instrumentation, and metrological technologies in addressing sustainability challenges across the region. Reliable, accurate, comparable, and traceable measurements are fundamental for monitoring resource consumption, environmental changes, energy performance, healthcare outcomes, industrial processes, and mitigation strategies. Metrology therefore provides the scientific foundation for evidence-based decisions, sustainable technologies, and societal resilience.
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Magnetic measurements offer a powerful, non-invasive route to condition monitoring of electrical machines, but the performance required from magnetic sensors and instruments depends strongly on the machine, fault mechanism, sensor location and operating environment. This Special Session brings together IMEKO TC4 expertise in electrical and magnetic measurement with TC10 expertise in diagnostics and condition monitoring, focusing on experimental applications that reveal how magnetic sensing technologies perform in practice.
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Test benches, physical simulators and reference artefacts are essential for experimental development, calibration, performance, validation and conformity assessment of biomedical measurement methods and instrumentation. Nevertheless, their metrological characterization, traceability, reproducibility and ability to represent the intended biological measurands remain open challenges.
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Non-destructive, label-free physical characterization of biological media is pivotal to advancing biomedical engineering, tissue diagnostics, and regenerative medicine. High-frequency electromagnetic and microwave sensing techniques provide unique, highly sensitive mechanisms to probe the complex dielectric signatures of biological systems across multiple structural levels—ranging from cellular suspensions and tissue scaffolds to intact organs and heterogeneous biological structures such as bone, muscle, and neural tissues.
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Building-scale remote sensing has emerged as a key research domain enabled by advances in high-resolution Earth Observation, UAV-based sensing, active and passive imaging systems, and data fusion methodologies. Modern sensing technologies allow the extraction of detailed information on building geometry, materials, energy performance, structural condition, and environmental interactions, supporting applications ranging from urban management to cultural heritage conservation and digital twin development.
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Artificial intelligence (AI) is becoming an increasingly integral component of measurement systems and processes, enabling advanced data processing, feature extraction, pattern recognition, anomaly detection, prediction, sensor fusion and automated decision-making capabilities. In application domains ranging from industrial monitoring and condition assessment to biomedical engineering and environmental measurements, AI-based methods provide opportunities to derive meaningful information from complex, high-dimensional and heterogeneous data.
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The session will focus on integrating emerging methods for evaluating measurement uncertainty in coordinate metrology with computational algorithms and mathematical models. It combines practical metrology with advanced mathematical methods, highlighting the interdisciplinary nature of the topics and the importance of sound mathematical foundations in developing modern metrological tools. The presented solutions may also be applicable to other fields of science and engineering where mathematical modelling and measurement uncertainty analysis are important.
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Modern data acquisition systems are evolving from passive digitizers into intelligent measurement nodes that are capable of making local decisions and adapting their behavior. This transformation is driven by advances in various areas, including software-defined instrumentation, classical adaptive signal processing, embedded machine learning, and edge inference.
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The digital transformation of the international quality infrastructure requires that units, quantities, values and the concepts that define them be represented in forms that machines can resolve, exchange and verify. Resolution 2 of the 27th CGPM (2022) called for an SI Digital Framework and for the adoption of the FAIR principles for metrological data and metadata.
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The transition to sustainable energy systems demands advanced metrology integrating flow and energy measurement across diverse applications. Central is accurate characterization of fluid properties, including hydrogen, energy gases and carriers, biofuels, synthetic fuels, and CO2 for capture and storage. Parameters such as density, viscosity, calorific value, composition and compressibility affect flow behaviour and energy content, requiring reliable, real-time measurement for process optimization and custody transfer.
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Multiphase systems are widespread in both engineering and biological systems. In industry, they appear as gas-liquid, liquid-solid and gas-liquid-solid flows, in energy production, chemical processing, and pipeline transportation. In living systems, they appear as blood cell suspensions, pulmonary air-tissue distributions, and perfusion through capillary networks.
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The international time and frequency community is progressing towards a future redefinition of the SI second based on optical frequency standards. This development represents one of the most significant changes to the International System of Units since the recent redefinition of the kilogram and has important implications for international timekeeping, metrological traceability and the realization of Coordinated Universal Time (UTC).
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The most ambitious experiments in fundamental physics push measurement science to its ultimate limits. Detecting a gravitational-wave strain of order 10⁻²¹, or reconstructing the trajectory of a charged particle with micrometer precision inside a multi-storey detector, demands sensors, calibration strategies, and uncertainty budgets that have no parallel in conventional metrology.
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