Pre-Conference Tutorials

Light-based measurement has long been central to biosensing and imaging. Working across the UV–VIS–NIR spectrum, it occupies a particularly useful regime that combines several practical advantages. The diffraction limit of light allows for contact-free interrogation of structures down to the submicron scale, often with little to no sample preparation. At the same time, photon energies in this range are sufficient to drive a wide range of light–matter interactions—such as absorption, fluorescence, and both elastic and inelastic scattering—while remaining low enough to avoid ionization.

Optical fibers were proposed for long-distance communications about six decades ago. Soon, researchers discovered that optical fibers could also be leveraged for sensing applications. Nowadays, many optical fiber sensor configurations have matured into successful commercial products and are very competitive in terms of performance. These include gyroscopes, distributed temperature and strain sensors, and fiber Bragg grating (FBG) sensors, among others.

This tutorial explores the technology behind fibre sensing, with a particular focus on Optical Time Domain Reflectometry (OTDR) for Distributed Acoustic Sensing (DAS), and examines both established and emerging DAS applications in Intelligent Transportation Systems (ITS).

Gas sensing is becoming critical for applications ranging from gas speciation of indoor and outdoor air-quality  to monitoring of energy-assets, precision agriculture, noninvasive medical diagnostics, and security. However, conventional legacy gas sensors rely on single-output designs that struggle with drift and detection of low-concentration analytes in chemically complex environments. 

A new paradigm is emerging in sensors, especially in energy-constrained applications such as smart wearables or parallelized multi-channel systems, such as radiation detectors, which consists in the migration of processing from the digital back-end towards the analog front-end. This represents the inversion of the traditional paradigm that had progressively pushed the boundary between analog and digital closer to the front-end, moving processing in the digital domain, thus achieving more robustness and versatility. Recently, this consolidated scenario has started to change, as machine learning (ML) techniques have been establishing as preferred tools to process raw sensors signals. 

Occupancy grid mapping (OGM) is a fundamental building block in probabilistic, spatial world models that support safe navigation and decision-making in both autonomous vehicles and mobile robots. This tutorial provides a blend of OGM theory and practice, connecting Bayesian estimation principles with modern autonomy stacks. 

This tutorial explores the emerging frontier of AI-augmented electromagnetic (EM) sensing, where non-contact technologies are transforming biomedical and industrial monitoring. It demonstrates how contactless systems can enable continuous vital sign monitoring, safe inspection in hazardous environments, and detection of hidden or occluded structures. 

Vibrational spectroscopy has consistently evolved to the real-world applicability, thanks to the miniaturization of the components. Techniques such as Raman, infrared (IR) and near-infrared (NIR) spectroscopy, that once were used only in controlled laboratory settings, are now moving to portable and hand-held devices that allow the development of in field non-destructive detection tools. Moreover, integration of spectroscopy with chemometric for data pretreatment and automatized analysis of complex spectra projected vibrational spectroscopy in the realm of enabling technologies.