Marco Piavanini

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About

Marco Piavanini is a leading researcher in industrial indoor positioning, with a focus on the Internet of Things (IoT) and advanced wireless technologies. His work addresses critical challenges in location-based services for autonomous robotics, industrial automation, and augmented/virtual reality. Piavanini’s major contributions include developing robust filtering techniques for mixed line-of-sight (LOS) and non-line-of-sight (NLOS) environments, as exemplified by his highly cited paper on the "Switching Model Stein Variational Sampling Filter" (2025, 2 citations). This work enhances the reliability of Ultra Wide-Band (UWB) and 5G-advanced millimeter-wave systems, which are pivotal for precise positioning in complex industrial settings. His research has garnered attention for its practical impact on real-time localization, with applications spanning smart factories and autonomous navigation. Piavanini’s achievements include advancing the state of the art in sensor fusion and Bayesian inference, making him a key figure in the evolution of industrial IoT. His work continues to inspire new approaches to resilient positioning under challenging conditions, bridging the gap between theoretical innovation and industrial deployment.