7 papers
A Body-of-Revolution Human Model for RF Sensing with Measurement-Driven Calibration for Indoor Environments
Haoqing Wen, Michele D'Amico, Matteo Oldoni +5
Model training for Device-Free Localization (DFL) and Radio-Frequency (RF) sensing systems heavily relies on large-scale datasets, which are costly and time-consuming to obtain thr…
Fast Full-Wave Simulation of Indoor RSS Maps for Pre-Measurement Validation in Device-Free Localization
Federica Fieramosca, Anastasia Maiolli, Alexander H. Paulus +2
Human localization is gaining momentum in security, healthcare, logistics, and smart spaces applications. While global navigation systems are unreliable indoor, device-free (a.k.a.…
Efficient 2.5-D FEM-Based Scattering Analysis of the Human Body for RF Sensing
Haoqing Wen, Michele D'Amico, Matteo Oldoni +5
Model training for Device-Free Localization (DFL) and Radio-Frequency (RF) sensing heavily relies on large-scale datasets, which are difficult, expensive, and time-consuming to obt…
RF sensing with dense IoT network graphs: An EM-informed analysis
Federica Fieramosca, Vittorio Rampa, Michele D'Amico +1
Radio Frequency (RF) sensing is attracting interest in research, standardization, and industry, especially for its potential in Internet of Things (IoT) applications. By leveraging…
Device-Free Localization with Multiple Antenna Receivers: Simulations and Results
Vittorio Rampa, Federica Fieramosca, Stefano Savazzi +1
Device-Free Localization (DFL) is a passive radio method able to detect, estimate, and localize targets (e.g., human or other obstacles) that do not need to carry any electronic de…
Bayesian Federated Learning for Continual Training
Usevalad Milasheuski, Luca Barbieri, Sanaz Kianoush +2
Bayesian Federated Learning (BFL) enables uncertainty quantification and robust adaptation in distributed learning. In contrast to the frequentist approach, it estimates the poster…