440 citations · 787 across the 29 of their papers we have counts for
29 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…
A Federated Learning Platform as a Service for Advancing Stroke Management in European Clinical Centers
Diogo Reis Santos, Albert Sund Aillet, Antonio Boiano +10
The rapid evolution of artificial intelligence (AI) technologies holds transformative potential for the healthcare sector. In critical situations requiring immediate decision-makin…
On the impact of the antenna radiation patterns in passive radio sensing
Federica Fieramosca, Vittorio Rampa, Stefano Savazzi +1
Electromagnetic (EM) body models based on the scalar diffraction theory allow to predict the impact of subject motions on the radio propagation channel without requiring a time-con…
Full-wave EM simulation analysis of human body blockage by dense 2D antenna arrays
Federica Fieramosca, Vittorio Rampa, Michele D'Amico +1
Recently, proposals of human-sensing-based services for cellular and local area networks have brought indoor localization to the attention of several research groups. In response t…
Physics-informed generative neural networks for RF propagation prediction with application to indoor body perception
Federica Fieramosca, Vittorio Rampa, Michele D'Amico +1
Electromagnetic (EM) body models designed to predict Radio-Frequency (RF) propagation are time-consuming methods which prevent their adoption in strict real-time computational imag…
Compressed Bayesian Federated Learning for Reliable Passive Radio Sensing in Industrial IoT
Luca Barbieri, Stefano Savazzi, Monica Nicoli
Bayesian Federated Learning (FL) has been recently introduced to provide well-calibrated Machine Learning (ML) models quantifying the uncertainty of their predictions. Despite thei…
Cooperation and Federation in Distributed Radar Point Cloud Processing
S. Savazzi, V. Rampa, S. Kianoush +2
The paper considers the problem of human-scale RF sensing utilizing a network of resource-constrained MIMO radars with low range-azimuth resolution. The radars operate in the mmWav…
An EM Body Model for Device-Free Localization with Multiple Antenna Receivers: A First Study
Vittorio Rampa, Federica Fieramosca, Stefano Savazzi +1
Device-Free Localization (DFL) employs passive radio techniques capable to detect and locate people without imposing them to wear any electronic device. By exploiting the Integrate…
A Secure and Trustworthy Network Architecture for Federated Learning Healthcare Applications
Antonio Boiano, Marco Di Gennaro, Luca Barbieri +7
Federated Learning (FL) has emerged as a promising approach for privacy-preserving machine learning, particularly in sensitive domains such as healthcare. In this context, the TRUS…
On the Impact of Data Heterogeneity in Federated Learning Environments with Application to Healthcare Networks
Usevalad Milasheuski, Luca Barbieri, Bernardo Camajori Tedeschini +2
Federated Learning (FL) allows multiple privacy-sensitive applications to leverage their dataset for a global model construction without any disclosure of the information. One of t…
A physics-informed generative model for passive radio-frequency sensing
Stefano Savazzi, Federica Fieramosca, Sanaz Kianoush +2
Electromagnetic (EM) body models predict the impact of human presence and motions on the Radio-Frequency (RF) stray radiation received by wireless devices nearby. These wireless de…
A Carbon Tracking Model for Federated Learning: Impact of Quantization and Sparsification
Luca Barbieri, Stefano Savazzi, Sanaz Kianoush +2
Federated Learning (FL) methods adopt efficient communication technologies to distribute machine learning tasks across edge devices, reducing the overhead in terms of data storage…
On the Energy and Communication Efficiency Tradeoffs in Federated and Multi-Task Learning
Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush +1
Recent advances in Federated Learning (FL) have paved the way towards the design of novel strategies for solving multiple learning tasks simultaneously, by leveraging cooperation a…
An Energy and Carbon Footprint Analysis of Distributed and Federated Learning
Stefano Savazzi, Vittorio Rampa, Sanaz Kianoush +1
Classical and centralized Artificial Intelligence (AI) methods require moving data from producers (sensors, machines) to energy hungry data centers, raising environmental concerns…
Wireless LAN sensing with smart antennas
Marco Santoboni, Riccardo Bersan, Stefano Savazzi +2
The paper targets the problem of human motion detection using Wireless Local Area Network devices (WiFi) equipped with pattern reconfigurable antennas. Motion sensing is obtained b…
Integrating Sensing and Communication in Cellular Networks via NR Sidelink
Dariush Salami, Ramin Hasibi, Stefano Savazzi +2
RF-sensing, the analysis and interpretation of movement or environment-induced patterns in received electromagnetic signals, has been actively investigated for more than a decade.…
Electromagnetic Models for Passive Detection and Localization of Multiple Bodies
Vittorio Rampa, Gian Guido Gentili, Stefano Savazzi +1
The paper proposes a multi-body electromagnetic (EM) model for the quantitative evaluation of the influence of multiple human bodies in the surroundings of a radio link. Modeling o…
A cloud-IoT platform for passive radio sensing: challenges and application case studies
Sanaz Kianoush, Muneeba Raja, Stefano Savazzi +1
We propose a platform for the integration of passive radio sensing and vision technologies into a cloud-IoT framework that performs real-time channel quality information (CQI) time…
A Multisensory Edge-Cloud Platform for Opportunistic Radio Sensing in Cobot Environments
Sanaz Kianoush, Stefano Savazzi, Manuel Beschi +2
Worker monitoring and protection in collaborative robot (cobots) industrial environments requires advanced sensing capabilities and flexible solutions to monitor the movements of t…