194 citations · 298 across the 15 of their papers we have counts for
15 papers
WiFi-Based People Counting Using Beam-Steerable Antennas: A Test-bed Study
Riccardo Bersan, Anay Ajit Deshpande, Sanaz Kianoush +2
Ubiquitous perception through RF signals is a pivotal opportunity for future technology: it enables personalized services such as smart living, remote healthcare, automated logisti…
A Unified Approach to Human-Scale Blockage and Scattering Analysis in Sub-THz Propagation With Application to RF Sensing
Stefano Savazzi, Fabio Paonessa, Sanaz Kianoush +2
RF sensing exploits phase-sensitive measurements of stray electromagnetic (EM) fields from wireless devices across various frequency bands to detect EM blockage and to reconstruct…
Gesture-Based Robot Control Integrating Mm-wave Radar and Behavior Trees
Yuqing Song, Cesare Tonola, Stefano Savazzi +3
As robots become increasingly prevalent in both homes and industrial settings, the demand for intuitive and efficient human-machine interaction continues to rise. Gesture recogniti…
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…
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…
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…
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…
A Framework for Energy and Carbon Footprint Analysis of Distributed and Federated Edge Learning
Stefano Savazzi, Sanaz Kianoush, Vittorio Rampa +1
Recent advances in distributed learning raise environmental concerns due to the large energy needed to train and move data to/from data centers. Novel paradigms, such as federated…
Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systems
Stefano Savazzi, Monica Nicoli, Mehdi Bennis +2
Next-generation autonomous and networked industrial systems (i.e., robots, vehicles, drones) have driven advances in ultra-reliable, low latency communications (URLLC) and computin…
Processing of body-induced thermal signatures for physical distancing and temperature screening
Stefano Savazzi, Vittorio Rampa, Leonardo Costa +2
Massive and unobtrusive screening of people in public environments is becoming a critical task to guarantee safety in congested shared spaces, as well as to support early non-invas…