activity
20182024
most citedA Multisensory Edge-Cloud Platform for Opportunistic Radio Sensing in Cobot Environments

40 citations · 54 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG20241 cited

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…

cs.NI2022

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…

eess.SP202140 cited

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…

cs.HC202013 cited

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…

cs.IT2020

Analog MIMO RoC Passive Relay for Indoor Deployments of Wireless Networks

A. Matera, V. Rampa, M. Donati +3

Most of the indoor coverage issues arise from network deployments that are usually planned for outdoor scenarios. Moreover, the ever-growing number of devices with different Radio…

eess.SP2019

Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks

Stefano Savazzi, Monica Nicoli, Vittorio Rampa

Federated learning (FL) is emerging as a new paradigm to train machine learning models in distributed systems. Rather than sharing, and disclosing, the training dataset with the se…