RadioVision: wireless and sensor-less radio-based vision systems  

“It’s not difficult. Every time I lift my arm, it distorts a small electromagnetic field that is maintained continuously across the room. Slightly different positions of my hand and fingers produce different distortions and my robots can interpret these distortions as orders. I only use it for simple orders: Come here! Bring tea! and so on.” Isaac Asimov, The robots of the dawn, 1983.

Sensor-less Wireless Vision is based on the continuous monitoring of wireless signals, it is designed to perform real-time tracking of object motion (humans, robots, machines) in line-of-sight, non-line-of-sight, and through-the-wall scenarios. Subjects affect the electromagnetic field in a predictable way such that it is possible to track their movements in the space. The subjects may be actively avoiding localization, or they may be passive and not emitting any useful signals; however, a wireless network deployed to locate them may contain elements which actively transmit.


Some Applications.

- Ambient intelligence, ambient assisted living

- Shared human-robot smart spaces

- Emergency and rescue operations, patient monitoring in medical facilities

- Anti-terrorism or law enforcement

- Localization, tracking and counting people in outdoor/indoor areas of interest (e.g., home and industrial automation applications)

- Measure usage statistics in train/subway stations, buildings and stores (e.g, pedestrian traffic monitoring and modeling)

- Passenger access counting

National Research Council of Italy (Consiglio Nazionale delle Ricerche, C.N.R.): See the CNR focus.

Institute of Electronics, Computer and Telecommunication Engineering (IEIIT)

Researchers: Savazzi Stefano, Vittorio Rampa, Sanaz Kianoush. Marcello Ioppolo (FIDEAS 2013-2015).


Institute of Industrial Technologies and Automation (ITIA)

Researchers: Federico Vicentini, Nicola Pedrocchi, Matteo Giussani


Politecnico di Milano, DEIB.  Nicoli Monica, Spagnolini Umberto, Michele D’Amico, Guido Gentili


MSc/BSc Thesis. Alessandro Gallo (BSc, 2011), Michele Riva (MSc, 2012), Francesca Carminati (MSc, 2013), Matteo Giussani (MSc, 2014), Silvia Schiaroli (MSc. 2015), Chiara Manno (MSc. 2016)


Related links: Radio Tomographic Imaging , SenseWaves, WiSee,  WiVi, Xandem

Contacts (for thesis, other): Stefano Savazzi

Related Papers

S. Savazzi, S. Sigg, M. Nicoli, V. Rampa, S. Kianoush, U. Spagnolini, “Device-Free Radio Vision for assisted living: leveraging wireless channel quality information for human sensing,” IEEE Signal Processing Magazine, (pdf), vol. 33, no. 2, pp. 45-58, March 2016.


S. Savazzi, S. Sigg, M. Nicoli, V. Rampa, S. Kianoush, U. Spagnolini, “Wireless Sensing for Device-Free Recognition of Human Motion”, in “Radar for Indoor Monitoring: Detection, Localization, and Assessment”, pp. 337-363, Edited by Moeness Amin, CRC Press Taylor & Francis Group, 390 pages, ISBN10 1498781985, ISBN13 9781138746091, Sept. 14, 2017, doi: 10.1201/9781315155340


S. Savazzi, M. Nicoli, F. Carminati, M. Riva, “A Bayesian approach to Device-Free Localization: modeling and experimental assessment,” IEEE Journal on Selected Topics in Signal Processing, (pdf), vol. 8, no. 1, pp.16-29, Feb. 2014.


V. Rampa, S. Savazzi, M. Nicoli, M. D'Amico “Physical modeling and performance bounds for device-free localization systems,” IEEE Signal Processing Letters, (pdf) vol. 22 no. 11, pp.1864-1868, November 2015.


S. Savazzi, V. Rampa, F. Vicentini, M. Giussani, “Device-free human sensing and localization in collaborative human-robot workspaces: a case study,” IEEE Sensors Journal, vol. 16, no. 5, pp. 1253-1264, (pdf), March, 2016.


S. Kianoush, S. Savazzi, F. Vicentini, V. Rampa, M. Giussani, “Device-free RF human body fall detection and localization in industrial workplaces,” IEEE Internet of Things Journal, (pdf), April, 2017.


V. Rampa, G. G. Gentili, S. Savazzi, M. D’Amico, “EM models for passive body occupancy inference”, IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 16, pp. 2517-2520, 2017


S. Savazzi, S. Sigg, M. Nicoli, S. Kianoush, F. Le Gall, H. Baqa, D. Remon, A cloud-IoT model for reconfigurable radio sensing: The Radio.Sense platform,” Proc. of IEEE 4rd World Forum on Internet of Things, WF-IoT, Singapore, Feb. 2018.


S. Kianoush, S. Savazzi, V. Rampa, “Tracking of frequency selectivity for device-free detection of multiple targets,” Proc. of IEEE International Conference on Communications (ICC), France, Paris, May 2017.


V. Rampa, G. G. Gentili, S. Savazzi, M. D’Amico, “Electromagnetic models for Device-Free Localization applications”, Proc. of the IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (IEEE APWC 2017), Verona, Italy, pp. 1-4, Sept. 11-15, 2017.


S. Savazzi, S. Kianoush, V. Rampa, U. Spagnolini, “Is someone moving around my cell-phone? Tracing cellular signals for passive motion detection,” Proc. of IEEE International Conference on Pervasive Computing and Communications (PerCom), Kona, Hawaii, USA, March 2017


M. Nicoli, V. Rampa, S. Savazzi, S. Schiaroli, “Device-free Localization of Multiple Targets,” Proc. of European Signal Processing Conference (EUSIPCO), Budapest, Hungary, Sept. 2016.


S. Kianoush, V. Rampa, S. Savazzi, M. Nicoli, “Pre-deployment performance assessment of device-free radio localization systems,” (pdf) in Proc. of IEEE International Conference on Communications (ICC), Malysia, Kuala Lumpur, May 2016.


S. Savazzi, S. Kianoush, V. Rampa, “A dynamic Bayesian network approach for device-free radio vision: modeling, learning and inference for body motion recognition,” (pdf) in Proc. of IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP), Shangai, China, March 2016.


S. Kianoush, S. Savazzi, V. Rampa, “Sensor-Free Wireless Activity Recognition for Smart Retail,” in Proc. of IEEE 12th Workshop on Positioning, Navigation and Communication, Dresden, March 2015


V. Rampa, F. Vicentini, S. Savazzi, L. Pedrocchi, M. Ioppolo, M, Giussani “Safe Human-Robot Cooperation through Sensor-less Radio Localization,” in Proc. of IEEE International Conference on Industrial Informatics (INDIN 2014), Porto Alegre, Brazil, July 2014.


S. Kianoush, S. Savazzi, F. Vicentini, V. Rampa, M. Giussani, “Leveraging RF signals for human sensing: fall detection and localization in human-machine shared workspaces,” (pdf) in Proc. of IEEE International Conference on Industrial Informatics (INDIN 2015), Cambridge, U.K., July 2015.


S. Savazzi, M. Nicoli, M. Riva, “Radio Imaging by Cooperative Wireless Network: localization algorithms and experiments,” (pdf) in Proc. of IEEE Wireless Communications and Networking Conference (WCNC 2012), Paris, France, April 2012.


Localization service demo



Live Demo (ICT4All)



How it works. Small, low-cost and low-power battery-operated wireless devices are spread over an area of interest creating a dense mesh network. Objects that move within the area modify the received signal strength field, this allows to extract the location of objects within the area and track their movements.


Test-bed. As shown in the following experiments, the system analyzes the fluctuations of received signal strength over the wireless links as a basis for image reconstruction, detection and localization.


FIDEAS project.  CNR – Regione Lombardia - Testing Pilot Plant (Institute of Industrial Technologies and Automation – ITIA