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.):
http://www.cnr.it. 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 stefano.savazzi@ieiit.cnr.it
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
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Live Demo (ICT4All)
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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 (
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