OWL – Opportunistic Wireless Localization

Objective

OWL provides a simple and scalable solution for indoor wireless localization and human activity monitoring of passive targets simply using the existing wireless architectures, without dedicated/expensive/customized hardware installations.

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Features

OWL runs on top of existing wireless architectures (such as WiFi Networks or Wireless Sensors Networks) processing in real-time the available wireless indicators. OWL features include:

sensor-less sensing, only the electromagnetic signal is exploited
through-wall localization thanks to the electromagnetic propagation through non-metallic objects
no privacy issues related to user identification (as for video-surveillance systems)
robustness to changes of environmental conditions (e.g., darkness, smoke, etc.)

Application fields

OWL enables location-based services where users are non-cooperative and transceiver-free. Examples of applications are:

human activity monitoring & gesture recognition
patient's breathing monitoring
flow management
intrusion detection
indoor navigation

How it works?

OWL exploits the effects of the electromagnetic interactions among electromagnetic fields and human bodies to solve the localization problem as an inverse problem.

Results - Device-Free Wireless Detection

Device-Free Wireless Detection Principle

Experimental Validation

Results - Device-Free Wireless Tracking

Device-Free Wireless Tracking Principle

Demo

Results - Posture and Gesture Recognition

Results - Breathing Rate Monitoring

References

A. Polo, F. Capra, S. Lusa, P. Rocca, A.A. Salas-Sanchez, and M. Salucci, "Machine Learning-based Inversion of Wireless Signals for Real-Time Gesture Recognition," IEEE International Conference on Modern Circuits and Systems Technologies (MOCAST), Athens, Greece, June 28-30 2023, pp. 1-3.
A. Polo, M. Salucci, S. Verzura, and A. Massa, "Real-time CSI-based wireless imaging for human-machine interaction," 2021 IEEE AP-S International Symposium and USNC-URSI Radio Science Meeting, Marina Bay Sands, Singapore, pp. 1649-1650, December 4-10, 2021.
A. Polo, M. Salucci, S. Verzura, Z. Zhou, and A. Massa, "Real-time CSI-based wireless gesture recognition for human-machine interaction," 2021 International Conference on Modern Circuits and Systems Technologies on Electronics and Communications (MOCAST 2021), Thessaloniki, Greece, July 5-7, 2021.
A. Polo, M. A. Hannan, G. Gottardi, and F. Viani, "A learning-based inversion strategy for passive wireless detection of crowds," Journal of Physics: Conference Series, vol. 1476, pp. 1-7, 2020.
G. Gottardi, M. A. Hannan, B. Li, A. Polo, M. Salucci, and F. Viani, "PCA-Based inversion of WiFi signal for robust device-free indoor target detection," Journal of Physics: Conference Series, vol. 1476, pp. 1-7, 2020.
G. Gottardi, M. A. Hannan, A. Polo, M. Salucci, and F. Viani, "Frequency-based inversion of a single wireless link for indoor passive target detection," 9th International Workshop on New Computational Methods for Inverse Problems (NCMIP 2019), Cachan, France, May 24, 2019.
F. Viani, M. D. Migliore, A. Polo, M. Salucci, and A. Massa, "An iterative classification strategy for multi-resolution wireless sensing of passive targets," Electronics Letters, vol. 54, no. 2, pp. 101-103, January 2018.
H. Ahmadi, R. Bouallegue, F. Viani, and A. Massa, "An improved prediction based strategy for target tracking in wireless sensor networks," International Journal of Internet Technology and Secured Transactions. in press, 2017.
H. Ahmadi, F. Viani, A. Polo, and R. Bouallegue, "Learning ensemble strategy for static and dynamic localization in wireless sensor networks," International Journal of Network Management, vol. 27, no. 4, pp. 1-10, July 2017.
M. Donelli and F. Viani, "Life signals detection system based on a continuous-wave X-band radar," Electronics Letters, vol. 52, no. 23, pp. 1903-1904, November 2016.
H. Ahmadi, A. Polo, T. Moriyama, M. Salucci, and F. Viani, "Semantic wireless localization of WiFi terminals in smart buildings," Radio Sci. – Special Issue on ‘Innovative Microwave Devices, Methods and Applications’, vol. 51, Jun. 2016.
F. Viani, "Opportunistic occupancy estimation in museums through wireless sensor networks," Microwave and Optical Technology Letters, vol. 57, no. 8, pp. 1975-1977, August 2015.
F. Viani, F. Robol, A. Polo, P. Rocca, G. Oliveri, and A. Massa, "Wireless architectures for heterogeneous sensing in smart home applications – Concepts and real implementations," Proc. IEEE – Special Issue on ‘The Smart Home,’ Invited Paper, vol. 101, no. 11, pp. 2381-2396, Nov. 2013.
F. Viani, P. Rocca, G. Oliveri, D. Trinchero, and A. Massa, "Localization, tracking, and imaging of targets in wireless sensor networks: An invited review," Radio Sci., Solicited Review Paper, vol. 46, RS5002, 2011.
F. Viani, P. Rocca, M. Benedetti, G. Oliveri, and A. Massa, "Electromagnetic passive localization and tracking of moving targets in a WSN-infrastructured environment," Inverse Probl. - Special Issue on “Electromagnetic Inverse Problems: Emerging Methods and Novel Applications,” vol. 26, 074003, pp. 1-15, Mar. 2010.
F. Viani, L. Lizzi, P. Rocca, M. Benedetti, M. Donelli, and A. Massa, "Object tracking through RSSI measurements in wireless sensor networks," Electron. Lett., vol. 44, no. 10, pp. 653-654, May 8, 2008.

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