Prof. Neal Patwari is giving a IEEE Utah Signal Processing and Communications Chapter seminar, in WEB Room 2250, on Wednesday April 18, at 6:30pm. The talk is titled, "Radio tomography: Environmental inference from wireless network signal strength measurements".
Abstract: The received power on a link between two static wireless devices is changed when a person stands near the line those two devices. We describe multiple methods to infer a person's location in a room or building using received signal strength (RSS) changes measured in a static wireless network. We describe tomographic imaging approaches and statistical inversion methods to this problem, which we call device free localization (DFL) because the person does not participate in the system by carrying any device. We show that a person can be tracked with average errors less than 1 meter, even when using a network outside of a building to perform through-wall imaging and tracking. On some links, RSS changes even when a person is stationary, due to their inhalation and exhalation. We describe algorithms to use these changes to reliably and accurately estimate breathing rate. In summary, we describe how networks made of standard wireless devices might be used to learn characteristics of the changing environment in which they are deployed.
NOTE: The "Radio Tomography..." presentation slides are now posted.