Multiple user recognition with passive RFID tomography

The positioning and tracing of multiple users is an important data source for ubiquitous assistance in smart environments and its superimposed intention recognition systems. Within application areas like elderly care or ambient assisted living, non-invasive, wireless, privacy preserving j technologies are indispensable. Device-free localization approaches (DFL) provide these advantages with no need for user-attached hardware. In our recent work we provide a passive RFID enabled and radio tomography based approach, which combines privacy and cost effectiveness. Within our previous proof of concepts only one user scenarios were investigated. An open problem within the DFL research is the recognition and distinction of multiple users. In this work we show related approaches and define methods and algorithms for multi user support. We conduct experiments in an indoor room DFL scenario for proof of concept and validation. We show that it is possible to recognize and distinct up to 3 users with reasonable precision.