LAUSR

Radio technologies are appealing for unobtrusive and remote monitoring of human activities. Radar-based human activity recognition proves to be a success, for example, Project Soli developed by Google. However, it is expensive to scale up for multiuser environments. In this article, we propose a solution—the HoloTag system—which circumvents the multichannel-radar scaling problem through the use of a quasivirtual ultralow-cost UHF RFID array over which a holographic projection of its environment is measured and used to both localize and monitor the health of several targets. The method is first described in detail, before the image reconstruction process, employing known beamforming algorithms—Delay & Sum, and Capon—is shown and its scaling properties simulated. Then, the idiosyncrasies of the implementation of HoloTag using low-cost off-the-shelf hardware are explained, before its ability to simultaneously measure the breathing rates and positions of multiple real and synthetic targets with accuracies of better than 0.8 bpm and 20 cm is demonstrated.