Abstract
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.
Highlights
A MBIENT computing has been gaining momentum to be one of the most impactful technological developments for the decade
Our era is witnessing a rapid development in the field of human activity monitoring, indoor localization, and health care systems
While one reader antenna is usually used as both TX and RX with the impinj reader, we have proposed a different method that reduces the crosstalk between the transmitting and receiving channels and, increases the receiver’s sensitivity
Summary
A MBIENT computing has been gaining momentum to be one of the most impactful technological developments for the decade. Contactless technologies generally rely on the observation of signals generated by patients in their immediate environment It is, beneficial to scale such systems to large coverage areas in order to reduce costs. Radar systems have demonstrated high accuracy localization and real-time vital sign monitoring in scenarios involving multiple targets [8], [9]. Those solutions require expensive, dedicated systems with performance, costs, and power consumptions scaling quasiproportionally with the bandwidth and with the number of transmitters and receivers and, with angular and radial resolutions. This addition played a significant role in the optimization of the hardware setup and processing of the data before experimenting with real humans, as well as facilitating multiusers scenarios
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