Commit 6875f813 authored by U-RAJESH-SIS\rajesh's avatar U-RAJESH-SIS\rajesh

moved related work items here

parent 7908bcad
......@@ -20,3 +20,22 @@ mbient light energy (indoors) is projected to provide~\cite{yildiz2007} a harves
\textbf{Other Application Domains \& Paradigms:} Our investigations in this paper have been confined to the use of a single AP, with 1-2 users, in an office-like setting. Variations of the core \name concept may find applicability in other settings. For example, WiFi AP-based energy harvesting may be used to capture key locomotion and gesture-related behaviors (e.g., fall \& eating detection) by elderly inhabitants in smart home environments. Similarly, such WiFi harvesting may be used by static sensors, deployed in industrial sites, warehouses and offshore platforms. In such cases, the RF power may be delivered not by static WiFi APs, but by mobile drones which move around to both collect data (like a data mule) and deliver energy (like a postman). Our current experience, however, suggests that, even with the increased power efficiency of beamformed WiFi transmissions, the client devices will need to adopt an event-triggered sensing paradigm, as the energy is unlikely to be enough to sustain continuous sensing.
\subsection{Improving the Tracking}
%More recently, researchers have also investigated \emph{device-free}
%approaches, which recognize an individual's location or gestures without
%requiring the user to wear any device. As an example, the WiSee
%system~\cite{pu2013whole} proposed a technique to recognize hand gestures,
%based on the doppler shift of a transmitted signal that is captured and
%analyzed by a separate receiver device. To support operation on a single
%AP, past work~\cite{bharadia2013full,jain2011practical} has demonstrated the
%ability to achieve full-duplex RF transmission, which implies that a single
%WiFi AP's antennas can be used to both transmit and receive (the reflected
%signal) simultaneously. Using such techniques, recent approaches such as
%IndoTrack~\cite{li2017} have demonstrated how passive tracking of RF signals
%reflected by the human body can be used for localization. However, such
%device-free approaches are still not robust enough to be deployed in
%arbitrary environments, especially when multiple human occupants are
%present.
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