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\section{Related Work}
\label{sec:relatedwork}
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There has been a wide variety of related work in the broad areas of energy
harvesting, including WiFi/RF energy harvesting, low-power wearable design
and WiFi beamforming.  

%We focus on prior work around our two key concepts of
%WiFi-based energy harvesting and indoor localization.
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%Energy harvesting papers \cite{talla2017battery} and WISP platform, some commercial products
%
%Localization/Activity recognition \cite{xiong2013arraytrack} \cite{pu2013whole}
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%Passive sensing \cite{bharadia2013full} and PIR sensors
%
%Simultaneous Wireless Information and Power Transfer (SWIPT)

\subsection{Energy Harvesting for Client Devices}

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There is significant prior work on energy harvesting for wearable / embedded
devices using light, kinetic energy, thermal gradients etc.  Ambient and
solar lighting generally provides the highest amount of harvested power as
demonstrated by Heliomotes~\cite{lin2005} to power embedded devices and
Hande et. al~\cite{hande2007} to power indoor APs.  Kinetic energy is another
popular energy harvesting source that can use body movements (e.g. 
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EnergyBug~\cite{ryokai2014}), and walking (e.g.  SolePower~\cite{solepower}) to
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power ultra low power body sensors.  Thermal energy harvesting uses
temperature gradients to generate an electrical charge.  For example,
Thermes~\cite{campbell2014} used thermal harvesting to detect water usage
events in buildings while Xu et. al~\cite{xu2013}, used thermal gradients
between a shoe's insole and the external ground.  More recent work, such as
Flicker~\cite{hester2017}, provide a platform for rapid prototyping of
energy harvesting-based sensors.  Our work is complementary to these prior
methods and can be used to a) power higher power devices, and b) deployed in
environments (e.g.  dark warehouses) where other methods would not work.
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\subsection{WiFi \& RF harvesting}

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Harvesting power from wireless transmissions has also been studied and
usually requires custom-designed hardware for the goal of charging RFID tags
and devices -- with WISP~\cite{sample2008} being a very well known example
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that is used to power a variety of sensors.  PoWiFi~\cite{talla2015powering} is the work closest
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in spirit, and the precursor, to our approach. PoWiFi modifies AP firmware to transmit `power packets' (without using beamforming) on multiple free channels simultaneously, and harvests such RF energy using a matched filter on the receiver that can simultaneously harvest power across multiple channels. The authors demonstrate that such WiFi power harvesting can be used to operate low power embedded sensors at reasonably large distances (up to 20 ft away), but with relatively low duty cycles (e.g., a camera image once every 20 mins).  Using beamforming to increase energy harvesting 
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has been studied via simulations by Huang et. al~\cite{huang2016performance} and Liu et.  al~\cite{liu2014multi}.  To the
best of our knowledge, \name is the first working prototype to utilize directional WiFi transmissions and a triggered operation (of the wearable platform) to support sensing of human activities.
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\subsection{WiFi-based Localization}
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\name requires accurate tracking of a wearable, potentially mobile, device,
to perform accurate beamforming to relieve sufficient RF energy.  Prior
work, such as ArrayTrack~\cite{xiong2013arraytrack} and
Chronos~\cite{vasisht2016} have shown how to leverage active client RF
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transmissions, coupled with precise AoA computations to very precisely
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locate the client.  We use similar methods in \names. Device-free
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localization approaches, such as WiSee~\cite{pu2013whole}, and single AP
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methods, such as Bharadia et. al~\cite{bharadia2013full}, Jain et.
al~\cite{jain2011practical}, and  IndoTrack~\cite{li2017} were also
considered. But they were not robust enough for our arbitrary deployment
environment with multiple human occupants.
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%\subsection{Simultaneous Wireless Information and Power Transfer (SWIPT)}
%\am{Jie--can you add a little text and some references here?}