Commit 9da855f4 authored by Tran Huy Vu's avatar Tran Huy Vu

Initial Version

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\usepackage{booktabs} % For formal tables
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\usepackage[ruled,linesnumbered,algoruled,boxed,lined]{algorithm2e} % For algorithms
\newcommand{\vt}[1]{\todo[backgroundcolor=green,inline]{\textbf{Vu:} #1}}
% Copyright
%\acmConference[ENSsys'17]{ACM Woodstock conference}{November 2017}{Amsterdam, The Netherlands}
\keywords{Batteryless, Wearable, Beamforming, Harvesting, RF}
\title{Focusing Your Energy. Beyond WiFi-based energy harvesting for wearable device}
%\titlenote{Produces the permission block, and
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%\subtitle{Technical Report}
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%\renewcommand{\shortauthors}{Vu H. Tran et al.}
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<concept_desc>Computer systems organization~Embedded systems</concept_desc>
<concept_desc>Computer systems organization~Redundancy</concept_desc>
<concept_desc>Computer systems organization~Robotics</concept_desc>
<concept_desc>Networks~Network reliability</concept_desc>
\ccsdesc[500]{Computer systems organization~Embedded systems}
\ccsdesc[300]{Computer systems organization~Redundancy}
\ccsdesc{Computer systems organization~Robotics}
\ccsdesc[100]{Networks~Network reliability}
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\section{Experimental Results}
\subsection{Experiment Setup}
The experiment setting the the room (MR 4.5)
\subsection{Office Working Environment}
Users working at the instrumented desk for 1-2 hours. This is to capture the energy pattern when user is at the desk.
\subsection{Average Working Day}
Users working at the instrumented desk for 8 hours. This is to capture the average energy pattern.
\subsection{Overnight Charging}
\subsection{Multi-user Scenarios}
- 1 narrow beam. Time multi-plexing
- 2 concurrent wide beams.
- 3 sitting positions
\subsection{Harvested Energy without User Presence}
This is to show the potential for industrial use case where the APs power sensors.
\subsection{Energy Characteristics of the System}
- Duty cycle
- Efficiency
- Efe]fects of number of antennas
- Compare with 1 antenna USRP (if possible)
\section{System Overview}
\subsection{The RF-Powered Wearable}
\subsection{Beamforming Technique}
\subsection{RF-based Energy Harvesting}
\subsection{How to locate device location automatically?}
\section{Related Work}
Related work.
\section{System Architecture of RF-based Wearable Device}
Though RF-based energy harvesting is known to be a practical solution for IoT such as RFID tags. WiFi-based energy harvesting has been under utilized because of the low, law-regulated energy of WiFi APs. However, we prove that by carefully design the whole close-loop system, we can increase the efficiency of WiFi power transfer so that it is practical to use WiFi to power more power hungry device than RFID tags. And we show that a full wearable device with inertial sensor and RF communication interface can survive on only WiFi energy. We based our study on previous studies of RF-based energy harvesting, beamforming and Direction of Arrival.
Our intuition is that WiFi power transfer has been unefficient because the antenna emits signal omnidirectionally. This is because it does not know the direction of the device, so it has to transfer the energy into all directions, though the device is at only 1 direction.
Our system is much more efficient because it can detect the direction of the device and form a narrow beam of WiFi signal toward that direction to charge the device. Using beamforming, the energy is concentrated into some narrower areas so the available energy in those areas is much higher. To achieve this, the system needs the cooperation of the 2 main components: the WiFI AP and the device. We also explore the use of motion trigger mechanism to lower he power consumption.
\subsection{The Wearable Device}
Harvester, Power Management, Micro-controller, Accelerometer and RF communication
\subsection{The Access Point}
2 set of antenna arrays for 2 main operations: Beamforming and DoA
\subsection{Motion Trigger Mechanism}
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