Commit 4a4afa87 authored by Tran Huy Vu's avatar Tran Huy Vu

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We now describe the design of our RF energy harvesting based wearable device, which includes an accelerometer sensor that can be used to track an individual's movement and gestures. Figure~\ref{fig:wearablediagram} illustrates the overall component-level design of the wearable device, which contains a few key components: (a) an RF-energy harvester, a low-power microcontroller, the low-power accelerometer sensor, a wireless communication interface, a supercapacitor (to provide transient energy storage) and a power management module. Figure~\ref{fig:pcbboard} shows the eventual implementation on a PCB board.
\subsection{The RF Energy Harvester}
The RF harvester works by converting the received wireless transmissions into an output voltage. However, the output voltage usually fluctuates significantly with slight movement in the wearable device. As a result, the instantaneous power of the harvester is not strong and stable enough to operate the wearable directly. We use a boost converter BQ25570\am{what is this}, which has been commonly used in prior energy harvesting applications. This converter converts input voltage as low as 100mV to a programmable output voltage. (In our implementation, we set the output voltage at 2.57V) This output voltage is then used to operate an entire embedded system including 1 microcontroller, 1 inertial sensor and 1 RF communication front end.
The RF harvester works by converting the received wireless transmissions into an output voltage. However, the output voltage usually fluctuates significantly with slight movement in the wearable device. As a result, the instantaneous power of the harvester is not strong and stable enough to operate the wearable directly. We use a boost converter, BQ25570, which stores low voltage energy and boost it into a higher voltage for common electronic devices. This converter has been commonly used in prior energy harvesting applications. It converts input voltage as low as 100mV to a programmable output voltage. (In our implementation, we set the output voltage at 2.57V) This output voltage is then used to operate an entire embedded system including 1 microcontroller, 1 inertial sensor and 1 RF communication front end.
In our current effort, we do not focus on the development of the ``best harvester"--instead, our goal is to demonstrate the viability of the overall \name framework. Accordingly, we implement the harvester (illustratedin Figure~\ref{fig:harvester}) on a commonplace prototype PCB (FR4 material). The harvester includes a ``impedance matching network", followed by a rectifier. Moreover, we hand-tune the inductor (approximately 1 round of wire) until the resonant voltage is highest on the WiFi 802.11b channel 1 (the channel used by the WiFi AP for transmitting ``power packets" in our study). In more product-grade implementations, the harvester would need to have multiple such inductors (to allow energy harvesting across dynamically varying AP channels), and would also need to implement dynamic impedance matching (e.g.,~\cite{felini2014}).
In our current effort, we do not focus on the development of the ``best harvester"--instead, our goal is to demonstrate the viability of the overall \name framework. Accordingly, we implement the harvester (illustrated in Figure~\ref{fig:harvester}) on a commonplace prototype PCB (FR4 material). The harvester includes a ``impedance matching network", followed by a rectifier. Moreover, we hand-tune the inductor (approximately 1 round of wire) until the resonant voltage is highest on the WiFi 802.11b channel 1 (the channel used by the WiFi AP for transmitting ``power packets" in our study). In more product-grade implementations, the harvester would need to have multiple such inductors (to allow energy harvesting across dynamically varying AP channels), and would also need to implement dynamic impedance matching (e.g.,~\cite{felini2014}).
\begin{figure}[!h]
......@@ -39,7 +39,7 @@ In our current effort, we do not focus on the development of the ``best harveste
The device also contains an RF front end, to transmit the collected sensor data (and any additional `ping' packets). This is the most power-hungry component in the overall system. It consumes 11.3 mA in transmission mode (when it is actively transmitting data at 0dBm), only and 0.9 \micro A in power-down mode (when only the SPI interface is running to maintain communication with the microcontroller). Because the instantaneous RF transmission power far exceeds the harvesting capacity of the device, it is infeasible to run the device using only the instantaneous harvested power. Accordingly, the wearable device include a supercapacitor, which effectively acts as a slowly-draining energy source. We use a 0.47F super capacitor which has an equivalent series resistance of only 45mOhm as the energy storage. The capacitor is small and thin enough (21x14x3.2mm) to be integrated in a wearable device.
\subsection{The Microcontroller+ Sensor}
We utilize a commodity low-power microcontroller, the STM32L053~\cite{XXX}, which onsumes 6.6 mW power at normal operation, but only 1 \micro W power during stop mode. In stop mode, all functions of the device is stopped. The microcontroller enter deep sleep mode, but the content of RAM is preserved. The device is waken up whenever an interrupt signal is fired. In this case, when the accelerometer records enough 3 sesonds of 10-Hz data, it generates an interrupt signal to wake up the microcontroller to read the buffer. The micro controller wakes up every 3 seconds to read 60 bytes of acceleration data from accelerometer, if the accelerometer is actually active. It also wakes up at every 1.5 minutes to transfer a block of about 3KB data back to the server, using the wireless interface.
We utilize a commodity low-power microcontroller, the STM32L053~\cite{XXX}, which onsumes 6.6 mW power at normal operation, but only 1 \micro W power during stop mode. In stop mode, all functions of the device is stopped. The microcontroller enter deep sleep mode, but the content of RAM is preserved. The device is waken up whenever an interrupt signal is fired. In our system, when the accelerometer records enough data and fully stored it in a buffer, it generates an interrupt signal to wake up the microcontroller to read the buffer. The micro controller wakes up every 3 seconds to read 60 bytes of acceleration data from accelerometer, if the accelerometer is actually active. It also wakes up at every 1.5 minutes to transfer a block of about 3KB data back to the server, using the wireless interface.
Our device implementation utilizes the LIS3DHTR 3-axes accelerometer from STMicroelectronics. According to the manufacturer, this low-power sensor consumes 2 \micro A at 1 Hz, and 6 \micro A at 50Hz. For our experimental studies, we set the accelerometer sampling frequency at 10 Hz. At this frequency, the accelerometer can internally buffer 32 samples (i.e., approx. 3.2 seconds of sensor data).
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