{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Battery Consumption Analysis\n", "We perform the battery consumption analysis of proposed crowdedness detection in two scenarios using Android Historian tool [1]. In one scenario, we executed the commuter module using continuous sensing of GPS and accelerometer sensors. In the other scenario, we executed the commuter module with the opportunistic use of GPS that schedules the use of GPS based on the changes in commuter state detected using accelerometer data." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For opportunistic sensing, we changed the commuter state for four times during the trip which resulted into enabling GPS for four times. As per the observation of data collection volunteers during the collection of records for learning module, we came to the conclusion that commuter state may change for four to five times during a journey. Data collection volunteers suggested that commuter would look for a seat on boarding the bus. If the commuter does not find a seat, he/she will stand. And, whenever the commuter finds a seat they occupy it. Further, the commuter may change a seat during the journey either to occupy a seat near the window or the exit door for the ease of alighting the bus. Moreover, the commuter state would change when the commuter is to alight the bus." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import sys\n", "import os\n", "\n", "'''Import project specific library'''\n", "sys.path.append(os.path.join(os.getcwd(), 'LibCode'))\n", "import BatteryConsumption" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "'''For updating the lib changes effects'''\n", "import importlib\n", "importlib.reload(BatteryConsumption)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", "'''For directory management'''\n", "path = Path(os.getcwd())\n", "\n", "OneLevelUpPath = path.parents[0]\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "#ResultPathDir = os.path.join(os.getcwd(), 'Result','OpportunisticSensing','')\n", "ResultPathDir = os.path.join(str(OneLevelUpPath), 'results','OpportunisticSensing','')\n", "\n", "if os.path.exists(ResultPathDir) == False:\n", " os.mkdir(ResultPathDir)\n", " " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "146.97752808988753 70.0\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "BatteryConsumption.Analysis(ResultPathDir)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## References\n", "1. Analyze power use with Battery Historian – Android developers, in: Android Dev., 2019, URL https://developer.android.com/topic/performance/ power/battery-historian. (Accessed 29 December 2019)." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.9" } }, "nbformat": 4, "nbformat_minor": 2 }