A dataset from the daily use of features in Android devices

The energy consumption of Android devices, measured via data collection from features, is a recurring theme in the literature. To evaluate the performance of such devices, databases are generated by collecting data from features while using the Android operating system. This is a database generated using Tucandeira Data Collector from the daily use of smartphones and tablets while performing everyday tasks. The dataset contains 98 features and 10,331,114 records related to dynamic, background, list of applications, and static data. Device records were collected daily from ten distinct devices and stored in CSV files that were later organized to generate a database by cleaning and preprocessing the data that are publically available in the Mendeley Data Repository. The dataset formed an integral component of the SWPERFI RD&I Project, a research, development, and innovation initiative aimed at improving the performance and energy optimization of mobile devices. This project was undertaken at the Federal University of Amazonas.通过特征数据采集测得的安卓（Android）设备能耗，是学术文献中反复探讨的研究主题。为评估此类设备的性能，研究人员常在安卓操作系统运行场景下采集特征数据以构建数据库。本数据集是通过Tucandeira数据采集工具（Tucandeira Data Collector），在用户日常使用智能手机与平板设备完成常规任务的场景下采集构建而成。该数据集共包含98项特征与10331114条记录，涵盖动态数据、后台数据、应用程序列表数据以及静态数据四类内容。研究人员从10台不同的设备中每日采集设备运行数据，先存储为逗号分隔值（CSV）格式文件，随后通过数据清洗与预处理完成数据整理，最终构建得到可用数据库，该数据集已公开发布于Mendeley数据仓储（Mendeley Data Repository）。本数据集是SWPERFI研发创新（RD&I）项目的核心组成部分，该项目是一项旨在提升移动设备性能与能耗优化水平的研究、开发与创新计划。该项目由亚马孙联邦大学（Federal University of Amazonas）牵头实施。