A dataset from the daily use of features in Android devices

Published: 21 February 2024| Version 3 | DOI: 10.17632/bpsrw76hgx.3


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 through the collection of data from features while using the Android operating system. This is a database generated from the daily use of smartphones and tablets while performing everyday tasks. The dataset contains 98 features and 5,248,296 records related to dynamic, background, list of applications, and static data. Device records were collected every day 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.


Steps to reproduce

Within the repository, there exists a Jupyter file named "readfiles.ipynb", which facilitates the visualization of each category of collected data. Accessing and executing this file locally on a computer requires the installation of Jupyter Notebook. Alternatively, users can utilize Google Colaboratory, an online tool for programming, for remote access without the need for local installation. It is imperative that the file remains within the same directory for proper functionality.


Universidade Federal do Amazonas


Software Engineering, Mobile Computing, Software Performance, Embedded System