Automatic Switching Between Video and Audio According to User's Context

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Paulo J. S. Ferreira (Author) Other; João M. P. Cardoso (Author) FEUP; João Mendes Moreira (Author) FEUP

Conference proceedings International

Title: Progress in Artificial Intelligence

Pages: 196-207

EPIA Conference on Artificial Intelligence

Vila Real, Setembro 2019

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-00R-4J7

DOI: 10.1007/978-3-030-30244-3_17

Abstract (EN): Smartphones are increasingly present in human¿s life. For example, for entertainment many people use their smartphones to watch videos or listen to music. Many users, however, stream or play videos with the intention to only listen to the audio track. This way, some battery energy, which is critical to most users, is unnecessarily consumed thus and switching between video and audio can increase the time of use of the smartphone between battery recharges. In this paper, we present a first approach that, based on the user context, can automatically switch between video and audio. A supervised learning approach is used along with the classifiers K-Nearest Neighbors, Hoeffding Trees and Naive Bayes, individually and combined to create an ensemble classifier. We investigate the accuracy for recognizing the context of the user and the overhead that this system can have on the smartphone energy consumption. We evaluate our approach with several usage scenarios and an average accuracy of 88.40% was obtained for the ensemble classifier. However, the actual overhead of the system on the smartphone energy consumption highlights the need for researching further optimizations and techniques. © 2019, Springer Nature Switzerland AG.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12