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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2019

Autores

Paulo J. S. Ferreira (Autor) Outra; João M. P. Cardoso (Autor) FEUP; João Mendes Moreira (Autor) FEUP

Ata de Conferência Internacional

Título: Progress in Artificial Intelligence

Páginas: 196-207

EPIA Conference on Artificial Intelligence

Vila Real, Setembro 2019

Indexação

Scopus - 0 Citações

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12