A low-power context-aware system for smartphone using hierarchical modular bayesian networks

Jae Min Yu, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Various applications using sensors and devices on smartphone are being developed. However, since limited battery capacity does not allow to utilize the phone all the time, studies to increase use-time of phone are very active. In this paper, we propose a hybrid system to increase the longevity of phone. User's context is recognized through hierarchical modular Bayesian networks, and unnecessary devices are inferred through device management rules. Inferring the user's context using sensor data, and considering device status, context inferred and user's tendency, we determine the device which is consuming the battery most. In the experiments with the real log data collected from 28 people for six months, we evaluated the proposed system resulting in the accuracy of 85.68 % and the improvement of battery consumption of about 6 %.

Original languageEnglish
Title of host publicationHybrid Artificial Intelligent Systems - 10th International Conference, HAIS 2015, Proceedings
EditorsHéctor Quintián, Emilio Corchado, Enrique Onieva, Igor Santos, Eneko Osaba
PublisherSpringer Verlag
Pages543-554
Number of pages12
ISBN (Electronic)9783319196435
DOIs
Publication statusPublished - 2015
Event10th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2015 - Bilbao, Spain
Duration: 2015 Jun 222015 Jun 24

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume9121
ISSN (Print)0302-9743

Other

Other10th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2015
CountrySpain
CityBilbao
Period15/6/2215/6/24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yu, J. M., & Cho, S. B. (2015). A low-power context-aware system for smartphone using hierarchical modular bayesian networks. In H. Quintián, E. Corchado, E. Onieva, I. Santos, & E. Osaba (Eds.), Hybrid Artificial Intelligent Systems - 10th International Conference, HAIS 2015, Proceedings (pp. 543-554). (Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science); Vol. 9121). Springer Verlag. https://doi.org/10.1007/978-3-319-19644-2_45