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Battery Power Saving Profile with Learning Engine in android Phones

by Rimpy Bala, Anu Garg
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 13
Year of Publication: 2013
Authors: Rimpy Bala, Anu Garg
10.5120/11906-7983

Rimpy Bala, Anu Garg . Battery Power Saving Profile with Learning Engine in android Phones. International Journal of Computer Applications. 69, 13 ( May 2013), 38-41. DOI=10.5120/11906-7983

@article{ 10.5120/11906-7983,
author = { Rimpy Bala, Anu Garg },
title = { Battery Power Saving Profile with Learning Engine in android Phones },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 13 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 38-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number13/11906-7983/ },
doi = { 10.5120/11906-7983 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:30:12.453664+05:30
%A Rimpy Bala
%A Anu Garg
%T Battery Power Saving Profile with Learning Engine in android Phones
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 13
%P 38-41
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Android is an open platform which is becoming very popular operating system. Its open source code is easily handled by the users to get and use new contents and applications on their handsets. Android is based on Linux kernel. Android device are being activated per day and power management of these device is becoming an issue. The one problem is common that is Low battery life of the device. It is not a common thing in smartphones. Now days, more powerful with power consuming technologies like GPS, 3G and 3GS. In this approach we do not require the client server architecture . we will include a learning engine. This learning will monitor the user behavior in terms of apps used, battery consumption and contexts, and then we will collect the information for a period of time and the fed to a learning engine. Artificial neural can be used to implement the learning engine. This pattern based learning engine intelligently decide, how to control the smartphones features. This will build after the learning of user behavior, would not include any statically define power saving profile.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Battery Viewer modeling system Mobile Phones.

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