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Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing

Energy consumption is a major concern in context-aware smartphone sensing. This paper first studies mobile device-based battery modeling, which adopts the kinetic battery model (KiBaM), under the scope of battery non-linearities with respect to variant loads. Second, this paper models the energy con...

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Detalles Bibliográficos
Autores principales: Yurur, Ozgur, Liu, Chi Harold, Moreno, Wilfrido
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4507616/
https://www.ncbi.nlm.nih.gov/pubmed/26016916
http://dx.doi.org/10.3390/s150612323
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author Yurur, Ozgur
Liu, Chi Harold
Moreno, Wilfrido
author_facet Yurur, Ozgur
Liu, Chi Harold
Moreno, Wilfrido
author_sort Yurur, Ozgur
collection PubMed
description Energy consumption is a major concern in context-aware smartphone sensing. This paper first studies mobile device-based battery modeling, which adopts the kinetic battery model (KiBaM), under the scope of battery non-linearities with respect to variant loads. Second, this paper models the energy consumption behavior of accelerometers analytically and then provides extensive simulation results and a smartphone application to examine the proposed sensor model. Third, a Markov reward process is integrated to create energy consumption profiles, linking with sensory operations and their effects on battery non-linearity. Energy consumption profiles consist of different pairs of duty cycles and sampling frequencies during sensory operations. Furthermore, the total energy cost by each profile is represented by an accumulated reward in this process. Finally, three different methods are proposed on the evolution of the reward process, to present the linkage between different usage patterns on the accelerometer sensor through a smartphone application and the battery behavior. By doing this, this paper aims at achieving a fine efficiency in power consumption caused by sensory operations, while maintaining the accuracy of smartphone applications based on sensor usages. More importantly, this study intends that modeling the battery non-linearities together with investigating the effects of different usage patterns in sensory operations in terms of the power consumption and the battery discharge may lead to discovering optimal energy reduction strategies to extend the battery lifetime and help a continual improvement in context-aware mobile services.
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spelling pubmed-45076162015-07-22 Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing Yurur, Ozgur Liu, Chi Harold Moreno, Wilfrido Sensors (Basel) Article Energy consumption is a major concern in context-aware smartphone sensing. This paper first studies mobile device-based battery modeling, which adopts the kinetic battery model (KiBaM), under the scope of battery non-linearities with respect to variant loads. Second, this paper models the energy consumption behavior of accelerometers analytically and then provides extensive simulation results and a smartphone application to examine the proposed sensor model. Third, a Markov reward process is integrated to create energy consumption profiles, linking with sensory operations and their effects on battery non-linearity. Energy consumption profiles consist of different pairs of duty cycles and sampling frequencies during sensory operations. Furthermore, the total energy cost by each profile is represented by an accumulated reward in this process. Finally, three different methods are proposed on the evolution of the reward process, to present the linkage between different usage patterns on the accelerometer sensor through a smartphone application and the battery behavior. By doing this, this paper aims at achieving a fine efficiency in power consumption caused by sensory operations, while maintaining the accuracy of smartphone applications based on sensor usages. More importantly, this study intends that modeling the battery non-linearities together with investigating the effects of different usage patterns in sensory operations in terms of the power consumption and the battery discharge may lead to discovering optimal energy reduction strategies to extend the battery lifetime and help a continual improvement in context-aware mobile services. MDPI 2015-05-26 /pmc/articles/PMC4507616/ /pubmed/26016916 http://dx.doi.org/10.3390/s150612323 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yurur, Ozgur
Liu, Chi Harold
Moreno, Wilfrido
Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing
title Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing
title_full Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing
title_fullStr Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing
title_full_unstemmed Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing
title_short Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing
title_sort modeling battery behavior on sensory operations for context-aware smartphone sensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4507616/
https://www.ncbi.nlm.nih.gov/pubmed/26016916
http://dx.doi.org/10.3390/s150612323
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