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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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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. |
format | Online Article Text |
id | pubmed-4507616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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