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http://dx.doi.org/10.6109/jkiice.2018.22.2.284

Performance Evaluation of Statistical Methods Applicable to Estimating Remaining Battery Runtime of Mobile Smart Devices  

Tak, Sungwoo (School of Electrical and Computer Engineering, Pusan National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.22, no.2, 2018 , pp. 284-294 More about this Journal
Abstract
Statistical methods have been widely used to estimate the remaining battery runtime of mobile smart devices, such as smart phones, smart gears, tablets, and etc. However, existing work available in the literature only considers a particular statistical method. Thus, it is difficult to determine whether statistical methods are applicable to estimating thr remaining battery runtime of mobile devices or not. In this paper, we evaluated the performance of statistical methods applicable to estimating the remaining battery runtime of mobile smart devices. The statistical estimation methods evaluated in this paper are as follows: simple and moving average, linear regression, multivariate adaptive regression splines, auto regressive, polynomial curve fitting, and double and triple exponential smoothing methods. Research results presented in this paper give valuable data of insight to IT engineers who are willing to deploy statistical methods on estimating the remaining battery runtime of mobile smart devices.
Keywords
Smart devices; Statistical methods; Remaining battery runtime estimation; Regression analysis;
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Times Cited By KSCI : 1  (Citation Analysis)
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